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Author SHA1 Message Date
Jeremy Kidwell 410eeadd2c fixed final bits 2022-03-05 17:05:31 +00:00
Jeremy Kidwell f879cc7d3d final fixes to conversion over to sf() and tidyverse 2022-03-05 08:44:38 +00:00
Jeremy Kidwell 6149e7212f fixed table 2022-03-04 15:13:35 +00:00
Jeremy Kidwell 0747180e54 finished transition to sf() 2022-03-04 14:54:43 +00:00
Jeremy Kidwell deb05acd7a added ragg(), removed unnecessary font libraries, streamlined crs loading 2022-03-04 11:18:42 +00:00
Jeremy Kidwell d83f3b1f43 added files 2020-03-26 18:11:34 +00:00
Jeremy Kidwell 099bed2021 added files 2020-03-26 18:09:35 +00:00
Jeremy Kidwell 61f39ecd34 updated readme 2020-03-26 18:08:49 +00:00
kidwellj 89c9a2a5a4 Merge branch 'master' of https://github.com/kidwellj/mapping_environmental_action 2020-03-10 19:40:08 +00:00
kidwellj 6a531782d3 Resolved issue #3 migrated all operations away from sp() to sf(). Installed renv snapshot. Merged in changes in staging file mapping_draft-hpc_optimised_wilderness.Rmd. 2020-03-10 19:39:51 +00:00
kidwellj def2fa4178 Resolved issue #2 migrated all operations away from sp() to sf(). Installed renv snapshot. Merged in changes in staging file mapping_draft-hpc_optimised_wilderness.Rmd. 2020-03-10 19:35:20 +00:00
kidwellj 44c25d89f7 Updating scripts, added license, contributor guidelines, shifting TODO lines to github issues 2020-03-08 12:20:20 +00:00
Jeremy Kidwell ec980c423d fixed error in ecs sssi table, added calc for pubs and grocery stores to other wilderness categories 2019-03-28 09:36:31 +00:00
Jeremy Kidwell 5fdf5cad8b quick fix to length calc on pubs for sssi table 2019-03-27 12:59:48 +00:00
Jeremy Kidwell 6a90c64a31 added qgis viz and additional sbatch 2019-03-27 12:34:54 +00:00
Jeremy Kidwell 16ed7fcd9b added wilderness specific script, extra poi 2019-03-27 12:23:09 +00:00
Jeremy Kidwell 659e32e38b added wilderness specific script, extra poi 2019-03-27 12:21:41 +00:00
Jeremy Kidwell d16a0709b2 added wilderness specific script, extra poi 2019-03-27 12:08:16 +00:00
Jeremy Kidwell 30510c7cc8 tweaking plots and tables for scenic areas 2019-03-26 12:19:01 +00:00
Jeremy Kidwell c9e38785ab minor tweaks to htpc setup 2019-03-25 19:23:00 +00:00
Jeremy Kidwell fcb586bac4 minor tweaks to htpc setup 2019-03-25 19:19:56 +00:00
Jeremy Kidwell 25dc685a36 changed name of optimised file 2019-03-25 13:46:15 +00:00
Jeremy Kidwell e814b05bf1 finalised hpc version, added calc for scenicareas 2019-03-25 13:30:35 +00:00
Jeremy Kidwell c76f9df02e testing hpc version, ctd 2019-03-25 11:50:39 +00:00
Jeremy Kidwell a8eee81490 testing hpc version, ctd 2019-03-25 11:47:30 +00:00
Jeremy Kidwell c39b197676 testing hpc version, ctd 2019-03-25 11:43:29 +00:00
Jeremy Kidwell f54e97d661 Merge branch 'master' of https://github.com/kidwellj/mapping_environmental_action 2019-03-25 11:29:02 +00:00
Jeremy Kidwell 9a8934935a testing hpc version 2019-03-25 11:28:48 +00:00
Jeremy Kidwell 43d28bac27 testing hpc version 2019-03-25 11:27:49 +00:00
Jeremy Kidwell a99b361523 added quite note re parallel() 2019-03-14 19:07:50 +00:00
Jeremy Kidwell a6f95cc20a added quite note re parallel() 2019-03-14 19:04:47 +00:00
Jeremy Kidwell 98ef3822bc rm sssi data from repo 2019-03-11 09:39:31 +00:00
Jeremy Kidwell 69beb33a38 added sssi and wildland data to repo 2019-03-11 09:36:43 +00:00
Jeremy Kidwell 01698552a8 added admin_lev2_population data set 2019-03-11 09:22:35 +00:00
Jeremy Kidwell 107ae69bfb final fixes on CRS, completed inset maps 2019-03-01 14:23:14 +00:00
Jeremy Kidwell 2acd7999fd final fixes on CRS, completed inset maps 2019-03-01 14:22:45 +00:00
Jeremy Kidwell 15c4c480c3 added sf class measurements, further inset work 2019-02-28 17:00:28 +00:00
Jeremy Kidwell de4a4afb51 fixed crs issues with sf and final draft of inset map for urbanrural 2019-02-28 10:53:30 +00:00
Jeremy Kidwell 756489ac15 small tweaks 2019-02-28 08:51:09 +00:00
Jeremy Kidwell cd72f06380 tidied up use of crs, early work on inset maps 2019-02-27 18:55:06 +00:00
Jeremy Kidwell a25025e65c successful knit 2019-02-23 07:00:04 +00:00
Jeremy Kidwell a2f61ea299 fixed tables 2019-02-22 18:21:35 +00:00
Jeremy Kidwell 1e8f91a3be fixed tmap choropleth charts 2019-02-22 10:34:53 +00:00
Jeremy Kidwell bf95175bb9 fixed tmap choropleth charts 2019-02-22 10:25:31 +00:00
Jeremy Kidwell f1aa12618a added calculations for normalising against admin_lev2 2019-02-22 10:06:08 +00:00
Jeremy Kidwell b660cb5116 shrinking lines on figure 1 2019-02-17 20:36:27 +00:00
Jeremy Kidwell 603430907c adapting figure1, fine tuning 2019-02-17 18:59:31 +00:00
Jeremy Kidwell 352c0b46e9 small fix 2019-02-17 18:46:04 +00:00
Jeremy Kidwell c0a8a42b50 fixed small error 2019-02-17 15:20:23 +00:00
Jeremy Kidwell 4fcb4b076c merged plots 1/2, updated styling on tmap plots 2019-02-16 22:34:13 +00:00
Jeremy Kidwell 880f0250d0 implemented tmap, renumbered figures, other small fixes 2019-02-16 14:37:31 +00:00
Jeremy Kidwell d037b23058 swapping out ggplot for tmap 2019-02-15 21:01:32 +00:00
Jeremy Kidwell c24f041a97 removed wip 2019-02-14 18:08:05 +00:00
Jeremy Kidwell 328f58e69a fixed small errors, compiled rmd successfully 2019-02-14 16:07:12 +00:00
Jeremy Kidwell 15e6302472 commenting out lines for experimental plots 2019-02-13 23:42:43 +00:00
Jeremy Kidwell 8d3046fb47 fixed plots and tables, switching to tmap 2019-02-13 23:38:24 +00:00
Jeremy Kidwell 391f893765 adding plots with simplification 2019-02-08 21:58:18 +00:00
Jeremy Kidwell d353964221 tweaking calculations 2019-02-08 17:41:47 +00:00
Jeremy Kidwell e74a9b7447 Merge branch 'master' of git@github.com:kidwellj/mapping_environmental_action.git 2019-02-08 09:44:51 +00:00
Jeremy Kidwell d46588f4f1 adding routines 2019-02-08 09:44:08 +00:00
Jeremy Kidwell 424a2d07c2 fixed colours and tables 2019-02-07 16:47:56 +00:00
Jeremy Kidwell b9f667fb47 fixed colours and tables 2019-02-07 16:46:13 +00:00
Jeremy Kidwell 67ad41cb8b removed ds_store" 2019-02-07 08:28:16 +00:00
Jeremy Kidwell a5eb08c372 small fixes for kables, added html and figures to repo 2019-02-07 08:27:10 +00:00
Jeremy Kidwell 47605c147f switching to kable for tables 2019-02-06 13:06:20 +00:00
28 changed files with 3712 additions and 3529 deletions

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# Contributor Code of Conduct
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8
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@ -0,0 +1,8 @@
html:
Rscript -e 'library(rmarkdown); rmarkdown::render("mapping_draft.Rmd", "html_document")'
hpc:
Rscript -e 'library(rmarkdown); rmarkdown::render("mapping_draft-hpc_optimised.Rmd", "html_document")'
pdf:
Rscript -e 'library(rmarkdown); rmarkdown::render("./mapping_draft.Rmd", "pdf_document")'

View file

@ -1,10 +1,12 @@
# Mapping Environmental Action # Mapping Environmental Action
## A Welcome For the Uninitiated ## This code is associated with a scholarly paper "Mapping Environmental Action" (currently unpublished). In the paper, I draw on original data gathered from my research with Eco-groups in Scotland (2013-2017) in order to do comparative geospatial analysis of the coincidence of these groups with a number of standard demographics. You can read (an unpublished version of) the paper at (http://mapenvcom.jeremykidwell.info/mapping_draft.html).
If you're new to github and reproducible research, welcome! It's nice to have you here. Github is ordinarily a place where software developers working on open source software projects deposit their code as they write software collaboratively. However, in recent years a number of scholarly researchers, especially people working on research which involves a digital component (including me!) have begun to deposit their papers in these same software repositories. The idea here is that you can download all of the source-code and data used in this paper alongside the actual text, run it yourself and ["reproduce" the results](http://kbroman.org/steps2rr/). This can serve as a useful safeguard, a layer of research transparency, and a cool teaching tool for other persons interested in doing similar work. ## Why Reproducible Research? ##
Eschewing proprietary, expensive and unreliable software like Microsoft Word, I write in a combination of two languages: (1) [Markdown](https://en.wikipedia.org/wiki/Markdown) which is intended to be as close as possible to plain text while still allowing for things like boldfaced type, headings and footnotes; and (2) a programming language called [R](https://en.wikipedia.org/wiki/R_(programming_language)) to do all the data analysis. R is an object oriented language which was specifically designed for statistical analysis. It's also great fun to tinker with. As you look through this paper, you'll see that R code is integrated into the text of the document. This is indicated by a series of three backticks (```). There is a formal specification now at a mature stage of development, which is RMarkdown. You can read semi-official specification [for this here](https://bookdown.org/yihui/rmarkdown/pdf-document.html). If you're new to github and reproducible research, welcome! It's nice to have you here. Github is ordinarily a place where software developers working on open source software projects deposit their code as they write software collaboratively. However, in recent years a number of scholarly researchers, especially people working on research that involves a digital component (including me!) have begun to deposit their papers in these same software repositories. The idea is that you can download all of the source-code and data used in this paper alongside the actual text, run it yourself and ["reproduce" the results](http://kbroman.org/steps2rr/). This can serve as a useful safeguard, a layer of research transparency, and a cool teaching tool for other persons interested in doing similar work. Particularly when, as is the case in subject areas that are only just starting to get involved in the digital humanities, like religious studies, there is a dearth of work of this nature, it can be helpful to have examples of practice which can be reused, or at least used as an example.
Eschewing proprietary, expensive and unreliable software like Microsoft Word, I write in a combination of two languages: (1) [Markdown](https://en.wikipedia.org/wiki/Markdown) which is intended to be as close as possible to plain text while still allowing for things like boldfaced type, headings and footnotes; and (2) a programming language called [R](https://en.wikipedia.org/wiki/R_(programming_language)) to do all the data analysis. R is an object oriented language that was specifically designed for statistical analysis. It's also great fun to tinker with. As you look through this paper, you'll see that R code is integrated into the text of the document. This is indicated by a series of three backticks (```). There is a formal specification now at a mature stage of development, which is RMarkdown. You can read semi-official specification [for this here](https://bookdown.org/yihui/rmarkdown/pdf-document.html).
To read a bit more on these things and start on your own path towards plain text reproducible research, I highly recommend: To read a bit more on these things and start on your own path towards plain text reproducible research, I highly recommend:
- Karl Broman's guide, "[Initial Steps Toward Reproducible Research](http://kbroman.org/steps2rr/)" - Karl Broman's guide, "[Initial Steps Toward Reproducible Research](http://kbroman.org/steps2rr/)"
@ -12,19 +14,22 @@ To read a bit more on these things and start on your own path towards plain text
The other advantage of putting this paper here is that readers and reviewers can suggest changes and point out errors in the document. To do this, I recommend that you create a github issue by clicking on the green "New issue" button [here](https://github.com/kidwellj/mapping_environmental_action/issues). If you must, you can also send me emails. More stuff about me [can be found here](http://jeremykidwell.info). The other advantage of putting this paper here is that readers and reviewers can suggest changes and point out errors in the document. To do this, I recommend that you create a github issue by clicking on the green "New issue" button [here](https://github.com/kidwellj/mapping_environmental_action/issues). If you must, you can also send me emails. More stuff about me [can be found here](http://jeremykidwell.info).
To skip ahead and start reading the actual paper, click on [`mapping_draft.rmd`](https://github.com/kidwellj/mapping_environmental_action/blob/master/mapping_draft.Rmd) above. To skip ahead and start reading the actual paper in raw format, click on [`mapping_draft.rmd`](https://github.com/kidwellj/mapping_environmental_action/blob/master/mapping_draft.Rmd) above. If you were looking for the article (without code) you can also find a working draft here: (http://mapenvcom.jeremykidwell.info/mapping_draft.html).
Now for... Now for...
## The quick technical version ## ## The technical version ##
This repository contains the code and writing towards a (working draft of a) scholarly paper which presents my analysis of the geospatial footprint of eco-groups in the UK. This is based on research I have been conducting since 2013 and which is ongoing. The paper is written in R Markdown and for the most part, I'm using the conventions outlined by Kieran Healy [here](https://kieranhealy.org/blog/archives/2014/01/23/plain-text/) and is best viewed (I think) in [R Studio](https://www.rstudio.com) though it will be reasonably comprehensible to anyone using a Markdown editor. If I'm not working in RStudio, I'm probably in Sublime text, FYI. Co-authors and collaborators take note, generally, I use [Hadley Wickham's venerable R Style Guide](http://adv-r.had.co.nz/Style.html). This repository contains the code and writing towards a (working draft of a) scholarly paper that presents my analysis of the geospatial footprint of eco-groups in the UK. This is based on research I have been conducting since 2013 and that is ongoing. The paper is written in R Markdown and for the most part, I'm using the conventions outlined by Kieran Healy [here](https://kieranhealy.org/blog/archives/2014/01/23/plain-text/) and is best viewed (I think) in [R Studio](https://www.rstudio.com) though it will be reasonably comprehensible to anyone using a Markdown editor. If I'm not working in RStudio, I'm probably in Sublime text, FYI. Co-authors and collaborators take note, generally, I use [Hadley Wickham's venerable R Style Guide](http://adv-r.had.co.nz/Style.html).
I'd be extremely happy if someone found errors, or imagined a more efficient means of analysis and either reported them as an issue on this github repository or sent me an email. I'd be extremely happy if someone found errors, or imagined a more efficient means of analysis and either reported them as an issue on this github repository or sent me an email.
The actual article is in `mapping_draft.Rmd`. The actual article is in `mapping_draft.Rmd` and can be compiled using knitr (assuming you have R installed as well as required packages) using the `Makefile` provided.
Paths in this folder are used mostly for R processing. Towards this end folders have the following significance: Note: actual execution may take over an hour, as calls to `st_buffer` and `st_within` under `wilderness_data_prep` are computationally intensive. To compile more briskly, I recommend you comment out this final section and knit the markdown/html files. I have been relying on the University of Birmingham supercomputing cluster for execution, which has resulted in a parallel version of this script `mapping_draft-hpc_optimised.Rmd`. The latter will only run on the BlueBEAR cluster at UOB, though other scholars may want to consult this script to get a sense of how geospatial operations can be parallelised for more efficient execution.
Paths in this folder are used mostly for R processing. I'm using a "project" oriented workflow, on which you can read more [in a blog by Jenny Bryan here](https://www.tidyverse.org/blog/2017/12/workflow-vs-script/). This uses the R package [here](https://cran.r-project.org/web/packages/here/index.html).
Towards this end folders have the following significance:
- `data` contains datasets used for analysis. - `data` contains datasets used for analysis.
- `derived_data` contains files which represent modified forms of files in the above path. - `derived_data` contains files which represent modified forms of files in the above path.
@ -32,3 +37,46 @@ Paths in this folder are used mostly for R processing. Towards this end folders
- `cache` isn't included in github but is usually used for working files - `cache` isn't included in github but is usually used for working files
Note: none of the contents of the above are included in the github repository unless they are unavailable from an external repository. Note: none of the contents of the above are included in the github repository unless they are unavailable from an external repository.
## And, a few notes for the data scientists
Over the course of this research project (since 2013, really), the state of geospatial tools for datascience in R (and python) has shifted and the increased attention and resources that have been brought to bear on geospatial has resulted in a dramatic improvement in the quality and precision of tools available, particularly the development of SimpleFeatures and the [sf](https://github.com/r-spatial/sf) and [tmap](https://github.com/mtennekes/tmap) packages for R. Ggplot2 is awesome, but starts to creak quickly when you push it in more creative geospatial directions. There are also inefficiencies with data handling in some of the older packages (such as sp) that aren't apparent until you start working with large datasets. Underlying data formats have been shifting quite a lot as well, from csvt and [very problematic and proprietary ESRI shapefiles](http://switchfromshapefile.org/) to geojson/topojson and [Geopackage](http://switchfromshapefile.org/#geopackage) formats. The result of this has a need to completely rewrite this script mid-way through the research process. I've left some of the messy bits in with as comprehensive comments as possible to give a sense of things, but there remain some bits which are accidentally messy.
There are a few aspects of this code which are novel or were difficult that I'm proud of, which I hope may be useful and on ehich I'd especially value
- The use of sf() and tmap()
- The creation of vignettes for visualisations
- The level of reproducibility
- Optimisation of intensive geospatial operations for htpc and parallel computing
# Prerequisites for reproducing this codebase
I've tried to follow best practices in setting up this script for reproducibility, but given some of the choices I've had to make computationally (e.g. running some operations in PostGIS) some setup is required before execution will be successful.
These steps are:
1. Acquire a working installation of R (and RStudio). I have produced a Docker container that replicates the environment I have used to execute this script that is probably the easiest way to complete this task.
2. Set up a working Postgres database with PostGIS extensions installed. The script will download necessary data and load it into your database if it is not already in place.
3. Install platform appropriate prerequisites for the R odbc() package, see here: [https://github.com/r-dbi/odbc#installation]
4. Configure a local `config.yml` file with the following information (used to connect to your PostGIS database):
```
default:
datawarehouse:
driver: 'Postgres'
server: 'change.to.yourserver.com'
uid: 'change-to-your-username'
pwd: 'change-to-your-password'
port: 5432
database: 'database-name'
```
5. Clone or download the code from this repository
6. Set up a proper R/RStudio working environment. I use the `renv` package to manage working environment, which takes snapshots and stores them to `renv.lock`. If you run `renv::restore()` in R after loading this code, it will install necessary libraries at proper versions.
7. Nearly all of the data used in this study is open, with one exception, that of the Ordnance Survey PointX data product. This is available to most UK academics via the EDINA service, so the user will need to manually download this data and place it in the `/data/` directory.
# Contributing
Please note that this project is released with a [Contributor Code of Conduct](CODE_OF_CONDUCT.md). By contributing to this project, you agree to abide by its terms.
# License
The content of this research paper are licensed under the [Creative Commons Attribution-ShareAlike 4.0 International Public License](https://creativecommons.org/licenses/by-sa/4.0/legalcode), and the underlying source code used to generate the paper is licensed under the [GNU AGPLv3](https://www.gnu.org/licenses/agpl-3.0.en.html) license. Underlying datasets designed as part of this research have their own licenses that are specified in their respective repositories.

