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finalised hpc version, added calc for scenicareas
This commit is contained in:
Jeremy Kidwell
parent
c76f9df02e
commit
e814b05bf1
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@ -764,8 +764,6 @@ urbanrural_centralbelt_ecs_choropleth_plot <-
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vp_urbanrural_centralbelt_ecs_choropleth_plot <- viewport(x = 0.5, y = 0.1, height = 6.0/centralbelt_ratio)
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# Save to file
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# plot full map with inset
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tmap_mode("plot")
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@ -966,8 +964,10 @@ forestinv_simplified <- st_simplify(forestinv)
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# download.file("https://opendata.arcgis.com/datasets/d7f6b987c7224a72a185ce012258d500_23.zip", destfile = "data/ScenicAreas.zip")
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# unzip("data/ScenicAreas.zip", exdir = "data")
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# scenicareas <- st_read("data/ScenicAreas.shp")
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# scenicareas_sp <- readOGR("./data", "ScenicAreas")
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scenicareas <- st_read("data/SG_NationalScenicAreas_1998.shp") %>% st_transform(paste0("+init=epsg:",27700))
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# Generate simplified polygon for plots below
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scenicareas_simplified <- st_simplify(scenicareas)
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# Set symmetrical CRS for analysis below (inserted here in order to correct errors, may be deprecated later)
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# st_crs(sssi) <- 27700
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@ -1012,6 +1012,9 @@ forestinv_buf500 <- st_buffer(forestinv_simplified, dist = 500)
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# forestinv_buf500_lines = st_union(forestinv_simplified) %>% st_buffer(500) %>%
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# st_cast(to = "LINESTRING")
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scenicareas_buf50 <- st_buffer(scenicareas_simplified, dist = 50)
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scenicareas_buf500 <- st_buffer(scenicareas_simplified, dist = 500)
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# Calculate number of groups within polygons
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# calculate coincidence of ecs points within each polygons and buffers for each
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@ -1023,21 +1026,26 @@ forestinv_buf500 <- st_buffer(forestinv_simplified, dist = 500)
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# plot(lnd[ sel, ], col = "turquoise", add = TRUE) # add selected zones to map
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# from https://gotellilab.github.io/Bio381/StudentPresentations/SpatialDataTutorial.html
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ecs_sf_sssi <- st_within(ecs_sf, sssi)
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ecs_sf_sssi <- st_within(ecs_sf, sssi_simplified)
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ecs_sf_sssi50m <- st_within(ecs_sf, sssi_buf50)
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ecs_sf_sssi500m <- st_within(ecs_sf, sssi_buf500)
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ecs_sf_sssibeyond500m <- !(st_within(ecs_sf, sssi_buf500))
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ecs_sf_wildland <- st_within(ecs_sf, wildland)
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ecs_sf_wildland <- st_within(ecs_sf, wildland_simplified)
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ecs_sf_wildland50m <- st_within(ecs_sf, wildland_buf50)
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ecs_sf_wildland500m <- st_within(ecs_sf, wildland_buf500)
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ecs_sf_wildlandbeyond500m <- !(st_within(ecs_sf, wildland_buf500))
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ecs_sf_forestinv <- st_within(ecs_sf, forestinv)
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ecs_sf_forestinv <- st_within(ecs_sf, forestinv_simplified)
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ecs_sf_forestinv50m <- st_within(ecs_sf, forestinv_buf50)
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ecs_sf_forestinv500m <- st_within(ecs_sf, forestinv_buf500)
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ecs_sf_forestinvbeyond500m <- !(st_within(ecs_sf, forestinv_buf500))
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ecs_sf_scenicareas <- st_within(ecs_sf, scenicareas_simplified)
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ecs_sf_scenicareas50m <- st_within(ecs_sf, scenicareas_buf50)
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ecs_sf_scenicareas500m <- st_within(ecs_sf, scenicareas_buf500)
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ecs_sf_scenicareasbeyond500m <- !(st_within(ecs_sf, scenicareas_buf500))
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# TODO: implement more efficient code using do.call() function or sapply() as here https://stackoverflow.com/questions/3642535/creating-an-r-dataframe-row-by-row
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# Generate dataframe based on SSSI buffers
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@ -1045,13 +1053,13 @@ ecs_sf_forestinvbeyond500m <- !(st_within(ecs_sf, forestinv_buf500))
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# Calculate incidence of ecs within SSSI and within buffers at 50/500m
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ecs_sssi_row <- c(sum(apply(st_within(ecs_sf, sssi_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(ecs_sf, sssi_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(ecs_sf, sssi_buf500, sparse=FALSE), 1, any)))
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pow_sssi_row <- c(sum(apply(st_within(pow_pointX_sf, sssi, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, sssi_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, sssi_buf500, sparse=FALSE), 1, any)))
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pow_sssi_row <- c(sum(apply(st_within(pow_pointX_sf, sssi_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, sssi_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, sssi_buf500, sparse=FALSE), 1, any)))
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dtas_sssi_row <- c(sum(apply(st_within(dtas_sf, sssi, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, sssi_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, sssi_buf500, sparse=FALSE), 1, any)))
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dtas_sssi_row <- c(sum(apply(st_within(dtas_sf, sssi_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, sssi_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, sssi_buf500, sparse=FALSE), 1, any)))
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transition_sssi_row <- c(sum(apply(st_within(transition_sf, sssi, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, sssi_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, sssi_buf500, sparse=FALSE), 1, any)))
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transition_sssi_row <- c(sum(apply(st_within(transition_sf, sssi_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, sssi_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, sssi_buf500, sparse=FALSE), 1, any)))
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permaculture_sssi_row <- c(sum(apply(st_within(permaculture_sf, sssi, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, sssi_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, sssi_buf500, sparse=FALSE), 1, any)))