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This script is a work in progress! In a spirit of open-ended collaboration and a continuous development cycle, I've collected aspirations towards improvement here in this file. There is a list of urgent tasks which need to be completed before the research is complete, and a batch of subsequent work which, while not necessary, can improve and extend the work here.
# Pre-pub changes todo:
Optimising for command-line use of knitr:
- [ ] fix issues preventing simultaneous output towards PDF/md, see [here](https://stackoverflow.com/questions/23621012/display-and-save-the-plot-simultaneously-in-r-rstudio) Related to problems with colliding knitr preferences for each document type
Complete transition away from sp() to sf()
- [ ] remove use of sp(), rgdal(), GISTools(), rgeos() and commands: readOGR, spTransform, poly.counts, prop.table
- [ ] remove use of ggplot2 (in favour of tmap)
Code changes:
- [ ] Shift intensive geospatial analysis using sf() within R to operations within PostGIS per https://www.r-bloggers.com/interact-with-postgis-from-r/ and https://rviews.rstudio.com/2019/03/21/how-to-avoid-publishing-credentials-in-your-code/
- [ ] Shift to "projects" as per (https://www.tidyverse.org/blog/2017/12/workflow-vs-script/)
- [ ] Set up conventions (per https://annakrystalli.me/talks/r-in-repro-research-dc.html#58) and
- [ ] Shift appendices to compendium
Streamline code:
- [ ] Merge htpc and wilderness versions back into main draft streamline drafts
note: htpc version created 25 Mar 2019, commit 9a8934935a57c4e9790b7c420eef7454d3fb7326; wilderness mods include pub data line 373 and lines 480ff
- [ ] remove "cuts" versions
Process oriented tasks:
- [ ] Install and use [ReDoc](https://github.com/noamross/redoc/blob/master/README.md) for reversible conversion to docx
- [ ] Consider implementing [knitcitations](https://github.com/cboettig/knitcitations)
- [ ] Install and use [here](https://here.r-lib.org/)
- [ ] Install and use [renv](https://rstudio.github.io/renv/)
Underlying data work:
- [ ] Convert shapefiles and csv to geopackages or geojson

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# Future changes (post-publication) to consider:
Spin off replicable operations into functions or packages:
- [ ] Ingest OrdnanceSurvey open data
- [ ] ProcessPubs, ProcessPlacesofWorship
- [ ] Ingest geolytics grocery store data
Clip shapes to buildings in admin plots, using st_difference
- [ ] 01_admin_ecs_choropleth
- [ ] 02_admin_ecs_normed_choropleth

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PROJCS["OSGB_1936_British_National_Grid",GEOGCS["GCS_OSGB 1936",DATUM["D_OSGB_1936",SPHEROID["Airy_1830",6377563.396,299.3249646]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",49],PARAMETER["central_meridian",-2],PARAMETER["scale_factor",0.9996012717],PARAMETER["false_easting",400000],PARAMETER["false_northing",-100000],UNIT["Meter",1]]

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<?xml version="1.0" encoding="utf-8"?>
<MD_Metadata xmlns="http://www.isotc211.org/2005/gmd"
xmlns:gco="http://www.isotc211.org/2005/gco"
xmlns:gts="http://www.isotc211.org/2005/gts"
xmlns:srv="http://www.isotc211.org/2005/srv"
xmlns:gml="http://www.opengis.net/gml"
xmlns:xlink="http://www.w3.org/1999/xlink"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<language>
<LanguageCode codeList="http://www.loc.gov/standards/iso639-2/php/code_list.php"
codeListValue="eng"
codeSpace="ISO639-2">eng</LanguageCode>
</language>
<characterSet>
<MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode"
codeListValue="utf8"
codeSpace="ISOTC211/19115">utf8</MD_CharacterSetCode>
</characterSet>
<hierarchyLevel>
<MD_ScopeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ScopeCode"
codeListValue="dataset"
codeSpace="ISOTC211/19115">dataset</MD_ScopeCode>
</hierarchyLevel>
<hierarchyLevelName>
<gco:CharacterString>dataset</gco:CharacterString>
</hierarchyLevelName>
<contact>
<CI_ResponsibleParty>
<individualName>
<gco:CharacterString>Geographic Information Group</gco:CharacterString>
</individualName>
<organisationName>
<gco:CharacterString>Scottish Natural Heritage</gco:CharacterString>
</organisationName>
<positionName>
<gco:CharacterString>Data Supply</gco:CharacterString>
</positionName>
<contactInfo>
<CI_Contact>
<phone>
<CI_Telephone>
<voice>
<gco:CharacterString>01463 725000</gco:CharacterString>
</voice>
</CI_Telephone>
</phone>
<address>
<CI_Address>
<deliveryPoint>
<gco:CharacterString>Great Glen House</gco:CharacterString>
</deliveryPoint>
<city>
<gco:CharacterString>Inverness</gco:CharacterString>
</city>
<postalCode>
<gco:CharacterString>IV3 8NW</gco:CharacterString>
</postalCode>
<electronicMailAddress>
<gco:CharacterString>data_supply@nature.scot</gco:CharacterString>
</electronicMailAddress>
</CI_Address>
</address>
</CI_Contact>
</contactInfo>
<role>
<CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
codeListValue="distributor"
codeSpace="ISOTC211/19115">distributor</CI_RoleCode>
</role>
</CI_ResponsibleParty>
</contact>
<dateStamp>
<gco:Date>2014-06-20</gco:Date>
</dateStamp>
<metadataStandardName>
<gco:CharacterString>ISO 19139 Geographic Information - Metadata - Implementation Specification</gco:CharacterString>
</metadataStandardName>
<metadataStandardVersion>
<gco:CharacterString>2007</gco:CharacterString>
</metadataStandardVersion>
<spatialRepresentationInfo>
<MD_GridSpatialRepresentation>
<numberOfDimensions gco:nilReason="missing"/>
<axisDimensionProperties>
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<TD WIDTH="100%" ROWSPAN="2">
<H1>Wild land areas 2014</H1>
<P><B>Responsible organisation: </B>Scottish Natural Heritage
</P>
<P><B>Metadata last updated: </B>2014-06-20
</P>
</TD>
</TR>
<TR class="noprint">
<TD class="smalltext" valign="bottom" align="left">Internal stylesheet for geo.View<br>To export please <A href="#" onClick="top.print()">print to PDF</A></TD>
</TR>
</TABLE>
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<div id="dataIdSection">
<H2 class="desc-background">Data Description (What?)</H2>
<H3>Alternate titles</H3>
<p>Wild_land_areas_v4</p>
<p>Dataset name: GIS_SNH_OWNER.WLA_2014</p>
<H3>Reference date(s)</H3>
<p> 2014-03-31
- creation
</p>
<H3>Abstract</H3>
<div><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The data contains boundaries of Wild Land Areas in Scotland as determined by their level of naturalness, remoteness, ruggedness and lack of built modern artefacts. Boundaries should be considered as fuzzy rather than definitive to reflect the transitional nature of wild land. It is an updateand replacementto the previously published Core Areas of Wild Land(CAWL)produced in 2013. Note that the areas have been renumbered sequentially and differ from those on the CAWL map.</SPAN><SPAN>For more information </SPAN><SPAN>visit</SPAN><SPAN>https://www.nature.scot/professional-advice/landscape-change/landscape-policy-and-guidance/landscape-policy-wild-land</SPAN></P></DIV></DIV></DIV></div>
<P class="noprint" align="right"><A HREF="#Top">Back to Top</A></P>
<H2 class="cont-background">Contact information (Who?)</H2>
<DIV class="contactInfo">
<TABLE>
<TR>
<TD valign="top" width="180" nowrap><B>Role: </B> pointOfContact
</TD>
<TD style="font-weight:bold;">
<LI><SPAN class="thin">Individual's name </SPAN>Catherine Harry
</LI>
<LI><SPAN class="thin">Contact's position </SPAN>Policy & Advice Officer / Landscape Adviser
</LI>
<LI><SPAN class="thin">Organization </SPAN>Scottish Natural Heritage
</LI>
<TABLE border="0" cellspacing="0" cellpadding="0">
<TR>
<TD width="150">Telephone</TD>
<TD>+44 01463 725098</TD>
</TR>
<TR>
<TD width="150">E-mail address</TD>
<TD><a href="mailto:catherine.harry@nature.scot">catherine.harry@nature.scot</a></TD>
</TR>
<TR>
<TD width="150">Delivery point</TD>
<TD>Great Glen House, Leachkin Road</TD>
</TR>
<TR>
<TD width="150">City</TD>
<TD>Inverness</TD>
</TR>
<TR>
<TD width="150">Postal code</TD>
<TD>IV3 8NW</TD>
</TR>
<TR>
<TD width="150">Country</TD>
<TD>United Kingdom</TD>
</TR><BR></TABLE>
</TD>
</TR>
</TABLE>
</DIV>
<HR>
<DIV class="contactInfo">
<TABLE>
<TR>
<TD valign="top" width="180" nowrap><B>Role: </B> custodian
</TD>
<TD style="font-weight:bold;">
<LI><SPAN class="thin">Individual's name </SPAN>Simon Brooks
</LI>
<LI><SPAN class="thin">Contact's position </SPAN>Policy & Advice Manager - Landscape
</LI>
<LI><SPAN class="thin">Organization </SPAN>Scottish Natural Heritage
</LI>
<TABLE border="0" cellspacing="0" cellpadding="0">
<TR>
<TD width="150">Telephone</TD>
<TD>+44 01463 725000</TD>
</TR>
<TR>
<TD width="150">E-mail address</TD>
<TD><a href="mailto:simon.brooks@nature.scot">simon.brooks@nature.scot</a></TD>
</TR>
<TR>
<TD width="150">Delivery point</TD>
<TD>Great Glen House, Leachkin Road</TD>
</TR>
<TR>
<TD width="150">City</TD>
<TD>Inverness</TD>
</TR>
<TR>
<TD width="150">Postal code</TD>
<TD>IV3 8NW</TD>
</TR>
<TR>
<TD width="150">Country</TD>
<TD>United Kingdom</TD>
</TR><BR></TABLE>
</TD>
</TR>
</TABLE>
</DIV>
<HR>
<DIV class="contactInfo">
<TABLE>
<TR>
<TD valign="top" width="180" nowrap><B>Role: </B> originator
</TD>
<TD style="font-weight:bold;">
<LI><SPAN class="thin">Individual's name </SPAN>Duncan Blake
</LI>
<LI><SPAN class="thin">Contact's position </SPAN>GI Analyst
</LI>
<LI><SPAN class="thin">Organization </SPAN>Scottish Natural Heritage
</LI>
<TABLE border="0" cellspacing="0" cellpadding="0">
<TR>
<TD width="150">Telephone</TD>
<TD>+44 01224 266502</TD>
</TR>
<TR>
<TD width="150">E-mail address</TD>
<TD><a href="mailto:duncan.blake@nature.scot">duncan.blake@nature.scot</a></TD>
</TR>
<TR>
<TD width="150">Delivery point</TD>
<TD>Inverdee House, Baxter Street, Torry</TD>
</TR>
<TR>
<TD width="150">City</TD>
<TD>Aberdeen</TD>
</TR>
<TR>
<TD width="150">Postal code</TD>
<TD>AB11 9QA</TD>
</TR>
<TR>
<TD width="150">Country</TD>
<TD>United Kingdom</TD>
</TR><BR></TABLE>
</TD>
</TR>
</TABLE>
</DIV>
<DIV class="contactInfo">
<TABLE>
<TR>
<TD valign="top" width="180" nowrap><B>Role: </B> pointOfContact
</TD>
<TD style="font-weight:bold;">
<LI><SPAN class="thin">Individual's name </SPAN>Geographic Information Group
</LI>
<LI><SPAN class="thin">Contact's position </SPAN>Data Supply
</LI>
<LI><SPAN class="thin">Organization </SPAN>Scottish Natural Heritage
</LI>
<TABLE border="0" cellspacing="0" cellpadding="0">
<TR>
<TD width="150">Telephone</TD>
<TD>01463 725000</TD>
</TR>
<TR>
<TD width="150">E-mail address</TD>
<TD><a href="mailto:data_supply@nature.scot">data_supply@nature.scot</a></TD>
</TR>
<TR>
<TD width="150">Delivery point</TD>
<TD>Great Glen House</TD>
</TR>
<TR>
<TD width="150">City</TD>
<TD>Inverness</TD>
</TR>
<TR>
<TD width="150">Postal code</TD>
<TD>IV3 8NW</TD>
</TR><BR></TABLE>
</TD>
</TR>
</TABLE>
</DIV>
<h3>Metadata contact(s)</h3>
<DIV class="contactInfo">
<TABLE>
<TR>
<TD valign="top" width="180" nowrap><B>Role: </B> distributor
</TD>
<TD style="font-weight:bold;">
<LI><SPAN class="thin">Individual's name </SPAN>Geographic Information Group
</LI>
<LI><SPAN class="thin">Contact's position </SPAN>Data Supply
</LI>
<LI><SPAN class="thin">Organization </SPAN>Scottish Natural Heritage
</LI>
<TABLE border="0" cellspacing="0" cellpadding="0">
<TR>
<TD width="150">Telephone</TD>
<TD>01463 725000</TD>
</TR>
<TR>
<TD width="150">E-mail address</TD>
<TD><a href="mailto:data_supply@nature.scot">data_supply@nature.scot</a></TD>
</TR>
<TR>
<TD width="150">Delivery point</TD>
<TD>Great Glen House</TD>
</TR>
<TR>
<TD width="150">City</TD>
<TD>Inverness</TD>
</TR>
<TR>
<TD width="150">Postal code</TD>
<TD>IV3 8NW</TD>
</TR><BR></TABLE>
</TD>
</TR>
</TABLE>
</DIV>
<P class="noprint" align="right"><A HREF="#Top">Back to Top</A></P>
<H2 class="cont-background">Keywords, categories, classification</H2>
<H3>Topic category</H3>
<UL>
<LI>environment</LI>
</UL>
<H3>Place keywords </H3>
<LI>GB-SCT</LI>
<H3>Theme keywords </H3>
<LI>Environmental protection</LI>
<LI>Downloadable Data</LI>
<P class="noprint" align="right"><A HREF="#Top">Back to Top</A></P>
<H2 class="cont-background">Dataset background, process history</H2>
<H3>Lineage, dataset history </H3>
<div class="wrapme">The data from the relative wildness map (Phase I) was split into eight wildness classes based on Jenks Natural Breaks Optimisation method. In Phase II extensive areas of the two highest classes were selected (using a guideline of >650 ha) which with their adjacent areas of high wildness suggested the largest and most wild areas. Phase III selected and defined Wild Land Areas, with boundaries drawn applying informed judgements to confirm the selection of areas following a set of guidelines. This phase allowed for the consideration of wind farm development consented or built since the wildness mapping (Phase I) was produced. Note the coastal boundaries have been cut to follow the OS BoundaryLine MHWS line. In places such as Rum and the Garvellachs this coastline was of insufficient quality so OS VectorMap District was used instead. For more detailed information visit https://www.nature.scot/professional-advice/landscape-change/landscape-policy-and-guidance/landscape-policy-wild-land</div>
<P class="noprint" align="right"><A HREF="#Top">Back to Top</A></P>
<H2 class="legl-background">Maintenance and legal restrictions</H2>
<H3>Maintenance</H3><B>Update frequency: </B> unknown<BR><H3>Access and usage constraints</H3>
<TABLE width="95%" cellspacing="0" cellpadding="0" border="0">
<TR>
<TD colspan="2"><B>Usage constraints</B></TD>
</TR>
<TR>
<TD nowrap valign="top" width="250">Limitations of use: </TD>
<TD width="100%"><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Available under the Open Government Licence (http://www.nationalarchives.gov.uk/doc/open-government-licence)</SPAN></P></DIV></DIV></DIV></TD>
</TR>
</TABLE><BR><TABLE width="95%" cellspacing="0" cellpadding="0" border="0">
<TR>
<TD colspan="2"><B>Legal Constraints</B></TD>
</TR>
<TR>
<TD nowrap width="250" valign="top">Access constraints: </TD>
<TD width="100%"> license<BR> copyright<BR></TD>
</TR>
<TR>
<TD nowrap width="250" valign="top">Use constraints: </TD>
<TD width="100%"></TD>
</TR>
<TR>
<TD nowrap width="250" valign="top">Attribution, acknowledgements: </TD>
<TD width="100%">Available under the Open Government Licence (http://www.nationalarchives.gov.uk/doc/open-government-licence). You must always use the following attribution statement to acknowledge the source of the information: Copyright Scottish Natural Heritage Contains Ordnance Survey data © Crown copyright and database right (year)</TD>
</TR>
</TABLE><BR><P class="noprint" align="right"><A HREF="#Top">Back to Top</A></P>
<H2 class="geog-background">Geographic properties (Where?)</H2>
<H3>Spatial Reference System</H3>
<P>
<P><B>Name: </B>27700
</P>
<P><B>Code space: </B>EPSG
</P>
<P><B>Version: </B>7.4.1
</P>
</P>
<H3>Spatial resolution</H3>
<P>Ground sample distance -
25 metres
</P>
<H3>Extent</H3>
<P>Bounding coordinates (WGS84, lat/lon)</P>
<TABLE border="0" cellspacing="5" cellpadding="0" class="extentTable">
<TR>
<TD width="100"></TD>
<TD align="center" width="100" valign="bottom"> 60.598607</TD>
<TD width="100"></TD>
</TR>
<TR height="100">
<TD nowrap align="right"> -7.88229</TD>
<TD></TD>
<TD nowrap> -1.354187</TD>
</TR>
<TR>
<TD></TD>
<TD align="center" valign="top"> 54.995434</TD>
<TD></TD>
</TR>
</TABLE><BR><H3>Extent</H3>
<P>Bounding coordinates (WGS84, lat/lon)</P>
<TABLE border="0" cellspacing="5" cellpadding="0" class="extentTable">
<TR>
<TD width="100"></TD>
<TD align="center" width="100" valign="bottom"> 60.598607</TD>
<TD width="100"></TD>
</TR>
<TR height="100">
<TD nowrap align="right"> -7.88229</TD>
<TD></TD>
<TD nowrap> -1.354187</TD>
</TR>
<TR>
<TD></TD>
<TD align="center" valign="top"> 54.995434</TD>
<TD></TD>
</TR>
</TABLE><BR><H3>Extent</H3>
<P>Bounding coordinates (WGS84, lat/lon)</P>
<TABLE border="0" cellspacing="5" cellpadding="0" class="extentTable">
<TR>
<TD width="100"></TD>
<TD align="center" width="100" valign="bottom"> 60.598607</TD>
<TD width="100"></TD>
</TR>
<TR height="100">
<TD nowrap align="right"> -7.88229</TD>
<TD></TD>
<TD nowrap> -1.354187</TD>
</TR>
<TR>
<TD></TD>
<TD align="center" valign="top"> 54.995434</TD>
<TD></TD>
</TR>
</TABLE><BR><H3>Extent</H3>
<P>Bounding coordinates (WGS84, lat/lon)</P>
<TABLE border="0" cellspacing="5" cellpadding="0" class="extentTable">
<TR>
<TD width="100"></TD>
<TD align="center" width="100" valign="bottom"> 65.171944</TD>
<TD width="100"></TD>
</TR>
<TR height="100">
<TD nowrap align="right"> -28.171997</TD>
<TD></TD>
<TD nowrap> 15.227695</TD>
</TR>
<TR>
<TD></TD>
<TD align="center" valign="top"> 45.501382</TD>
<TD></TD>
</TR>
</TABLE><BR><P class="noprint" align="right"><A HREF="#Top">Back to Top</A></P>
</div>
<H2 class="dist-background">Distribution Information</H2>
<h3>Distributor contact</h3>
<DIV class="contactInfo">
<TABLE>
<TR>
<TD valign="top" width="180" nowrap><B>Role: </B> distributor
</TD>
<TD style="font-weight:bold;">
<LI><SPAN class="thin">Individual's name </SPAN>Geographic Information Group
</LI>
<LI><SPAN class="thin">Contact's position </SPAN>Data Supply
</LI>
<LI><SPAN class="thin">Organization </SPAN>Scottish Natural Heritage
</LI>
<TABLE border="0" cellspacing="0" cellpadding="0">
<TR>
<TD width="150">Telephone</TD>
<TD>01463 725000</TD>
</TR>
<TR>
<TD width="150">E-mail address</TD>
<TD><a href="mailto:data_supply@nature.scot">data_supply@nature.scot</a></TD>
</TR>
<TR>
<TD width="150">Delivery point</TD>
<TD>Great Glen House</TD>
</TR>
<TR>
<TD width="150">City</TD>
<TD>Inverness</TD>
</TR>
<TR>
<TD width="150">Postal code</TD>
<TD>IV3 8NW</TD>
</TR><BR></TABLE>
</TD>
</TR>
</TABLE>
</DIV>
<h3>Available formats</h3>
<LI>File Geodatabase Feature Class
(version )
</LI><BR><P class="noprint" align="right"><A HREF="#Top">Back to Top</A></P>
</div>
</BODY>
</HTML>

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data/poi_2015_12_scot06340459.csv Executable file → Normal file
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Council areas,2011_pop,CODE council areas,2011_pop,code
Aberdeen City,"222,793",S12000033 Aberdeen City,"222,793",S12000033
Aberdeenshire,"252,973",S12000034 Aberdeenshire,"252,973",S12000034
Angus,"115,978",S12000041 Angus,"115,978",S12000041

1 Council areas council areas 2011_pop CODE code
2 Aberdeen City 222,793 S12000033
3 Aberdeenshire 252,973 S12000034
4 Angus 115,978 S12000041

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CODE,Scottish Parliamentary Constituency Name,Postcode Population,Postcodes,Output area population,Output areas,OA Population minus PC Population,"% difference, OA Population - PC Population",Data zone Population,Data zones,DZ Population minus PC Population,"% difference, DZ Population - PC Population"
S16000074,Aberdeen Central,"83,618","2,071","83,557",778,-61,-0.07,"83,180",100,-438,-0.5
S16000075,Aberdeen Donside,"78,492","1,853","78,497",683,5,0.01,"78,359",105,-133,-0.2
S16000076,Aberdeen South and North Kincardine,"74,686","1,933","74,663",637,-23,-0.03,"74,947",95,261,0.3
S16000077,Aberdeenshire East,"77,707","2,914","77,427",624,-280,-0.36,"78,196",107,489,0.6
S16000078,Aberdeenshire West,"73,159","2,866","73,253",575,94,0.13,"73,383",101,224,0.3
S16000079,Airdrie and Shotts,"70,674","1,534","69,935",578,-739,-1.05,"69,863",95,-811,-1.1
S16000080,Almond Valley,"85,232","1,603","85,165",652,-67,-0.08,"85,219",114,-13,0
S16000081,Angus North and Mearns,"70,311","2,197","70,567",610,256,0.36,"70,990",93,679,1
S16000082,Angus South,"72,629","2,383","72,452",619,-177,-0.24,"72,260",98,-369,-0.5
S16000083,Argyll and Bute,"62,449","2,124","62,306",582,-143,-0.23,"62,449",88,0,0
S16000084,Ayr,"76,922","2,015","76,846",686,-76,-0.1,"76,602",105,-320,-0.4
S16000085,Banffshire and Buchan Coast,"75,850","2,778","76,084",644,234,0.31,"75,185",99,-665,-0.9
S16000086,"Caithness, Sutherland and Ross","71,863","2,506","71,882",622,19,0.03,"71,296",100,-567,-0.8
S16000087,"Carrick, Cumnock and Doon Valley","76,411","2,603","76,445",676,34,0.04,"76,689",103,278,0.4
S16000088,Clackmannanshire and Dunblane,"68,014","1,692","67,944",548,-70,-0.1,"68,022",91,8,0
S16000089,Clydebank and Milngavie,"71,354","1,838","71,768",642,414,0.58,"71,644",90,290,0.4
S16000090,Clydesdale,"72,935","2,099","72,866",621,-69,-0.09,"72,519",99,-416,-0.6
S16000091,Coatbridge and Chryston,"70,092","1,581","69,965",584,-127,-0.18,"70,750",91,658,0.9
S16000092,Cowdenbeath,"71,270","1,559","71,249",611,-21,-0.03,"71,245",97,-25,0
S16000093,Cumbernauld and Kilsyth,"65,183","1,177","65,405",530,222,0.34,"64,871",85,-312,-0.5
S16000094,Cunninghame North,"71,585","2,222","71,683",648,98,0.14,"71,510",94,-75,-0.1
S16000095,Cunninghame South,"66,561","1,685","66,463",566,-98,-0.15,"66,636",92,75,0.1
S16000096,Dumbarton,"72,254","2,137","71,957",654,-297,-0.41,"72,533",102,279,0.4
S16000097,Dumfriesshire,"77,148","3,042","77,160",662,12,0.02,"76,900",103,-248,-0.3
S16000098,Dundee City East,"72,022","1,953","72,001",670,-21,-0.03,"70,664",94,"-1,358",-1.9
S16000099,Dundee City West,"75,246","2,181","75,267",674,21,0.03,"76,604",94,"1,358",1.8
S16000100,Dunfermline,"72,714","1,757","72,643",603,-71,-0.1,"72,643",100,-71,-0.1
S16000101,East Kilbride,"75,256","1,601","75,201",653,-55,-0.07,"75,724",105,468,0.6
S16000102,East Lothian,"74,756","2,224","74,719",627,-37,-0.05,"74,719",98,-37,0
S16000103,Eastwood,"66,546","1,665","66,511",515,-35,-0.05,"66,511",89,-35,-0.1
S16000104,Edinburgh Central,"83,731","2,208","83,867",792,136,0.16,"83,965",99,234,0.3
S16000105,Edinburgh Eastern,"79,840","1,930","79,883",743,43,0.05,"80,497",105,657,0.8
S16000106,Edinburgh Northern and Leith,"86,205","1,971","86,344",837,139,0.16,"85,328",107,-877,-1
S16000107,Edinburgh Pentlands,"73,325","1,796","73,177",619,-148,-0.2,"73,108",94,-217,-0.3
S16000108,Edinburgh Southern,"77,706","1,846","77,561",679,-145,-0.19,"76,990",96,-716,-0.9
S16000109,Edinburgh Western,"75,819","2,094","75,794",652,-25,-0.03,"76,738",96,919,1.2
S16000110,Na h-Eileanan an Iar,"27,684",882,"27,684",253,0,0,"27,684",36,0,0
S16000111,"Ettrick, Roxburgh and Berwickshire","68,309","2,675","68,312",633,3,0,"68,482",87,173,0.3
S16000112,Falkirk East,"78,413","1,959","78,458",680,45,0.06,"78,707",106,294,0.4
S16000113,Falkirk West,"77,577","1,858","77,532",670,-45,-0.06,"77,283",108,-294,-0.4
S16000114,Galloway and West Dumfries,"74,176","3,441","74,164",664,-12,-0.02,"74,424",98,248,0.3
S16000115,Glasgow Anniesland,"74,843","1,811","74,628",693,-215,-0.29,"73,718",92,"-1,125",-1.5
S16000116,Glasgow Cathcart,"74,914","1,602","74,883",697,-31,-0.04,"74,554",96,-360,-0.5
S16000117,Glasgow Kelvin,"79,100","2,108","79,334",754,234,0.3,"82,550",94,"3,450",4.4
S16000118,Glasgow Maryhill and Springburn,"74,709","1,658","74,753",711,44,0.06,"72,206",90,"-2,503",-3.4
S16000119,Glasgow Pollok,"78,377","1,812","78,356",684,-21,-0.03,"78,080",101,-297,-0.4
S16000120,Glasgow Provan,"73,150","1,736","72,896",662,-254,-0.35,"72,837",98,-313,-0.4
S16000121,Glasgow Shettleston,"72,212","1,859","72,390",675,178,0.25,"72,690",93,478,0.7
S16000122,Glasgow Southside,"65,953","1,586","66,005",610,52,0.08,"66,610",82,657,1
S16000123,Greenock and Inverclyde,"76,325","1,941","76,221",689,-104,-0.14,"76,221",107,-104,-0.1
S16000124,"Hamilton, Larkhall and Stonehouse","73,361","1,694","73,468",636,107,0.15,"73,170",99,-191,-0.3
S16000125,Inverness and Nairn,"86,122","2,108","86,191",736,69,0.08,"86,769",115,647,0.8
S16000126,Kilmarnock and Irvine Valley,"82,233","2,412","82,275",731,42,0.05,"82,275",108,42,0.1
S16000127,Kirkcaldy,"78,045","1,881","78,007",718,-38,-0.05,"78,117",105,72,0.1
S16000128,Linlithgow,"89,886","2,163","89,953",766,67,0.07,"89,899",125,13,0
S16000129,Mid Fife and Glenrothes,"69,396","1,734","69,972",620,576,0.83,"70,038",96,642,0.9
S16000130,Midlothian North and Musselburgh,"78,002","2,368","78,174",675,172,0.22,"78,255",107,253,0.3
S16000131,"Midlothian South, Tweeddale and Lauderdale","75,707","2,461","75,569",642,-138,-0.18,"75,318",98,-389,-0.5
S16000132,Moray,"78,587","2,389","78,539",668,-48,-0.06,"78,539",106,-48,-0.1
S16000133,Motherwell and Wishaw,"73,924","1,589","74,624",645,700,0.95,"74,764",101,840,1.1
S16000134,North East Fife,"73,773","2,428","73,327",624,-446,-0.6,"73,155",96,-618,-0.8
S16000135,Orkney Islands,"21,349",663,"21,349",190,0,0,"21,349",29,0,0
S16000136,Paisley,"71,350","1,710","71,384",670,34,0.05,"72,034",91,684,1
S16000137,Perthshire North,"70,092","2,628","70,179",623,87,0.12,"70,979",89,887,1.3
S16000138,Perthshire South and Kinrossshire,"76,560","2,323","76,473",657,-87,-0.11,"75,673",97,-887,-1.2
S16000139,Renfrewshire North and West,"64,917","1,647","65,037",556,120,0.18,"64,446",85,-471,-0.7
S16000140,Renfrewshire South,"67,829","1,713","67,814",594,-15,-0.02,"67,755",89,-74,-0.1
S16000141,Rutherglen,"75,866","1,915","75,912",683,46,0.06,"76,028",106,162,0.2
S16000142,Shetland Islands,"23,167",582,"23,167",200,0,0,"23,167",30,0,0
S16000143,"Skye, Lochaber and Badenoch","74,147","2,394","74,059",648,-88,-0.12,"74,067",97,-80,-0.1
S16000144,Stirling,"73,675","2,189","73,745",637,70,0.1,"73,667",102,-8,0
S16000145,Strathkelvin and Bearsden,"77,842","2,220","77,881",643,39,0.05,"77,286",96,-556,-0.7
S16000146,Uddingston and Bellshill,"74,266","1,913","74,181",618,-85,-0.11,"73,868",97,-398,-0.5
1 CODE Scottish Parliamentary Constituency Name Postcode Population Postcodes Output area population Output areas OA Population minus PC Population % difference, OA Population - PC Population Data zone Population Data zones DZ Population minus PC Population % difference, DZ Population - PC Population
2 S16000074 Aberdeen Central 83,618 2,071 83,557 778 -61 -0.07 83,180 100 -438 -0.5
3 S16000075 Aberdeen Donside 78,492 1,853 78,497 683 5 0.01 78,359 105 -133 -0.2
4 S16000076 Aberdeen South and North Kincardine 74,686 1,933 74,663 637 -23 -0.03 74,947 95 261 0.3
5 S16000077 Aberdeenshire East 77,707 2,914 77,427 624 -280 -0.36 78,196 107 489 0.6
6 S16000078 Aberdeenshire West 73,159 2,866 73,253 575 94 0.13 73,383 101 224 0.3
7 S16000079 Airdrie and Shotts 70,674 1,534 69,935 578 -739 -1.05 69,863 95 -811 -1.1
8 S16000080 Almond Valley 85,232 1,603 85,165 652 -67 -0.08 85,219 114 -13 0
9 S16000081 Angus North and Mearns 70,311 2,197 70,567 610 256 0.36 70,990 93 679 1
10 S16000082 Angus South 72,629 2,383 72,452 619 -177 -0.24 72,260 98 -369 -0.5
11 S16000083 Argyll and Bute 62,449 2,124 62,306 582 -143 -0.23 62,449 88 0 0
12 S16000084 Ayr 76,922 2,015 76,846 686 -76 -0.1 76,602 105 -320 -0.4
13 S16000085 Banffshire and Buchan Coast 75,850 2,778 76,084 644 234 0.31 75,185 99 -665 -0.9
14 S16000086 Caithness, Sutherland and Ross 71,863 2,506 71,882 622 19 0.03 71,296 100 -567 -0.8
15 S16000087 Carrick, Cumnock and Doon Valley 76,411 2,603 76,445 676 34 0.04 76,689 103 278 0.4
16 S16000088 Clackmannanshire and Dunblane 68,014 1,692 67,944 548 -70 -0.1 68,022 91 8 0
17 S16000089 Clydebank and Milngavie 71,354 1,838 71,768 642 414 0.58 71,644 90 290 0.4
18 S16000090 Clydesdale 72,935 2,099 72,866 621 -69 -0.09 72,519 99 -416 -0.6
19 S16000091 Coatbridge and Chryston 70,092 1,581 69,965 584 -127 -0.18 70,750 91 658 0.9
20 S16000092 Cowdenbeath 71,270 1,559 71,249 611 -21 -0.03 71,245 97 -25 0
21 S16000093 Cumbernauld and Kilsyth 65,183 1,177 65,405 530 222 0.34 64,871 85 -312 -0.5
22 S16000094 Cunninghame North 71,585 2,222 71,683 648 98 0.14 71,510 94 -75 -0.1
23 S16000095 Cunninghame South 66,561 1,685 66,463 566 -98 -0.15 66,636 92 75 0.1
24 S16000096 Dumbarton 72,254 2,137 71,957 654 -297 -0.41 72,533 102 279 0.4
25 S16000097 Dumfriesshire 77,148 3,042 77,160 662 12 0.02 76,900 103 -248 -0.3
26 S16000098 Dundee City East 72,022 1,953 72,001 670 -21 -0.03 70,664 94 -1,358 -1.9
27 S16000099 Dundee City West 75,246 2,181 75,267 674 21 0.03 76,604 94 1,358 1.8
28 S16000100 Dunfermline 72,714 1,757 72,643 603 -71 -0.1 72,643 100 -71 -0.1
29 S16000101 East Kilbride 75,256 1,601 75,201 653 -55 -0.07 75,724 105 468 0.6
30 S16000102 East Lothian 74,756 2,224 74,719 627 -37 -0.05 74,719 98 -37 0
31 S16000103 Eastwood 66,546 1,665 66,511 515 -35 -0.05 66,511 89 -35 -0.1
32 S16000104 Edinburgh Central 83,731 2,208 83,867 792 136 0.16 83,965 99 234 0.3
33 S16000105 Edinburgh Eastern 79,840 1,930 79,883 743 43 0.05 80,497 105 657 0.8
34 S16000106 Edinburgh Northern and Leith 86,205 1,971 86,344 837 139 0.16 85,328 107 -877 -1
35 S16000107 Edinburgh Pentlands 73,325 1,796 73,177 619 -148 -0.2 73,108 94 -217 -0.3
36 S16000108 Edinburgh Southern 77,706 1,846 77,561 679 -145 -0.19 76,990 96 -716 -0.9
37 S16000109 Edinburgh Western 75,819 2,094 75,794 652 -25 -0.03 76,738 96 919 1.2
38 S16000110 Na h-Eileanan an Iar 27,684 882 27,684 253 0 0 27,684 36 0 0
39 S16000111 Ettrick, Roxburgh and Berwickshire 68,309 2,675 68,312 633 3 0 68,482 87 173 0.3
40 S16000112 Falkirk East 78,413 1,959 78,458 680 45 0.06 78,707 106 294 0.4
41 S16000113 Falkirk West 77,577 1,858 77,532 670 -45 -0.06 77,283 108 -294 -0.4
42 S16000114 Galloway and West Dumfries 74,176 3,441 74,164 664 -12 -0.02 74,424 98 248 0.3
43 S16000115 Glasgow Anniesland 74,843 1,811 74,628 693 -215 -0.29 73,718 92 -1,125 -1.5
44 S16000116 Glasgow Cathcart 74,914 1,602 74,883 697 -31 -0.04 74,554 96 -360 -0.5
45 S16000117 Glasgow Kelvin 79,100 2,108 79,334 754 234 0.3 82,550 94 3,450 4.4
46 S16000118 Glasgow Maryhill and Springburn 74,709 1,658 74,753 711 44 0.06 72,206 90 -2,503 -3.4
47 S16000119 Glasgow Pollok 78,377 1,812 78,356 684 -21 -0.03 78,080 101 -297 -0.4
48 S16000120 Glasgow Provan 73,150 1,736 72,896 662 -254 -0.35 72,837 98 -313 -0.4
49 S16000121 Glasgow Shettleston 72,212 1,859 72,390 675 178 0.25 72,690 93 478 0.7
50 S16000122 Glasgow Southside 65,953 1,586 66,005 610 52 0.08 66,610 82 657 1
51 S16000123 Greenock and Inverclyde 76,325 1,941 76,221 689 -104 -0.14 76,221 107 -104 -0.1
52 S16000124 Hamilton, Larkhall and Stonehouse 73,361 1,694 73,468 636 107 0.15 73,170 99 -191 -0.3
53 S16000125 Inverness and Nairn 86,122 2,108 86,191 736 69 0.08 86,769 115 647 0.8
54 S16000126 Kilmarnock and Irvine Valley 82,233 2,412 82,275 731 42 0.05 82,275 108 42 0.1
55 S16000127 Kirkcaldy 78,045 1,881 78,007 718 -38 -0.05 78,117 105 72 0.1
56 S16000128 Linlithgow 89,886 2,163 89,953 766 67 0.07 89,899 125 13 0
57 S16000129 Mid Fife and Glenrothes 69,396 1,734 69,972 620 576 0.83 70,038 96 642 0.9
58 S16000130 Midlothian North and Musselburgh 78,002 2,368 78,174 675 172 0.22 78,255 107 253 0.3
59 S16000131 Midlothian South, Tweeddale and Lauderdale 75,707 2,461 75,569 642 -138 -0.18 75,318 98 -389 -0.5
60 S16000132 Moray 78,587 2,389 78,539 668 -48 -0.06 78,539 106 -48 -0.1
61 S16000133 Motherwell and Wishaw 73,924 1,589 74,624 645 700 0.95 74,764 101 840 1.1
62 S16000134 North East Fife 73,773 2,428 73,327 624 -446 -0.6 73,155 96 -618 -0.8
63 S16000135 Orkney Islands 21,349 663 21,349 190 0 0 21,349 29 0 0
64 S16000136 Paisley 71,350 1,710 71,384 670 34 0.05 72,034 91 684 1
65 S16000137 Perthshire North 70,092 2,628 70,179 623 87 0.12 70,979 89 887 1.3
66 S16000138 Perthshire South and Kinrossshire 76,560 2,323 76,473 657 -87 -0.11 75,673 97 -887 -1.2
67 S16000139 Renfrewshire North and West 64,917 1,647 65,037 556 120 0.18 64,446 85 -471 -0.7
68 S16000140 Renfrewshire South 67,829 1,713 67,814 594 -15 -0.02 67,755 89 -74 -0.1
69 S16000141 Rutherglen 75,866 1,915 75,912 683 46 0.06 76,028 106 162 0.2
70 S16000142 Shetland Islands 23,167 582 23,167 200 0 0 23,167 30 0 0
71 S16000143 Skye, Lochaber and Badenoch 74,147 2,394 74,059 648 -88 -0.12 74,067 97 -80 -0.1
72 S16000144 Stirling 73,675 2,189 73,745 637 70 0.1 73,667 102 -8 0
73 S16000145 Strathkelvin and Bearsden 77,842 2,220 77,881 643 39 0.05 77,286 96 -556 -0.7
74 S16000146 Uddingston and Bellshill 74,266 1,913 74,181 618 -85 -0.11 73,868 97 -398 -0.5

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---
title: "Mapping Environmental Action in Scotland"
abstract:
# thanks: "Replication files are available on the author's Github account (https://github.com/kidwellj/mapping_environmental_action). **Current version**: February 05, 2019
style: jeremy1
author: "[Jeremy H. Kidwell](http://jeremykidwell.info)"
affiliation: University of Birmingham
institute: University of Birmingham
e-mail: "[j.kidwell@bham.ac.uk](mailto:j.kidwell@bham.ac.uk)"
date: "2019-02-05"
bibliography: biblio.bib
linkcolor: black
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fontsize: 11pt
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keep_md: true
code_folding: hide
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number_sections: true
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pdf_document:
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citation_package: natbib
latex_engine: xelatex
---
# Introduction[^15541312]
Until recently, environmentalism has been treated by governments and environmental charities as a largely secular concern. In spite of the well-developed tradition of "eco-theology" which began in earnest in the UK in the mid-twentieth century (and which has many precursors in previous centuries), third-sector groups and governments, particularly in Britain and Europe, have largely ignored religious groups as they have gone about their business crafting agendas for behaviour change, developing funding programmes, and developing platforms to mitigate ecological harm, motivate consumers and create regulation regimes. That this has changed is evidenced by the fact that several prominent non-religious environmental groups have commissioned studies and crafted outreach programmes to persons with a particular faith tradition or to "spiritual communities" including RSPB (2013) and the Sierra Club USA (2008).[^158261118] Further, since 2008, the Scottish Government has provided a significant portion of funding for the ecumenical charity, Eco-Congregation Scotland, which works to promote literacy on environmental issues in religious communities in Scotland and helps to certify congregations under their award programme. What is not well known, however, even by these religious environmental groups themselves, is whether or how their membership might be different from other environmental groups. This study represents an attempt to illuminate this new interest with some more concrete data about religious groups in Scotland and how they may differ from non-religious counterparts.
# Eco-Congregation Scotland: The Basics
There are 344 eco-congregations in Scotland. By some measurements, particularly in terms of individual sites and possibly also with regards to volunteers, this makes Eco-Congregation Scotland one of the largest environmental third-sector groups in Scotland.[^159141043]
In seeking to conduct GIS and statistical analysis of ECS, it is important to note that there some ways in which these sites are statistically opaque. Our research conducted through interviews at a sampling of sites and analysis of a variety of documents suggests that there is a high level of diversity both in terms of the number of those participating in environmental action and the types of action underway at specific sites. Work at a particular site can also ebb and flow over the course of time. Of course, as research into other forms of activism and secular environmental NGOs has shown, this is no different from any other third sector volunteer group. Variability is a regular feature of groups involved in activism and/or environmental concern.
For the sake of this analysis, we took each Eco-Congregation Scotland site to represent a point of analysis as if each specific site represented a community group which had "opted-in" on environmental concern. On this basis, in this section, in the tradition of human geography, we "map" environmental action among religious communities in Scotland a variety of ways. This is the first major geographical analysis of this kind conducted to date in Europe. We measure the frequency and location of ECS sites against a variety of standard geo-referenced statistical data sets, seeking to provide a statistical and geographically based assessment of the participation of religious groups in relation to the following:
- Location within Scotland
- Religious affiliation
- Relation to the Scottish Index of Multiple Deprivation (SIMD)
- Relation to the 8-Fold Scottish Government Urban-Rural Scale
- Proximity to "wilderness" (based on several different designations)
For the sake of comparison, we also measured the geographical footprint of two other forms of community group in Scotland, (1) Transition Towns (taking into account their recent merge with Scotland Communities Climate Action Network) and (2) member groups of the Development Trust Association Scotland ("DTAS"). These two groups provide a helpful basis for comparison as they are not centralised and thus have a significant geographical dispersion across Scotland. They also provide a useful comparison as transition is a (mostly) non-religious environmental movement, and community development trusts are not explicitly linked to environmental conservation (though this is often part of their remit), so we have a non-religious point of comparison in Transition and a non-environmental point of comparison with DTAS
# Technical Background
Analysis was conducted using QGIS 2.8 and R 3.5.2, and data-sets were generated in CSV format.[^15541313] To begin with, I assembled a data set consisting of x and y coordinates for each congregation in Scotland and collated this against a variety of other specific data. Coordinates were checked by matching UK postcodes of individual congregations against geo-referencing data in the Office for National Statistics postcode database. In certain instances a single "congregation" is actually a series of sites which have joined together under one administrative unit. In these cases, each site was treated as a separate data point if worship was held at that site at least once a month, but all joined sites shared a single unique identifier. As noted above, two other datasets were generated for the sake of comparative analysis.[^177171536] These included one similar Environmental Non-Governmental Organisation (ENGO) in Scotland (1) Transition Scotland (which includes Scotland Communities Climate Action Network);[^15541342] and another community-based NGO, Scottish Community Development Trusts.[^158261232] As this report will detail, these three overlap in certain instances both literally and in terms of their aims, but each also has a separate identity and footprint in Scotland. Finally, in order to normalise data, we utilised the PointX POI dataset which maintains a complete database of Places of Worship in Scotland.[^15541614]
# Background and History of Eco-Congregation Scotland
Eco-Congregation Scotland began a year before the official launch of Eco-Congregation England and Wales, in 1999, as part of an effort by Kippen Environment Centre (later renamed to Forth Environment Link, or "FEL") a charity devoted to environmental education in central Scotland[^158261210] to broaden the scope of its environmental outreach to churches in central Scotland.[^15826124] Initial funding was provided, through Kippen Environment Centre by way of a "sustainable action grant" (with funds drawn from a government landfill tax) through a government programme called Keep Scotland Beautiful (the Scottish cousin of Keep Britain Tidy). After this initial pilot project concluded, the Church of Scotland provided additional funding for the project in the form of staff time and office space. Additional funding a few years later from the Scottish Government helped subsidise the position of a business manager, and in 2011 the United Reformed Church contributed additional funding which subsidised the position of a full-time environmental chaplain for a 5-year term, bringing the total staff to five.
The programme launched officially in 2001 at Dunblane Cathedral in Stirling and by 2005 the project had 89 congregations registered to be a part of the programme and 25 which had completed the curriculum successfully and received an Eco-Congregation award. By 2011, the number of registrations had tripled to 269 and the number of awarded congregations had quadrupled to `sum(ecs$award1 < "01/01/2012", na.rm=TRUE)`. This process of taking registrations and using a tiered award or recognition scheme is common to many voluntary organisations. The ECS curriculum was developed in part by consulting the Eco-Congregation England and Wales materials which had been released just a year earlier in 1999, though it has been subsequently revised, particularly with a major redesign in 2010. In the USA, a number of similar groups take a similar approach including Earth Ministry (earthministry.org) and Green Faith (greenfaith.org).
In the case of Eco-Congregation Scotland, congregations are invited to begin by "registering" their interest in the programme by completing a basic one-sided form. The next step requires the completion of an award application, which includes a facilitated curriculum called a "church check-up" and after an application is submitted, the site is visited and assessed by third-party volunteer assessors. Sites are invited to complete additional applications for further awards which are incremental (as is the application process). Transition communities, at least in the period reflected on their map, go through a similar process (though this does not involve the use of a supplied curriculum) by which they are marked first as "interested," become "active" and then gain "official" status.[^1554162]
# Representation by Regional Authorities (Council Areas)
Perhaps the first important question to ask of these groups is, where are they? I calculated the spread of eco-congregations and transition groups across each of the 32 council areas in Scotland. Every council area in Scotland has at least one eco-congregation or transition group). The most are located in , with 48, whereas the mean among all the 32 council areas is 10.75, with a median of 8, standard deviation of 9.4698162, and interquartile range of 11.5. The following choropleth maps show the relative concentration of eco-congregations (indicated by yellow to red).
(*TODO: need to implement*) Though there are too few eco-congregations and transition groups for a numerically significant representation in any of the intermediate geographies, mapping the concentration of sites by agricultural parishes allows for a more granular visual and I include this for comparison sake. Note, for the sake of a more accurate visual communication, we have also marked out areas of Scotland that are uninhabited with hash marks on the map of agricultural parishes. (*TODO: this will be done in the final draft, once I get my image masking fixed!*).[^15571030]
![Figure 1](figures/plot_admin_ecs_choropleth-1.png)
![Figure 2](figures/plot_admin_ecs_normed_choropleth-1.png)![Figure 2](figures/plot_admin_ecs_normed_choropleth-2.png)
Given the way population and places of worship are unevenly distributed across Scotland it is important to represent data in terms of relative distribution. For this study, we attempted to "normalise" our data in two different ways, (1) as shown by Figure 2 above, by taking population figures from the 2011 census (see data sheet in Appendix A) and (2) by adjusting relative to the number of places of worship in each council region.[^15914204] The latter of these two can yield particularly unexpected results. Thus, of the 4048 "places of worship" in Scotland, the highest concentration is actually the region, with 435, second is 329 (). Rank of Council Areas by population and number of places of worship is also included in Appendix A.
We can use this data to normalise our figures regarding Eco-Congregation Scotland communities and this draws the presence in Edinburgh of ECS communities into even sharper relief, as Edinburgh, though ranked second in terms of population and fifth in terms of places of worship, ranks first for the presence of all ECS congregations and awarded ECS congregations. However, taking population as the basis for normalisation first, we find that Edinburgh is far from the most prominent outlier. In trying to communicate this difference for a lay-audience, we have chosen to list this difference as a multiplier (i.e. there are 2.x times as many congregations as their share of population and an average figure of congregations might allow for) as this conveys the difference in a straight-forward way. Outliers where the disparity between their relative share of the total ECS footprint and their relative share of population is different by a positive ratio of more than double include the Orkney Islands (3.7 times more eco-congregations than their expected average share based on population), Argyll and Bute (`admin_lev1[CODE=S12000023]$ecs_pop_factor` 4.2x), Stirling (2.76x), and Perthshire and Kinross (2.18x). Interestingly, there are no outliers whose relative share of the total footprint of ECS is double or more in the negative direction (see Appendix A chart for full numbers).
Turning to the total of 4048 "places of worship" in Scotland, we find a slightly different picture of the relative concentration of Eco-Congregations in Scotland. In this case, the outliers are
Whereas our initial measurements indicated a prominent lead for Edinburgh, by normalising our data in this way we can highlight the stronger-than-expected presence of several others that might otherwise escape notice because they lie in a region with significantly lower population or numerically less places of worship. Taking the PointX data on "places of worship" in Scotland, we find a less dramatic picture, but also a slightly different one. The positive outliers include East Renfrewshire (3.4x) Edinburgh (2.9x), Stirling (2.2), West Lothian (1.9x) and Aberdeen (1.5x). Again, negative outliers are far less dramatic, with only Midlothian possessing a ratio of more than 100% negative difference from the number of "places of worship" at 1.5x *fewer*.
![](figures/create_admin_barplot-1.png)<!-- -->
## Concentration of groups {.tabset}
### Choropleth
![Figure 4](figures/create_choropleth_others-1.png)![Figure 4](figures/create_choropleth_others-2.png)![Figure 4](figures/create_choropleth_others-3.png)
### Cartogram
We can compare the representation in these various regions against our comparison groups to see how other community-based organisations cluster in Scottish administrative districts. Here there are some significant contrasts. Scottish Community Development trusts are most intensely concentrated in the Highlands and Argyll & Bute. But, this is consistent with all the other categories, Eco-Congregations, Places of Worship, and dtas are all over-represented in this area, varying only by the degree. Edinburgh is different, here we find that Eco-Congregations and Transition projects are over-represented, while dtass are under-represented. Finally, the highlands are another strong contrast, here we find a very strong over-representation by transition towns and dtass while the representation of Eco-Congregations is relatively close to the population share for that area. The two areas of greatest contrast for Eco-Congregations from the other groups are unsurprising, Edinburgh is the location of the ECS offices, while Stirling is the area in which ECS first began (see Appendix B for full data).
# Christian Denominations #
Eco-Congregation Scotland describes itself as an "ecumenical movement helping local groups of Christians link environmental issues to their faith, reduce their environmental impact and engage with their local community." There are several ties to the Church of Scotland, as the denomination provides office space to Eco-Congregation Scotland in the Church of Scotland complex at 121 George Street in Edinburgh and provides funding for one full-time member of staff. In spite of this, ECS has, from the start, attempted to emphasise its ecumenical aspirations and this is reflected in a wide variety of ways. The name "eco-congregation" is meant to be tradition neutral (in interviews, staff noted how they have sought to avoid names such as "eco-kirk" which would be the more obvious Presbyterian title, or "eco-community" or "eco-church" which might indicate allegiance towards another). Further, the group has a environmental chaplain on their staff whose position is funded by the United Reformed Church, and other members of staff are funded by the Scottish government, and as such, carry no formal affiliation with a religious institution. This diversity and ecumenicism is reflected in a membership which is, though dominated by the Church of Scotland, nevertheless, made up of a range of Christian traditions.
Though these are not numerically significant, it is important to note that some member congregations describe themselves as ecumenical communities, and others are hybrids reflecting the merging of two traditions. As this ecumenical/hybrid designation involves a small number of the overall total, for the sake of this research, these have been combined into a category called "ecumenical." Further, as research conducted by Church of Scotland statistician Fiona Tweedie has shown, in many Scottish communities with only one church, members of this church will specify their denominational affiliation in a variety of ways (Roman Catholic, Quaker, Methodist, etc.) even though the church and its minister are formally affiliated with the Church of Scotland.[^159142242] So, we should be careful not to assume that the various denominational affiliations of eco-congregations are indicative in an absolute way.
A wide variety of historians and sociologists of religion have noted the regional significance of different Christian denominations in Scotland so we sought to assess the relative distribution and concentration of eco-congregations by denomination. Finding comparative statistics is a complex task, made more complicated by several factors. First, most demographic data on religious belonging in Scotland comes in the form of the 2011 census and as such is far more atomised than this data-set which identifies groups at the level of "congregations" rather than individuals. Equating these two is also complex, as participation by members of congregations can be measured in a variety of ways, there are often a small number of active participants in each eco-congregation group, but may also be a large scale, but passive, support by the wider community.
So why provide this kind of data (i.e. at the level of individual churches) when more granular data (i.e. at the level of individuals persons) is available in the form of the census and related parallel publications such as the 2008 Scottish Environmental Attitudes survey? We believe that mapping places of worship provides a useful intermediate level of analysis and may complement our more atomised understanding of EA which has been assessed at the level of individual persons to date. Because representation within some administrative areas of Scotland, can lead to a small number of data points, we have kept analysis to a National level and have not provided more specific administrative-area level calculations.
Table: ECS by denomination
x
------------- ----
Baptist 4
C of S 254
C of S / URC 3
Cong 1
Ecu 5
FCS 1
Independent 2
Meth 4
Non. 1
Quaker 1
RC 15
SEC 41
Unitarian 1
URC 11
As one might expect, there is a strong representation of the Church of Scotland, almost 74% of eco-congregations, with this number remaining the same when we only count awarded sites. We can confirm, on the basis of this analysis that ECS has a disproportional representation by Church of Scotland churches. At the 2002 church census count, it only represented 40.20% of Scottish churches (1666 of 4144 total churches). Similarly, on the 2011 Scottish census, only 32.44% of persons claimed to be members of the Church of Scotland. We can adjust this representation to 60%, if one excludes the 2,445,204 persons (46% of the total on the census) who reported either "no religion" or adherence to a religious tradition not currently represented among the eco-congregation sites. There is a slight over-representation by the United Reformed church, though this seems considerably more dramatic when one takes into account the fact that this is a trebling or more of their overall share of Scottish churches. The URC makes up only sightly more than 1% of church buildings in Scotland and a tiny 0.04% of respondents to the 2011 census. The Scottish Episcopal church hovers right around a proportional representation within ECS. More concerning are the significant underrepresentation by Roman Catholic churches, Baptists, the Free Church of Scotland, and other independent churches.
While Roman Catholic churches make up just over 10% of the church buildings in Scotland, less than 5% of churches registered as eco-congregations are RC. Even more dramatic is the quartering of baptist churches, and the non-existent representation among the significant group of independent churches and small denominations. These make up nearly 25% of all Scottish churches (over a thousand) and yet only 4 have registered as eco-congregations. We provide several tentative advisories in response to these under-representations in the final section of this paper.
# Eco-Congregations, Urban, Rural and Remote
```
## OGR data source with driver: ESRI Shapefile
## Source: "/Users/jeremy/gits/mapping_environmental_action/data", layer: "SG_UrbanRural_2016"
## with 8 features
## It has 6 fields
```
Rather than bifurcate congregations into an urban/rural dichotomy, for this study we used the Scottish Government's six-point remoteness scale to categorise eco-congregations along a spectrum of highly populated to remote areas. This 8-fold scale (calculated biennially) offers a more nuanced measurement that combines measurements of remoteness and population along the following lines:
1. Large Urban Areas - Settlements of over 125,000 people.
2. Other Urban Areas - Settlements of 10,000 to 125,000 people.
3. Accessible Small Towns - Settlements of between 3,000 and 10,000 people, and within a 30 minute drive time of a Settlement of 10,000 or more.
4. Remote Small Towns - Settlements of between 3,000 and 10,000 people, and with a drive time between 30 and 60 minutes to a Settlement of 10,000 or more.
5. Very Remote Small Towns - Settlements of between 3,000 and 10,000 people, and with a drive time of over 60 minutes to a Settlement of 10,000 or more.
6. Accessible Rural Areas - Areas with a population of less than 3,000 people, and within a drive time of 30 minutes to a Settlement of 10,000 or more.
7. Remote Rural Areas - Areas with a population of less than 3,000 people, and with a drive time of between 30 and 60 minutes to a Settlement of 10,000 or more.
8. Very Remote Rural Areas - Areas with a population of less than 3,000 people, and with a drive time of over 60 minutes to a Settlement of 10,000 or more.
The key question which this analysis seeks to answer is whether ECS, or the other groups surveyed, are more concentrated in Urban or Rural areas, so as is the case below with our analysis of deprivation, we are concerned with the outer conditions, i.e. the urban areas (items 1-2) and remote areas (items 7-8).
Of all the groups surveyed in this study, Eco-Congregation Scotland is the most heavily concentrated in large urban areas (33.53%), exceeding by almost 50% the rate for all places of worship (22.96% in large urban areas). Transition is a much more modest 20% and development trusts a bit lower at 15%. It is interesting to note that the rate of ECS concentration in these large urban areas matches the level of overall population distribution (34.5%). On the other end of the scale, Eco-Congregation Scotland is the least concentrated in remote rural areas (with 3.93% on level 7 and 5.44% on level 8 on the urban-rural scale), though again, they correlate roughly to the general population distribution (3.2% and 2.9% respectively). Places of worship outpace both the population of Scotland and the footprint of Eco-Congregation Scotland, with 14.98% in very remote rural areas, but this is exceeded by transition at 16.47% and both by Scottish community development trusts at 32.14%. So while Eco-Congregation Scotland correlates roughly with Scottish population distribution across the urban-rural scale, it has a considerably more urban profile than either of the other two groups surveyed.
![](figures/create_ur_barplot-1.png)<!-- -->
![Figure 9](figures/create_urbanrural_ecs_chart_choropleth-1.png)
# Wealth, Employment, and Literacy
```
## OGR data source with driver: ESRI Shapefile
## Source: "/Users/jeremy/gits/mapping_environmental_action/data", layer: "sc_dz_11"
## with 6976 features
## It has 9 fields
```
## SIMD representation across domains by group {.tabset}
### Jitterplot
### Barplot
![](figures/create_simd_barplot-1.png)<!-- -->
### Boxplot
Another crucial point of assessment relates to the relation of Eco-Congregation communities to the Scottish Index of Multiple Deprivation. This instrument aggregates a large variety of factors which can lead to deprivation including crime rates, employment levels, access to services (implicating remoteness), and literacy. By assessing ECS, Transition, and dtas against the deprivation scale, we can assess whether eco-congregations fall within particular demographics and also whether the fully aggregated SIMD measurement provides a useful point of comparison for our purposes. The SIMD essentially divides Scotland into 6407 geographic zones and then ranks them based on their relative deprivation. This data set can be split into any number of groups, but for our purposes we have settled on Quintiles, splitting the SIMD data set at every 1302 entries. We then measured where each transition group, ECS, and dtas fell within these zones and calculated how they fell into these five quintiles, from more to least deprived.
The first, and most compelling finding is that, in general Eco-Congregation Scotland and Transition Scotland are both roughly the same and match the level of population distribution in the lowest quintile of the general SIMD measurement. 8% of transition groups and eco-congregation groups which have received awards and 9% of the population are located within this quintile. However, taken in relation to the distribution of places of worship in the lowest quintile, we find that eco-congregations are located at half the rate that places of worship are (15%) and dtass match this much more closely at 14%. Turning towards the top quintile, this pattern also holds, here both transition groups (21%) and eco-congregations (21% and 29% of awarded congregations) depart from the population distribution in this upper quintile (which is 10%). Again, general places of worship (at 11%) and DTASs (at 5%) take the opposite direction. We can say decisively that in communities which have been identified as good candidates for intervention to reduce deprivation, ECS and Transition are less likely, and they are over-represented at the areas which fall into the least deprived quintile.
We can find divergence between transition communities and eco-congregation when we split out SIMD domains. In the lowest quartile, measuring exclusively for the income domain, ECS is more represented (11%) - roughly the same as DTAS (12%), and transition is less (6%) represented. In general (as shown on the chart in Appendix D), these trends hold when representation of our groups are measured within other non-remoteness domains of the SIMD. Our basic conclusion is that transition towns are least likely to operate within the lowest quartile of SIMD and DTASs are most likely, with ECS somewhere in the middle. Given the general disparity against the presence of places of worship, it seems fair to suggest that this might be an area for improvement, perhaps even worth developing a special programme which might target areas in SIMD quartile 1 for eco-congregation outreach. This might be considered particularly in light of the starkest underrepresentation of ECS and transition within the SIMD domain of education, skills, and training.
```
## Reading layer `SSSI_SCOTLAND' from data source `/Users/jeremy/gits/mapping_environmental_action/data/SSSI_SCOTLAND.shp' using driver `ESRI Shapefile'
## Simple feature collection with 15872 features and 7 fields
## geometry type: POLYGON
## dimension: XY
## bbox: xmin: -296506.9 ymin: 530237.9 xmax: 467721.5 ymax: 1220310
## epsg (SRID): NA
## proj4string: +proj=tmerc +lat_0=49 +lon_0=-2 +k=0.9996012717 +x_0=400000 +y_0=-100000 +datum=OSGB36 +units=m +no_defs
```
```
## OGR data source with driver: ESRI Shapefile
## Source: "/Users/jeremy/gits/mapping_environmental_action/data", layer: "SSSI_SCOTLAND"
## with 15872 features
## It has 7 fields
## Integer64 fields read as strings: PA_CODE
```
```
## Reading layer `WILDLAND_SCOTLAND' from data source `/Users/jeremy/gits/mapping_environmental_action/data/WILDLAND_SCOTLAND.shp' using driver `ESRI Shapefile'
## Simple feature collection with 42 features and 3 fields
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## dimension: XY
## bbox: xmin: 76877.24 ymin: 578454.1 xmax: 435367.1 ymax: 1190510
## epsg (SRID): NA
## proj4string: +proj=tmerc +lat_0=49 +lon_0=-2 +k=0.9996012717 +x_0=400000 +y_0=-100000 +datum=OSGB36 +units=m +no_defs
```
```
## OGR data source with driver: ESRI Shapefile
## Source: "/Users/jeremy/gits/mapping_environmental_action/data", layer: "WILDLAND_SCOTLAND"
## with 42 features
## It has 3 fields
```
```
## Reading layer `National_Forest_Inventory_Woodland_Scotland_2017' from data source `/Users/jeremy/gits/mapping_environmental_action/data/National_Forest_Inventory_Woodland_Scotland_2017.shp' using driver `ESRI Shapefile'
## Simple feature collection with 199698 features and 7 fields
## geometry type: POLYGON
## dimension: XY
## bbox: xmin: 65210.1 ymin: 532547.9 xmax: 461253.7 ymax: 1209179
## epsg (SRID): NA
## proj4string: +proj=tmerc +lat_0=49 +lon_0=-2 +k=0.9996012717 +x_0=400000 +y_0=-100000 +datum=OSGB36 +units=m +no_defs
```
```
## OGR data source with driver: ESRI Shapefile
## Source: "/Users/jeremy/gits/mapping_environmental_action/data", layer: "National_Forest_Inventory_Woodland_Scotland_2017"
## with 199698 features
## It has 7 fields
## Integer64 fields read as strings: OBJECTID
```
# Proximity to "Wilderness"
Chasing down a curiosity, I decided to try and calculate whether proximity to "wilderness" or "scenic nature" or just trees might have some impact on generating more mobilised communities. I realised that there would be several problems with this kind of calculation up front, first being that "nature" is a deeply problematic construct, reviled by geographers and philosophers alike. With this in mind, I identified several different ways of reckoning wilderness, starting with the highly anachronistic "Scenic Land" designation from the 1970s. Then I pursued the more carefully calculated "core wild areas" generated by SNH just a few years ago. However, even the core wile areas concept has been criticised heavily, so I also expanded out my search to include all sites of special scientific interest and then went even wider to include the Scottish Forestry Service's "Native Woodland" and finally, the most generic possible measurement, any land identified as forested at the last Forest Inventory.
Proximity to these areas was the next concern, because many of these designations deliberately exclude human habitat, so it was necessary to measure the number of sites within proximity. There is a question which lies here regarding aesthetics, namely, what sort of proximity might generate an affective connection? From my own experience, I decided upon the distance represented by a short walk, i.e. a half-kilometre. However, with the more generic measurements, such as SSSI and forestation, this wouldn't do, as there are so many of these sites that a buffer of 500 meters encapsulates almost all of inhabited Scotland. So for these sites I also calculated a count within 50 metres.
So what did I discover? The results were inconclusive. First, it is important to note that on the whole, Eco-Congregations tend to be more urban than place of worship taken generally at a rate of nearly 3:1 (5.4% of Eco-Congregations lie in areas currently designated as "Very Remote Rural Areas" whereas nearly 15% of places of worship lie in these areas), so what I was testing for was whether this gap was smaller when specifying these various forms of "wild" remoteness. For our narrowest measurements, there were so few sites captured as to render measurement unreliable. There are, for obvious reasons, 0 sites located within any of SNG's core wild areas. Similarly, there are very few of our activist communities located within SSSI's (only `st_within(pow_pointX_sf, sssi)` places of worship out of 4048, `st_within(transition_sf, sssi)` transition towns, (or 2%) and `st_within(dtas_sf, sssi)` community development trusts (3%)). However, expanding this out makes things a bit more interesting, within 50 metres of SSSI's in Scotland lie `st_within(ecs_sf, st_buffer(sssi, dist = 50))` Eco-Congregations (or just under 1%), which compares favourably with the `st_within(pow_pointX_sf, st_buffer(sssi, dist = 50))` places of worship (or just 1.5%) far exceeding our ratio (1:1.5 vs. 1:3). This is the same with our more anachronistic measure of "scenic areas," there are 7 eco-congregations within these areas, and 175 places of worship, making for a ratio of nearly 1:2 (2.1% vs. 4.3%). Taking our final measure, of forested areas, this is hard to calculate, as only one Eco-Congregation lies within either native or generally forested land.
--------------------------------- -------------- -------- ---------
**titles** Within SSSIs ...50m ...500m
**ecs_wilderness_row** 0 3 59
**pow_wilderness_row** 7 62 610
**dtas_wilderness_row** 7 11 49
**transition_wilderness_row** 0 1 17
**permaculture_wilderness_row** 0 0 3
--------------------------------- -------------- -------- ---------
# Appendix A
----------------------------------------------------------------
name ecs_count pow_count dtas_count
--------------------------- ----------- ----------- ------------
Fife 18 243 11
South Ayrshire 3 68 1
Inverclyde 2 53 1
Aberdeen City 15 96 1
Highland 21 435 34
West Dunbartonshire 6 52 3
Moray 11 103 6
Orkney Islands 4 50 10
Aberdeenshire 19 244 15
East Renfrewshire 8 37 2
Clackmannanshire 3 30 1
East Ayrshire 4 68 6
North Lanarkshire 5 187 1
Dundee City 3 94 1
Argyll and Bute 18 172 24
Angus 12 106 0
Glasgow City 25 329 21
East Dunbartonshire 7 43 1
Shetland Islands 3 89 4
Scottish Borders 11 153 9
Comhairle nan Eilean Siar 0 114 9
Renfrewshire 6 84 5
North Ayrshire 7 96 3
East Lothian 8 71 2
Falkirk 8 83 0
West Lothian 11 70 7
Perth and Kinross 20 162 10
Dumfries and Galloway 7 189 15
Stirling 13 73 10
City of Edinburgh 48 233 7
Midlothian 1 45 4
South Lanarkshire 17 176 8
----------------------------------------------------------------
Table: Table continues below
--------------------
permaculture_count
--------------------
1
0
0
0
1
0
0
0
1
0
0
0
0
0
3
0
2
0
0
2
0
0
0
0
0
0
1
2
0
0
1
0
--------------------
# Appendix B
(JK note to self: same as above, but augmented with multipliers by which categories are different from one another)
# Appendix C - Data by Urban / Rural Classification
--------------------------------------------------------------------------------
UR8FOLD ecs_count ecs_percent pow_count pow_percent transition_count
--------- ----------- ------------- ----------- ------------- ------------------
1 111 0.32 907 0.22 35
2 98 0.28 1015 0.25 16
3 30 0.087 265 0.065 7
4 9 0.026 100 0.025 2
5 6 0.017 87 0.021 2
6 54 0.16 696 0.17 14
7 16 0.047 372 0.092 7
8 20 0.058 606 0.15 11
--------------------------------------------------------------------------------
Table: Table continues below
---------------------------------------------------------------------
transition_percent dtas_count dtas_percent permaculture_count
-------------------- ------------ -------------- --------------------
0.37 35 0.15 2
0.17 25 0.11 1
0.074 20 0.087 1
0.021 7 0.03 0
0.021 1 0.0043 1
0.15 46 0.2 2
0.074 27 0.12 3
0.12 69 0.3 4
---------------------------------------------------------------------
Table: Table continues below
----------------------
permaculture_percent
----------------------
0.14
0.071
0.071
0
0.071
0.14
0.21
0.29
----------------------
# Citations
[^15541312]: This research was jointly funded by the AHRC/ESRC under project numnbers AH/K005456/1 and AH/P005063/1.
[^158261118]: This is not to say that there have been no collaborations before 2000, noteworthy in this respect is the WWF who helped to found the Alliance of Religion and Conservation (ARC) in 1985.
[^159141043]: This suggestion should be qualified - RSPB would greatly exceed ECS both in terms of the number of individual subscribers and budget. The RSPB trustee's report for 2013-2014 suggests that their member base was 1,114,938 people across Britain with a net income of £127m - the latter of which exceeds the Church of Scotland. If we adjust this based on the Scottish share of the population of the United Kingdom as of the 2011 census (8.3%) this leaves us with an income of £9.93m. The British charity commission requires charities to self-report the number of volunteers and staff, and from their most recent statistics we learn that RSPB engaged with 17,600 volunteers and employed 2,110 members of staff. Again, adjusted for population, this leaves 1,460 volunteers in Scotland and 176 staff. However, if we measure environmental groups based on the number of sites they maintain, RSPB has only 40 reserves with varying levels of local community engagement. For comparison, as of Sep 14 2015, Friends of the Earth Scotland had only 10 local groups (concentrated mostly in large urban areas). Depending on how one measures "volunteerism," it may be possible that ECS has more engaged volunteers in Scotland as well - if each ECS group had only 4 "volunteers" then this would exceed RSPB.
[^15541313]: Kidwell, Jeremy. (2016). Eco-Congregation Scotland, 2014-2016. University of Edinburgh. http://dx.doi.org/10.7488/ds/1357.
[^15541342]:My dataset on transition towns will be made available later in 2016. Initial data was aquired from the Transition Scotland website http://www.transitionscotland.org/transition-in-scotland on December 10, 2014. We are currently in the process of collaboratively generating a more up-to-date dataset which will reflect their collaboration with SCCAN.
[^177171536]: For further detail on Dataset generation, see Kidwell, Forthcoming, 2018.
[^158261232]:Data was acquired from the Development Trusts Association website, http://www.dtascot.org.uk, accessed on 20 July 2015. As above, we are currently in the process of active collaboration with volunteers from the DTAS to co-generate a new dataset.
[^15541614]:PointX data for "Landscape Data" items is sourced from Ordnance Survey Land-Line and MasterMap(R) and the data points are augmented with additional information provided through research by PointX staff, and data aquired from unidentified "local data companie(s)" and the "118 Information" database (see: http://www.118information.co.uk). This data is under license and cannot be made available for use. It is important to note that I became aware of inaccuracies in this dataset over the course of use and subsequently generated my own dataset in collaboration with churches in Scotland. This will be made available later in 2016. I am in active conversation with OS about improving the quality of the data in PointX regarding places of worship.
[^15826124]:Interview with Margaret Warnock, 29 Aug 2014.
[^158261210]:From http://www.forthenvironmentlink.org, accessed 12 July 2015.
[^1554162]:From the Transition map key, "Green pins are 'official' groups
Blue pins are active communities who are connected to the Scottish Transition network Yellow pins show interest in this area"
[^15571030]:This was calculated by calculating a 10m wide footprint for every postcode in Scotland, areas which are not within 10m of a postcode (as of May 2014) are counted as uninhabited.
[^159142242]: Fiona Tweedia, *Ecumenical Audit: Questionnaire Findings* (2014).
[^15914204]:See note above regarding the data used from the PointX POI database. Note, for our research,we filtered out religious groups not represented within the Eco-Congregation footprint. We discuss representation by tradition and religion further below.adition and religion further below.

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\section[Introduction]{\texorpdfstring{Introduction\footnote{This
research was jointly funded by the AHRC/ESRC under project numnbers
AH/K005456/1 and AH/P005063/1.}}{Introduction}}\label{introduction15541312}}
Until recently, environmentalism has been treated by governments and
environmental charities as a largely secular concern. In spite of the
well-developed tradition of ``eco-theology'' which began in earnest in
the UK in the mid-twentieth century (and which has many precursors in
previous centuries), third-sector groups and governments, particularly
in Britain and Europe, have largely ignored religious groups as they
have gone about their business crafting agendas for behaviour change,
developing funding programmes, and developing platforms to mitigate
ecological harm, motivate consumers and create regulation regimes. That
this has changed is evidenced by the fact that several prominent
non-religious environmental groups have commissioned studies and crafted
outreach programmes to persons with a particular faith tradition or to
``spiritual communities'' including RSPB (2013) and the Sierra Club USA
(2008).\footnote{This is not to say that there have been no
collaborations before 2000, noteworthy in this respect is the WWF who
helped to found the Alliance of Religion and Conservation (ARC) in
1985.} Further, since 2008, the Scottish Government has provided a
significant portion of funding for the ecumenical charity,
Eco-Congregation Scotland, which works to promote literacy on
environmental issues in religious communities in Scotland and helps to
certify congregations under their award programme. What is not well
known, however, even by these religious environmental groups themselves,
is whether or how their membership might be different from other
environmental groups. This study represents an attempt to illuminate
this new interest with some more concrete data about religious groups in
Scotland and how they may differ from non-religious counterparts.
\hypertarget{eco-congregation-scotland-the-basics}{%
\section{Eco-Congregation Scotland: The
Basics}\label{eco-congregation-scotland-the-basics}}
There are 344 eco-congregations in Scotland. By some measurements,
particularly in terms of individual sites and possibly also with regards
to volunteers, this makes Eco-Congregation Scotland one of the largest
environmental third-sector groups in Scotland.\footnote{This suggestion
should be qualified - RSPB would greatly exceed ECS both in terms of
the number of individual subscribers and budget. The RSPB trustee's
report for 2013-2014 suggests that their member base was 1,114,938
people across Britain with a net income of £127m - the latter of which
exceeds the Church of Scotland. If we adjust this based on the
Scottish share of the population of the United Kingdom as of the 2011
census (8.3\%) this leaves us with an income of £9.93m. The British
charity commission requires charities to self-report the number of
volunteers and staff, and from their most recent statistics we learn
that RSPB engaged with 17,600 volunteers and employed 2,110 members of
staff. Again, adjusted for population, this leaves 1,460 volunteers in
Scotland and 176 staff. However, if we measure environmental groups
based on the number of sites they maintain, RSPB has only 40 reserves
with varying levels of local community engagement. For comparison, as
of Sep 14 2015, Friends of the Earth Scotland had only 10 local groups
(concentrated mostly in large urban areas). Depending on how one
measures ``volunteerism,'' it may be possible that ECS has more
engaged volunteers in Scotland as well - if each ECS group had only 4
``volunteers'' then this would exceed RSPB.}
In seeking to conduct GIS and statistical analysis of ECS, it is
important to note that there some ways in which these sites are
statistically opaque. Our research conducted through interviews at a
sampling of sites and analysis of a variety of documents suggests that
there is a high level of diversity both in terms of the number of those
participating in environmental action and the types of action underway
at specific sites. Work at a particular site can also ebb and flow over
the course of time. Of course, as research into other forms of activism
and secular environmental NGOs has shown, this is no different from any
other third sector volunteer group. Variability is a regular feature of
groups involved in activism and/or environmental concern.
For the sake of this analysis, we took each Eco-Congregation Scotland
site to represent a point of analysis as if each specific site
represented a community group which had ``opted-in'' on environmental
concern. On this basis, in this section, in the tradition of human
geography, we ``map'' environmental action among religious communities
in Scotland a variety of ways. This is the first major geographical
analysis of this kind conducted to date in Europe. We measure the
frequency and location of ECS sites against a variety of standard
geo-referenced statistical data sets, seeking to provide a statistical
and geographically based assessment of the participation of religious
groups in relation to the following:
\begin{itemize}
\tightlist
\item
Location within Scotland
\item
Religious affiliation
\item
Relation to the Scottish Index of Multiple Deprivation (SIMD)
\item
Relation to the 8-Fold Scottish Government Urban-Rural Scale
\item
Proximity to ``wilderness'' (based on several different designations)
\end{itemize}
For the sake of comparison, we also measured the geographical footprint
of two other forms of community group in Scotland, (1) Transition Towns
(taking into account their recent merge with Scotland Communities
Climate Action Network) and (2) member groups of the Development Trust
Association Scotland (``DTAS''). These two groups provide a helpful
basis for comparison as they are not centralised and thus have a
significant geographical dispersion across Scotland. They also provide a
useful comparison as transition is a (mostly) non-religious
environmental movement, and community development trusts are not
explicitly linked to environmental conservation (though this is often
part of their remit), so we have a non-religious point of comparison in
Transition and a non-environmental point of comparison with DTAS
\hypertarget{technical-background}{%
\section{Technical Background}\label{technical-background}}
Analysis was conducted using QGIS 2.8 and R 3.5.2, and data-sets were
generated in CSV format.\footnote{Kidwell, Jeremy. (2016).
Eco-Congregation Scotland, 2014-2016. University of Edinburgh.
\url{http://dx.doi.org/10.7488/ds/1357}.} To begin with, I assembled a
data set consisting of x and y coordinates for each congregation in
Scotland and collated this against a variety of other specific data.
Coordinates were checked by matching UK postcodes of individual
congregations against geo-referencing data in the Office for National
Statistics postcode database. In certain instances a single
``congregation'' is actually a series of sites which have joined
together under one administrative unit. In these cases, each site was
treated as a separate data point if worship was held at that site at
least once a month, but all joined sites shared a single unique
identifier. As noted above, two other datasets were generated for the
sake of comparative analysis.\footnote{For further detail on Dataset
generation, see Kidwell, Forthcoming, 2018.} These included one
similar Environmental Non-Governmental Organisation (ENGO) in Scotland
(1) Transition Scotland (which includes Scotland Communities Climate
Action Network);\footnote{My dataset on transition towns will be made
available later in 2016. Initial data was aquired from the Transition
Scotland website
\url{http://www.transitionscotland.org/transition-in-scotland} on
December 10, 2014. We are currently in the process of collaboratively
generating a more up-to-date dataset which will reflect their
collaboration with SCCAN.} and another community-based NGO, Scottish
Community Development Trusts.\footnote{Data was acquired from the
Development Trusts Association website,
\url{http://www.dtascot.org.uk}, accessed on 20 July 2015. As above,
we are currently in the process of active collaboration with
volunteers from the DTAS to co-generate a new dataset.} As this report
will detail, these three overlap in certain instances both literally and
in terms of their aims, but each also has a separate identity and
footprint in Scotland. Finally, in order to normalise data, we utilised
the PointX POI dataset which maintains a complete database of Places of
Worship in Scotland.\footnote{PointX data for ``Landscape Data'' items
is sourced from Ordnance Survey Land-Line and MasterMap(R) and the
data points are augmented with additional information provided through
research by PointX staff, and data aquired from unidentified ``local
data companie(s)'' and the ``118 Information'' database (see:
\url{http://www.118information.co.uk}). This data is under license and
cannot be made available for use. It is important to note that I
became aware of inaccuracies in this dataset over the course of use
and subsequently generated my own dataset in collaboration with
churches in Scotland. This will be made available later in 2016. I am
in active conversation with OS about improving the quality of the data
in PointX regarding places of worship.}
\hypertarget{background-and-history-of-eco-congregation-scotland}{%
\section{Background and History of Eco-Congregation
Scotland}\label{background-and-history-of-eco-congregation-scotland}}
Eco-Congregation Scotland began a year before the official launch of
Eco-Congregation England and Wales, in 1999, as part of an effort by
Kippen Environment Centre (later renamed to Forth Environment Link, or
``FEL'') a charity devoted to environmental education in central
Scotland\footnote{From \url{http://www.forthenvironmentlink.org},
accessed 12 July 2015.} to broaden the scope of its environmental
outreach to churches in central Scotland.\footnote{Interview with
Margaret Warnock, 29 Aug 2014.} Initial funding was provided, through
Kippen Environment Centre by way of a ``sustainable action grant'' (with
funds drawn from a government landfill tax) through a government
programme called Keep Scotland Beautiful (the Scottish cousin of Keep
Britain Tidy). After this initial pilot project concluded, the Church of
Scotland provided additional funding for the project in the form of
staff time and office space. Additional funding a few years later from
the Scottish Government helped subsidise the position of a business
manager, and in 2011 the United Reformed Church contributed additional
funding which subsidised the position of a full-time environmental
chaplain for a 5-year term, bringing the total staff to five.
The programme launched officially in 2001 at Dunblane Cathedral in
Stirling and by 2005 the project had 89 congregations registered to be a
part of the programme and 25 which had completed the curriculum
successfully and received an Eco-Congregation award. By 2011, the number
of registrations had tripled to 269 and the number of awarded
congregations had quadrupled to
\texttt{sum(ecs\$award1\ \textless{}\ "01/01/2012",\ na.rm=TRUE)}. This
process of taking registrations and using a tiered award or recognition
scheme is common to many voluntary organisations. The ECS curriculum was
developed in part by consulting the Eco-Congregation England and Wales
materials which had been released just a year earlier in 1999, though it
has been subsequently revised, particularly with a major redesign in
2010. In the USA, a number of similar groups take a similar approach
including Earth Ministry (earthministry.org) and Green Faith
(greenfaith.org).
In the case of Eco-Congregation Scotland, congregations are invited to
begin by ``registering'' their interest in the programme by completing a
basic one-sided form. The next step requires the completion of an award
application, which includes a facilitated curriculum called a ``church
check-up'' and after an application is submitted, the site is visited
and assessed by third-party volunteer assessors. Sites are invited to
complete additional applications for further awards which are
incremental (as is the application process). Transition communities, at
least in the period reflected on their map, go through a similar process
(though this does not involve the use of a supplied curriculum) by which
they are marked first as ``interested,'' become ``active'' and then gain
``official'' status.\footnote{From the Transition map key, ``Green pins
are `official' groups Blue pins are active communities who are
connected to the Scottish Transition network Yellow pins show interest
in this area''}
\hypertarget{representation-by-regional-authorities-council-areas}{%
\section{Representation by Regional Authorities (Council
Areas)}\label{representation-by-regional-authorities-council-areas}}
Perhaps the first important question to ask of these groups is, where
are they? I calculated the spread of eco-congregations and transition
groups across each of the 32 council areas in Scotland. Every council
area in Scotland has at least one eco-congregation or transition group).
The most are located in , with 48, whereas the mean among all the 32
council areas is 10.75, with a median of 8, standard deviation of
9.4698162, and interquartile range of 11.5. The following choropleth
maps show the relative concentration of eco-congregations (indicated by
yellow to red).
(\emph{TODO: need to implement}) Though there are too few
eco-congregations and transition groups for a numerically significant
representation in any of the intermediate geographies, mapping the
concentration of sites by agricultural parishes allows for a more
granular visual and I include this for comparison sake. Note, for the
sake of a more accurate visual communication, we have also marked out
areas of Scotland that are uninhabited with hash marks on the map of
agricultural parishes. (\emph{TODO: this will be done in the final
draft, once I get my image masking fixed!}).\footnote{This was
calculated by calculating a 10m wide footprint for every postcode in
Scotland, areas which are not within 10m of a postcode (as of May
2014) are counted as uninhabited.}
\begin{figure}
\centering
\includegraphics{figures/plot_admin_ecs_choropleth-1.pdf}
\caption{Figure 1}
\end{figure}
\includegraphics{figures/plot_admin_ecs_normed_choropleth-1.pdf}
\includegraphics{figures/plot_admin_ecs_normed_choropleth-2.pdf}
Given the way population and places of worship are unevenly distributed
across Scotland it is important to represent data in terms of relative
distribution. For this study, we attempted to ``normalise'' our data in
two different ways, (1) as shown by Figure 2 above, by taking population
figures from the 2011 census (see data sheet in Appendix A) and (2) by
adjusting relative to the number of places of worship in each council
region.\footnote{See note above regarding the data used from the PointX
POI database. Note, for our research,we filtered out religious groups
not represented within the Eco-Congregation footprint. We discuss
representation by tradition and religion further below.adition and
religion further below.} The latter of these two can yield
particularly unexpected results. Thus, of the 4048 ``places of worship''
in Scotland, the highest concentration is actually the region, with 435,
second is 329 (). Rank of Council Areas by population and number of
places of worship is also included in Appendix A.
We can use this data to normalise our figures regarding Eco-Congregation
Scotland communities and this draws the presence in Edinburgh of ECS
communities into even sharper relief, as Edinburgh, though ranked second
in terms of population and fifth in terms of places of worship, ranks
first for the presence of all ECS congregations and awarded ECS
congregations. However, taking population as the basis for normalisation
first, we find that Edinburgh is far from the most prominent outlier. In
trying to communicate this difference for a lay-audience, we have chosen
to list this difference as a multiplier (i.e.~there are 2.x times as
many congregations as their share of population and an average figure of
congregations might allow for) as this conveys the difference in a
straight-forward way. Outliers where the disparity between their
relative share of the total ECS footprint and their relative share of
population is different by a positive ratio of more than double include
the Orkney Islands (3.7 times more eco-congregations than their expected
average share based on population), Argyll and Bute
(\texttt{admin\_lev1{[}CODE=S12000023{]}\$ecs\_pop\_factor} 4.2x),
Stirling (2.76x), and Perthshire and Kinross (2.18x). Interestingly,
there are no outliers whose relative share of the total footprint of ECS
is double or more in the negative direction (see Appendix A chart for
full numbers).
Turning to the total of 4048 ``places of worship'' in Scotland, we find
a slightly different picture of the relative concentration of
Eco-Congregations in Scotland. In this case, the outliers are
Whereas our initial measurements indicated a prominent lead for
Edinburgh, by normalising our data in this way we can highlight the
stronger-than-expected presence of several others that might otherwise
escape notice because they lie in a region with significantly lower
population or numerically less places of worship. Taking the PointX data
on ``places of worship'' in Scotland, we find a less dramatic picture,
but also a slightly different one. The positive outliers include East
Renfrewshire (3.4x) Edinburgh (2.9x), Stirling (2.2), West Lothian
(1.9x) and Aberdeen (1.5x). Again, negative outliers are far less
dramatic, with only Midlothian possessing a ratio of more than 100\%
negative difference from the number of ``places of worship'' at 1.5x
\emph{fewer}.
\includegraphics{figures/create_admin_barplot-1.pdf}
\includegraphics{figures/create_choropleth_others-1.pdf}
\includegraphics{figures/create_choropleth_others-2.pdf}
\includegraphics{figures/create_choropleth_others-3.pdf}
We can compare the representation in these various regions against our
comparison groups to see how other community-based organisations cluster
in Scottish administrative districts. Here there are some significant
contrasts. Scottish Community Development trusts are most intensely
concentrated in the Highlands and Argyll \& Bute. But, this is
consistent with all the other categories, Eco-Congregations, Places of
Worship, and dtas are all over-represented in this area, varying only by
the degree. Edinburgh is different, here we find that Eco-Congregations
and Transition projects are over-represented, while dtass are
under-represented. Finally, the highlands are another strong contrast,
here we find a very strong over-representation by transition towns and
dtass while the representation of Eco-Congregations is relatively close
to the population share for that area. The two areas of greatest
contrast for Eco-Congregations from the other groups are unsurprising,
Edinburgh is the location of the ECS offices, while Stirling is the area
in which ECS first began (see Appendix B for full data).
\hypertarget{christian-denominations}{%
\section{Christian Denominations}\label{christian-denominations}}
Eco-Congregation Scotland describes itself as an ``ecumenical movement
helping local groups of Christians link environmental issues to their
faith, reduce their environmental impact and engage with their local
community.'' There are several ties to the Church of Scotland, as the
denomination provides office space to Eco-Congregation Scotland in the
Church of Scotland complex at 121 George Street in Edinburgh and
provides funding for one full-time member of staff. In spite of this,
ECS has, from the start, attempted to emphasise its ecumenical
aspirations and this is reflected in a wide variety of ways. The name
``eco-congregation'' is meant to be tradition neutral (in interviews,
staff noted how they have sought to avoid names such as ``eco-kirk''
which would be the more obvious Presbyterian title, or ``eco-community''
or ``eco-church'' which might indicate allegiance towards another).
Further, the group has a environmental chaplain on their staff whose
position is funded by the United Reformed Church, and other members of
staff are funded by the Scottish government, and as such, carry no
formal affiliation with a religious institution. This diversity and
ecumenicism is reflected in a membership which is, though dominated by
the Church of Scotland, nevertheless, made up of a range of Christian
traditions.
Though these are not numerically significant, it is important to note
that some member congregations describe themselves as ecumenical
communities, and others are hybrids reflecting the merging of two
traditions. As this ecumenical/hybrid designation involves a small
number of the overall total, for the sake of this research, these have
been combined into a category called ``ecumenical.'' Further, as
research conducted by Church of Scotland statistician Fiona Tweedie has
shown, in many Scottish communities with only one church, members of
this church will specify their denominational affiliation in a variety
of ways (Roman Catholic, Quaker, Methodist, etc.) even though the church
and its minister are formally affiliated with the Church of
Scotland.\footnote{Fiona Tweedia, \emph{Ecumenical Audit: Questionnaire
Findings} (2014).} So, we should be careful not to assume that the
various denominational affiliations of eco-congregations are indicative
in an absolute way.
A wide variety of historians and sociologists of religion have noted the
regional significance of different Christian denominations in Scotland
so we sought to assess the relative distribution and concentration of
eco-congregations by denomination. Finding comparative statistics is a
complex task, made more complicated by several factors. First, most
demographic data on religious belonging in Scotland comes in the form of
the 2011 census and as such is far more atomised than this data-set
which identifies groups at the level of ``congregations'' rather than
individuals. Equating these two is also complex, as participation by
members of congregations can be measured in a variety of ways, there are
often a small number of active participants in each eco-congregation
group, but may also be a large scale, but passive, support by the wider
community.
So why provide this kind of data (i.e.~at the level of individual
churches) when more granular data (i.e.~at the level of individuals
persons) is available in the form of the census and related parallel
publications such as the 2008 Scottish Environmental Attitudes survey?
We believe that mapping places of worship provides a useful intermediate
level of analysis and may complement our more atomised understanding of
EA which has been assessed at the level of individual persons to date.
Because representation within some administrative areas of Scotland, can
lead to a small number of data points, we have kept analysis to a
National level and have not provided more specific administrative-area
level calculations.
\begin{longtable}[]{@{}lr@{}}
\caption{ECS by denomination}\tabularnewline
\toprule
& x\tabularnewline
\midrule
\endfirsthead
\toprule
& x\tabularnewline
\midrule
\endhead
Baptist & 4\tabularnewline
C of S & 254\tabularnewline
C of S / URC & 3\tabularnewline
Cong & 1\tabularnewline
Ecu & 5\tabularnewline
FCS & 1\tabularnewline
Independent & 2\tabularnewline
Meth & 4\tabularnewline
Non. & 1\tabularnewline
Quaker & 1\tabularnewline
RC & 15\tabularnewline
SEC & 41\tabularnewline
Unitarian & 1\tabularnewline
URC & 11\tabularnewline
\bottomrule
\end{longtable}
As one might expect, there is a strong representation of the Church of
Scotland, almost 74\% of eco-congregations, with this number remaining
the same when we only count awarded sites. We can confirm, on the basis
of this analysis that ECS has a disproportional representation by Church
of Scotland churches. At the 2002 church census count, it only
represented 40.20\% of Scottish churches (1666 of 4144 total churches).
Similarly, on the 2011 Scottish census, only 32.44\% of persons claimed
to be members of the Church of Scotland. We can adjust this
representation to 60\%, if one excludes the 2,445,204 persons (46\% of
the total on the census) who reported either ``no religion'' or
adherence to a religious tradition not currently represented among the
eco-congregation sites. There is a slight over-representation by the
United Reformed church, though this seems considerably more dramatic
when one takes into account the fact that this is a trebling or more of
their overall share of Scottish churches. The URC makes up only sightly
more than 1\% of church buildings in Scotland and a tiny 0.04\% of
respondents to the 2011 census. The Scottish Episcopal church hovers
right around a proportional representation within ECS. More concerning
are the significant underrepresentation by Roman Catholic churches,
Baptists, the Free Church of Scotland, and other independent churches.
While Roman Catholic churches make up just over 10\% of the church
buildings in Scotland, less than 5\% of churches registered as
eco-congregations are RC. Even more dramatic is the quartering of
baptist churches, and the non-existent representation among the
significant group of independent churches and small denominations. These
make up nearly 25\% of all Scottish churches (over a thousand) and yet
only 4 have registered as eco-congregations. We provide several
tentative advisories in response to these under-representations in the
final section of this paper.
\hypertarget{eco-congregations-urban-rural-and-remote}{%
\section{Eco-Congregations, Urban, Rural and
Remote}\label{eco-congregations-urban-rural-and-remote}}
\begin{verbatim}
## OGR data source with driver: ESRI Shapefile
## Source: "/Users/jeremy/gits/mapping_environmental_action/data", layer: "SG_UrbanRural_2016"
## with 8 features
## It has 6 fields
\end{verbatim}
Rather than bifurcate congregations into an urban/rural dichotomy, for
this study we used the Scottish Government's six-point remoteness scale
to categorise eco-congregations along a spectrum of highly populated to
remote areas. This 8-fold scale (calculated biennially) offers a more
nuanced measurement that combines measurements of remoteness and
population along the following lines:
\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\tightlist
\item
Large Urban Areas - Settlements of over 125,000 people.
\item
Other Urban Areas - Settlements of 10,000 to 125,000 people.
\item
Accessible Small Towns - Settlements of between 3,000 and 10,000
people, and within a 30 minute drive time of a Settlement of 10,000 or
more.
\item
Remote Small Towns - Settlements of between 3,000 and 10,000 people,
and with a drive time between 30 and 60 minutes to a Settlement of
10,000 or more.
\item
Very Remote Small Towns - Settlements of between 3,000 and 10,000
people, and with a drive time of over 60 minutes to a Settlement of
10,000 or more.
\item
Accessible Rural Areas - Areas with a population of less than 3,000
people, and within a drive time of 30 minutes to a Settlement of
10,000 or more.
\item
Remote Rural Areas - Areas with a population of less than 3,000
people, and with a drive time of between 30 and 60 minutes to a
Settlement of 10,000 or more.
\item
Very Remote Rural Areas - Areas with a population of less than 3,000
people, and with a drive time of over 60 minutes to a Settlement of
10,000 or more.
\end{enumerate}
The key question which this analysis seeks to answer is whether ECS, or
the other groups surveyed, are more concentrated in Urban or Rural
areas, so as is the case below with our analysis of deprivation, we are
concerned with the outer conditions, i.e.~the urban areas (items 1-2)
and remote areas (items 7-8).
Of all the groups surveyed in this study, Eco-Congregation Scotland is
the most heavily concentrated in large urban areas (33.53\%), exceeding
by almost 50\% the rate for all places of worship (22.96\% in large
urban areas). Transition is a much more modest 20\% and development
trusts a bit lower at 15\%. It is interesting to note that the rate of
ECS concentration in these large urban areas matches the level of
overall population distribution (34.5\%). On the other end of the scale,
Eco-Congregation Scotland is the least concentrated in remote rural
areas (with 3.93\% on level 7 and 5.44\% on level 8 on the urban-rural
scale), though again, they correlate roughly to the general population
distribution (3.2\% and 2.9\% respectively). Places of worship outpace
both the population of Scotland and the footprint of Eco-Congregation
Scotland, with 14.98\% in very remote rural areas, but this is exceeded
by transition at 16.47\% and both by Scottish community development
trusts at 32.14\%. So while Eco-Congregation Scotland correlates roughly
with Scottish population distribution across the urban-rural scale, it
has a considerably more urban profile than either of the other two
groups surveyed.
\includegraphics{figures/create_ur_barplot-1.pdf}
\begin{figure}
\centering
\includegraphics{figures/create_urbanrural_ecs_chart_choropleth-1.pdf}
\caption{Figure 9}
\end{figure}
\hypertarget{wealth-employment-and-literacy}{%
\section{Wealth, Employment, and
Literacy}\label{wealth-employment-and-literacy}}
\begin{verbatim}
## OGR data source with driver: ESRI Shapefile
## Source: "/Users/jeremy/gits/mapping_environmental_action/data", layer: "sc_dz_11"
## with 6976 features
## It has 9 fields
\end{verbatim}
\includegraphics{figures/create_simd_barplot-1.pdf}
Another crucial point of assessment relates to the relation of
Eco-Congregation communities to the Scottish Index of Multiple
Deprivation. This instrument aggregates a large variety of factors which
can lead to deprivation including crime rates, employment levels, access
to services (implicating remoteness), and literacy. By assessing ECS,
Transition, and dtas against the deprivation scale, we can assess
whether eco-congregations fall within particular demographics and also
whether the fully aggregated SIMD measurement provides a useful point of
comparison for our purposes. The SIMD essentially divides Scotland into
6407 geographic zones and then ranks them based on their relative
deprivation. This data set can be split into any number of groups, but
for our purposes we have settled on Quintiles, splitting the SIMD data
set at every 1302 entries. We then measured where each transition group,
ECS, and dtas fell within these zones and calculated how they fell into
these five quintiles, from more to least deprived.
The first, and most compelling finding is that, in general
Eco-Congregation Scotland and Transition Scotland are both roughly the
same and match the level of population distribution in the lowest
quintile of the general SIMD measurement. 8\% of transition groups and
eco-congregation groups which have received awards and 9\% of the
population are located within this quintile. However, taken in relation
to the distribution of places of worship in the lowest quintile, we find
that eco-congregations are located at half the rate that places of
worship are (15\%) and dtass match this much more closely at 14\%.
Turning towards the top quintile, this pattern also holds, here both
transition groups (21\%) and eco-congregations (21\% and 29\% of awarded
congregations) depart from the population distribution in this upper
quintile (which is 10\%). Again, general places of worship (at 11\%) and
DTASs (at 5\%) take the opposite direction. We can say decisively that
in communities which have been identified as good candidates for
intervention to reduce deprivation, ECS and Transition are less likely,
and they are over-represented at the areas which fall into the least
deprived quintile.
We can find divergence between transition communities and
eco-congregation when we split out SIMD domains. In the lowest quartile,
measuring exclusively for the income domain, ECS is more represented
(11\%) - roughly the same as DTAS (12\%), and transition is less (6\%)
represented. In general (as shown on the chart in Appendix D), these
trends hold when representation of our groups are measured within other
non-remoteness domains of the SIMD. Our basic conclusion is that
transition towns are least likely to operate within the lowest quartile
of SIMD and DTASs are most likely, with ECS somewhere in the middle.
Given the general disparity against the presence of places of worship,
it seems fair to suggest that this might be an area for improvement,
perhaps even worth developing a special programme which might target
areas in SIMD quartile 1 for eco-congregation outreach. This might be
considered particularly in light of the starkest underrepresentation of
ECS and transition within the SIMD domain of education, skills, and
training.
\begin{verbatim}
## Reading layer `SSSI_SCOTLAND' from data source `/Users/jeremy/gits/mapping_environmental_action/data/SSSI_SCOTLAND.shp' using driver `ESRI Shapefile'
## Simple feature collection with 15872 features and 7 fields
## geometry type: POLYGON
## dimension: XY
## bbox: xmin: -296506.9 ymin: 530237.9 xmax: 467721.5 ymax: 1220310
## epsg (SRID): NA
## proj4string: +proj=tmerc +lat_0=49 +lon_0=-2 +k=0.9996012717 +x_0=400000 +y_0=-100000 +datum=OSGB36 +units=m +no_defs
\end{verbatim}
\begin{verbatim}
## Reading layer `WILDLAND_SCOTLAND' from data source `/Users/jeremy/gits/mapping_environmental_action/data/WILDLAND_SCOTLAND.shp' using driver `ESRI Shapefile'
## Simple feature collection with 42 features and 3 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: 76877.24 ymin: 578454.1 xmax: 435367.1 ymax: 1190510
## epsg (SRID): NA
## proj4string: +proj=tmerc +lat_0=49 +lon_0=-2 +k=0.9996012717 +x_0=400000 +y_0=-100000 +datum=OSGB36 +units=m +no_defs
\end{verbatim}
\begin{verbatim}
## Reading layer `National_Forest_Inventory_Woodland_Scotland_2017' from data source `/Users/jeremy/gits/mapping_environmental_action/data/National_Forest_Inventory_Woodland_Scotland_2017.shp' using driver `ESRI Shapefile'
## Simple feature collection with 199698 features and 7 fields
## geometry type: POLYGON
## dimension: XY
## bbox: xmin: 65210.1 ymin: 532547.9 xmax: 461253.7 ymax: 1209179
## epsg (SRID): NA
## proj4string: +proj=tmerc +lat_0=49 +lon_0=-2 +k=0.9996012717 +x_0=400000 +y_0=-100000 +datum=OSGB36 +units=m +no_defs
\end{verbatim}
\hypertarget{proximity-to-wilderness}{%
\section{Proximity to ``Wilderness''}\label{proximity-to-wilderness}}
Chasing down a curiosity, I decided to try and calculate whether
proximity to ``wilderness'' or ``scenic nature'' or just trees might
have some impact on generating more mobilised communities. I realised
that there would be several problems with this kind of calculation up
front, first being that ``nature'' is a deeply problematic construct,
reviled by geographers and philosophers alike. With this in mind, I
identified several different ways of reckoning wilderness, starting with
the highly anachronistic ``Scenic Land'' designation from the 1970s.
Then I pursued the more carefully calculated ``core wild areas''
generated by SNH just a few years ago. However, even the core wile areas
concept has been criticised heavily, so I also expanded out my search to
include all sites of special scientific interest and then went even
wider to include the Scottish Forestry Service's ``Native Woodland'' and
finally, the most generic possible measurement, any land identified as
forested at the last Forest Inventory.
Proximity to these areas was the next concern, because many of these
designations deliberately exclude human habitat, so it was necessary to
measure the number of sites within proximity. There is a question which
lies here regarding aesthetics, namely, what sort of proximity might
generate an affective connection? From my own experience, I decided upon
the distance represented by a short walk, i.e.~a half-kilometre.
However, with the more generic measurements, such as SSSI and
forestation, this wouldn't do, as there are so many of these sites that
a buffer of 500 meters encapsulates almost all of inhabited Scotland. So
for these sites I also calculated a count within 50 metres.
So what did I discover? The results were inconclusive. First, it is
important to note that on the whole, Eco-Congregations tend to be more
urban than place of worship taken generally at a rate of nearly 3:1
(5.4\% of Eco-Congregations lie in areas currently designated as ``Very
Remote Rural Areas'' whereas nearly 15\% of places of worship lie in
these areas), so what I was testing for was whether this gap was smaller
when specifying these various forms of ``wild'' remoteness. For our
narrowest measurements, there were so few sites captured as to render
measurement unreliable. There are, for obvious reasons, 0 sites located
within any of SNG's core wild areas. Similarly, there are very few of
our activist communities located within SSSI's (only
\texttt{st\_within(pow\_pointX\_sf,\ sssi)} places of worship out of
over 4k, 2 transition towns, (or 2\%) and 7 community development trusts
(3\%)). However, expanding this out makes things a bit more interesting,
within 50 metres of SSSI's in Scotland lie
\texttt{st\_within(ecs\_sf,\ st\_buffer(sssi,\ dist\ =\ 50))}
Eco-Congregations (or just under 1\%), which compares favourably with
the
\texttt{st\_within(pow\_pointX\_sf,\ st\_buffer(sssi,\ dist\ =\ 50))}
places of worship (or just 1.5\%) far exceeding our ratio (1:1.5
vs.~1:3). This is the same with our more anachronistic measure of
``scenic areas,'' there are 7 eco-congregations within these areas, and
175 places of worship, making for a ratio of nearly 1:2 (2.1\%
vs.~4.3\%). Taking our final measure, of forested areas, this is hard to
calculate, as only one Eco-Congregation lies within either native or
generally forested land.
\begin{verbatim}
## [1] 0 3 59
\end{verbatim}
\begin{verbatim}
## [1] 7 62 610
\end{verbatim}
\includegraphics{figures/wilderness_plots-1.pdf}
\includegraphics{figures/wilderness_plots-2.pdf}
\hypertarget{appendix-a}{%
\section{Appendix A}\label{appendix-a}}
\hypertarget{appendix-b}{%
\section{Appendix B}\label{appendix-b}}
(JK note to self: same as above, but augmented with multipliers by which
categories are different from one another)
\hypertarget{appendix-c---data-by-urban-rural-classification}{%
\section{Appendix C - Data by Urban / Rural
Classification}\label{appendix-c---data-by-urban-rural-classification}}
\renewcommand\refname{Citations}
\bibliography{biblio.bib}
\end{document}

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library/
python/
staging/

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local({
# the requested version of renv
version <- "0.9.3"
# avoid recursion
if (!is.na(Sys.getenv("RENV_R_INITIALIZING", unset = NA)))
return(invisible(TRUE))
# signal that we're loading renv during R startup
Sys.setenv("RENV_R_INITIALIZING" = "true")
on.exit(Sys.unsetenv("RENV_R_INITIALIZING"), add = TRUE)
# signal that we've consented to use renv
options(renv.consent = TRUE)
# load the 'utils' package eagerly -- this ensures that renv shims, which
# mask 'utils' packages, will come first on the search path
library(utils, lib.loc = .Library)
# check to see if renv has already been loaded
if ("renv" %in% loadedNamespaces()) {
# if renv has already been loaded, and it's the requested version of renv,
# nothing to do
spec <- .getNamespaceInfo(.getNamespace("renv"), "spec")
if (identical(spec[["version"]], version))
return(invisible(TRUE))
# otherwise, unload and attempt to load the correct version of renv
unloadNamespace("renv")
}
# construct path to renv in library
libpath <- local({
root <- Sys.getenv("RENV_PATHS_LIBRARY", unset = "renv/library")
prefix <- paste("R", getRversion()[1, 1:2], sep = "-")
# include SVN revision for development versions of R
# (to avoid sharing platform-specific artefacts with released versions of R)
devel <-
identical(R.version[["status"]], "Under development (unstable)") ||
identical(R.version[["nickname"]], "Unsuffered Consequences")
if (devel)
prefix <- paste(prefix, R.version[["svn rev"]], sep = "-r")
file.path(root, prefix, R.version$platform)
})
# try to load renv from the project library
if (requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) {
# warn if the version of renv loaded does not match
loadedversion <- utils::packageDescription("renv", fields = "Version")
if (version != loadedversion) {
# assume four-component versions are from GitHub; three-component
# versions are from CRAN
components <- strsplit(loadedversion, "[.-]")[[1]]
remote <- if (length(components) == 4L)
paste("rstudio/renv", loadedversion, sep = "@")
else
paste("renv", loadedversion, sep = "@")
fmt <- paste(
"renv %1$s was loaded from project library, but renv %2$s is recorded in lockfile.",
"Use `renv::record(\"%3$s\")` to record this version in the lockfile.",
"Use `renv::restore(packages = \"renv\")` to install renv %2$s into the project library.",
sep = "\n"
)
msg <- sprintf(fmt, loadedversion, version, remote)
warning(msg, call. = FALSE)
}
# load the project
return(renv::load())
}
# failed to find renv locally; we'll try to install from GitHub.
# first, set up download options as appropriate (try to use GITHUB_PAT)
install_renv <- function() {
message("Failed to find installation of renv -- attempting to bootstrap...")
# ensure .Rprofile doesn't get executed
rpu <- Sys.getenv("R_PROFILE_USER", unset = NA)
Sys.setenv(R_PROFILE_USER = "<NA>")
on.exit({
if (is.na(rpu))
Sys.unsetenv("R_PROFILE_USER")
else
Sys.setenv(R_PROFILE_USER = rpu)
}, add = TRUE)
# prepare download options
pat <- Sys.getenv("GITHUB_PAT")
if (nzchar(Sys.which("curl")) && nzchar(pat)) {
fmt <- "--location --fail --header \"Authorization: token %s\""
extra <- sprintf(fmt, pat)
saved <- options("download.file.method", "download.file.extra")
options(download.file.method = "curl", download.file.extra = extra)
on.exit(do.call(base::options, saved), add = TRUE)
} else if (nzchar(Sys.which("wget")) && nzchar(pat)) {
fmt <- "--header=\"Authorization: token %s\""
extra <- sprintf(fmt, pat)
saved <- options("download.file.method", "download.file.extra")
options(download.file.method = "wget", download.file.extra = extra)
on.exit(do.call(base::options, saved), add = TRUE)
}
# fix up repos
repos <- getOption("repos")
on.exit(options(repos = repos), add = TRUE)
repos[repos == "@CRAN@"] <- "https://cloud.r-project.org"
options(repos = repos)
# check for renv on CRAN matching this version
db <- as.data.frame(available.packages(), stringsAsFactors = FALSE)
if ("renv" %in% rownames(db)) {
entry <- db["renv", ]
if (identical(entry$Version, version)) {
message("* Installing renv ", version, " ... ", appendLF = FALSE)
dir.create(libpath, showWarnings = FALSE, recursive = TRUE)
utils::install.packages("renv", lib = libpath, quiet = TRUE)
message("Done!")
return(TRUE)
}
}
# try to download renv
message("* Downloading renv ", version, " ... ", appendLF = FALSE)
prefix <- "https://api.github.com"
url <- file.path(prefix, "repos/rstudio/renv/tarball", version)
destfile <- tempfile("renv-", fileext = ".tar.gz")
on.exit(unlink(destfile), add = TRUE)
utils::download.file(url, destfile = destfile, mode = "wb", quiet = TRUE)
message("Done!")
# attempt to install it into project library
message("* Installing renv ", version, " ... ", appendLF = FALSE)
dir.create(libpath, showWarnings = FALSE, recursive = TRUE)
# invoke using system2 so we can capture and report output
bin <- R.home("bin")
exe <- if (Sys.info()[["sysname"]] == "Windows") "R.exe" else "R"
r <- file.path(bin, exe)
args <- c("--vanilla", "CMD", "INSTALL", "-l", shQuote(libpath), shQuote(destfile))
output <- system2(r, args, stdout = TRUE, stderr = TRUE)
message("Done!")
# check for successful install
status <- attr(output, "status")
if (is.numeric(status) && !identical(status, 0L)) {
text <- c("Error installing renv", "=====================", output)
writeLines(text, con = stderr())
}
}
try(install_renv())
# try again to load
if (requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) {
message("Successfully installed and loaded renv ", version, ".")
return(renv::load())
}
# failed to download or load renv; warn the user
msg <- c(
"Failed to find an renv installation: the project will not be loaded.",
"Use `renv::activate()` to re-initialize the project."
)
warning(paste(msg, collapse = "\n"), call. = FALSE)
})

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external.libraries:
ignored.packages:
package.dependency.fields: Imports, Depends, LinkingTo
snapshot.type: packrat
use.cache: TRUE
vcs.ignore.library: TRUE

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#!/bin/bash
#SBATCH --mail-type ALL
#SBATCH --cpus-per-task 1
#SBATCH --time 180:0
#SBATCH --ntasks 20
#SBATCH --qos bbdefault
module purge; module load bluebear
module load R/3.5.0-iomkl-2018a-X11-20180131
module load Pandoc/2.3.1
module load plotly/4.7.1-iomkl-2018a-R-3.5.0
module load rgeos/0.3-28-iomkl-2018a-R-3.5.0
module load tmap/2.2-iomkl-2018a-R-3.5.0
Rscript -e 'library(rmarkdown); rmarkdown::render("mapping_draft-hpc_optimised.Rmd", "html_document")'
cp mapping_draft.html /rds/projects/2016/kidwellj-01/mapping_environmental_action/
cp figures/* /rds/projects/2016/kidwellj-01/mapping_environmental_action/figures
cp derivedData/* /rds/projects/2016/kidwellj-01/mapping_environmental_action/derivedData

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@ -1,26 +0,0 @@
require(RCurl) # used for fetching reproducible datasets
require(sf) # new simplefeature data class, supercedes sp in many ways
# using GEOS 3.6.1, GDAL 2.1.3, PROJ 4.9.3
require(sp) # needed for proj4string, deprecated by sf()
require(rgdal) # version version: 1.3-6
if (file.exists("data/National_Forest_Inventory_Woodland_Scotland_2017.shp") == FALSE) {
download.file("https://opendata.arcgis.com/datasets/3cb1abc185a247a48b9d53e4c4a8be87_0.zip?outSR=%7B%22wkid%22%3A27700%2C%22latestWkid%22%3A27700%7D",
destfile = "data/National_Forest_Inventory_Woodland_Scotland_2017.zip")
unzip("data/National_Forest_Inventory_Woodland_Scotland_2017.zip", exdir = "data")
}
forest_inventory <- st_read("data/National_Forest_Inventory_Woodland_Scotland_2017.shp")
forest_inventory_sp <- readOGR("./data", "National_Forest_Inventory_Woodland_Scotland_2017")
system.time(
ggplot() +
geom_sf(data = forest_inventory)
)
system.time(
ggplot() +
geom_polygon(data = forest_inventory_sp)
)

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@ -1,66 +0,0 @@
# Plot SSSI polygons with ECS points (using sp, for now)
ggplot() +
geom_polygon(aes(x = long, y = lat, group = group),
data = sssi_sp,
colour = 'black',
alpha = .7,
size = .005) +
geom_point(aes(X, Y, fill = NULL, group = NULL), size = 1, data=ecs_df,
colour = "black",
fill = "white",
size = .15,
stroke = .002,
alpha = .6,
show.legend = TRUE) +
labs(x = NULL, y = NULL, fill = "Groups",
title = "Figure 11",
subtitle="Sites of Special Scientific Interest with points marked",
caption = paste("Jeremy H. Kidwell :: jeremykidwell.info",
"Data: UK Data Service (OGL) & Jeremy H. Kidwell",
"You may redistribute this graphic under the terms of the CC-by-SA 4.0 license.",
sep = "\n"))
# # ggplot using sf seems to be severely broken for now. Commenting out and reverting to sp
# if (utils::packageVersion("ggplot2") > "2.2.1")
# ggplot() + geom_sf(data = sssi) +
# geom_point(aes(X, Y, fill = NULL, group = NULL), size = 1, data=ecs_df,
# colour = "black",
# fill = "white",
# size = .3,
# stroke = .1,
# show.legend = FALSE) +
# labs(x = NULL,
# title = "Figure 11",
# subtitle="Sites of Special Scientific Interest with points marked",
# caption = paste("Jeremy H. Kidwell :: jeremykidwell.info",
# "Data: UK Data Service (OGL) & Jeremy H. Kidwell",
# "You may redistribute this graphic under the terms of the CC-by-SA 4.0 license.",
# sep = "\n"))
# Plot Forest Inventory
ggplot() +
geom_polygon(aes(x = long, y = lat, group = group),
data = forest_inventory_sp,
colour = 'black',
alpha = .7,
size = .005) +
geom_point(aes(X, Y, fill = NULL, group = NULL), size = 1, data=ecs_df,
colour = "black",
fill = "white",
size = .15,
stroke = .002,
alpha = .6,
show.legend = TRUE) +
labs(x = NULL, y = NULL, fill = "Groups",
title = "Figure 11",
subtitle="Sites of Special Scientific Interest with points marked",
caption = paste("Jeremy H. Kidwell :: jeremykidwell.info",
"Data: UK Data Service (OGL) & Jeremy H. Kidwell",
"You may redistribute this graphic under the terms of the CC-by-SA 4.0 license.",
sep = "\n"))
# # ggplot using sf seems to be severely broken for now. Commenting out and reverting to sp
# ggplot() +
# geom_sf(data = forest_inventory)