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permaculture_sssi_row <- c(sum(apply(st_within(permaculture_sf, sssi_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, sssi_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, sssi_buf500, sparse=FALSE), 1, any)))
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# Generate dataframe from rows based on counts
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sssi_counts <- rbind(ecs_sssi_row, pow_sssi_row)
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@ -1080,18 +1088,18 @@ sssi_counts_merged <- cbind(sssi_counts, sssi_counts_pct)
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# Generate dataframe based on wildland buffers
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ecs_wildland_row <- c(sum(apply(st_within(ecs_sf, wildland, sparse=FALSE), 1, any)), sum(apply(st_within(ecs_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(ecs_sf, wildland_buf500, sparse=FALSE), 1, any)))
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ecs_wildland_row <- c(sum(apply(st_within(ecs_sf, wildland_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(ecs_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(ecs_sf, wildland_buf500, sparse=FALSE), 1, any)))
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pow_wildland_row <- c(sum(apply(st_within(pow_pointX_sf, wildland, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, wildland_buf500, sparse=FALSE), 1, any)))
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pow_wildland_row <- c(sum(apply(st_within(pow_pointX_sf, wildland_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, wildland_buf500, sparse=FALSE), 1, any)))
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wildland_counts <- rbind(ecs_wildland_row, pow_wildland_row)
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dtas_wildland_row <- c(sum(apply(st_within(dtas_sf, wildland, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, wildland_buf500, sparse=FALSE), 1, any)))
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dtas_wildland_row <- c(sum(apply(st_within(dtas_sf, wildland_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, wildland_buf500, sparse=FALSE), 1, any)))
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wildland_counts <- rbind(wildland_counts, dtas_wildland_row)
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transition_wildland_row <- c(sum(apply(st_within(transition_sf, wildland, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, wildland_buf500, sparse=FALSE), 1, any)))
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transition_wildland_row <- c(sum(apply(st_within(transition_sf, wildland_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, wildland_buf500, sparse=FALSE), 1, any)))
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wildland_counts <- rbind(wildland_counts, transition_wildland_row)
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permaculture_wildland_row <- c(sum(apply(st_within(permaculture_sf, wildland, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, wildland_buf500, sparse=FALSE), 1, any)))
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permaculture_wildland_row <- c(sum(apply(st_within(permaculture_sf, wildland_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, wildland_buf500, sparse=FALSE), 1, any)))
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wildland_counts <- rbind(wildland_counts, permaculture_wildland_row)
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colnames(wildland_counts) <- c("Within Wildland Areas", "...50m", "...500m")
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@ -1115,18 +1123,18 @@ wildland_counts_merged <- cbind(wildland_counts, wildland_counts_pct)
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# Generate dataframe based on forestinv buffers
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ecs_forestinv_row <- c(sum(apply(st_within(ecs_sf, forestinv, sparse=FALSE), 1, any)), sum(apply(st_within(ecs_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(ecs_sf, forestinv_buf500, sparse=FALSE), 1, any)))
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ecs_forestinv_row <- c(sum(apply(st_within(ecs_sf, forestinv_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(ecs_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(ecs_sf, forestinv_buf500, sparse=FALSE), 1, any)))
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pow_forestinv_row <- c(sum(apply(st_within(pow_pointX_sf, forestinv, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, forestinv_buf500, sparse=FALSE), 1, any)))
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pow_forestinv_row <- c(sum(apply(st_within(pow_pointX_sf, forestinv_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, forestinv_buf500, sparse=FALSE), 1, any)))
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forestinv_counts <- rbind(ecs_forestinv_row, pow_forestinv_row)
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dtas_forestinv_row <- c(sum(apply(st_within(dtas_sf, forestinv, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, forestinv_buf500, sparse=FALSE), 1, any)))
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dtas_forestinv_row <- c(sum(apply(st_within(dtas_sf, forestinv_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, forestinv_buf500, sparse=FALSE), 1, any)))
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forestinv_counts <- rbind(forestinv_counts, dtas_forestinv_row)
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transition_forestinv_row <- c(sum(apply(st_within(transition_sf, forestinv, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, forestinv_buf500, sparse=FALSE), 1, any)))
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transition_forestinv_row <- c(sum(apply(st_within(transition_sf, forestinv_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, forestinv_buf500, sparse=FALSE), 1, any)))
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forestinv_counts <- rbind(forestinv_counts, transition_forestinv_row)
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permaculture_forestinv_row <- c(sum(apply(st_within(permaculture_sf, forestinv, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, forestinv_buf500, sparse=FALSE), 1, any)))
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permaculture_forestinv_row <- c(sum(apply(st_within(permaculture_sf, forestinv_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, forestinv_buf500, sparse=FALSE), 1, any)))
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forestinv_counts <- rbind(forestinv_counts, permaculture_forestinv_row)
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colnames(forestinv_counts) <- c("Within Woodlands", "...50m", "...500m")
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@ -1147,6 +1155,42 @@ colnames(forestinv_counts_pct) <- c("% Within Woodlands", "% within 50m", "% wit
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# Merge into larger dataframe
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forestinv_counts_merged <- cbind(forestinv_counts, forestinv_counts_pct)
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# Generate dataframe based on scenicareas buffers
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ecs_scenicareas_row <- c(sum(apply(st_within(ecs_sf, scenicareas_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(ecs_sf, scenicareas_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(ecs_sf, scenicareas_buf500, sparse=FALSE), 1, any)))
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pow_scenicareas_row <- c(sum(apply(st_within(pow_pointX_sf, scenicareas_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, scenicareas_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(pow_pointX_sf, scenicareas_buf500, sparse=FALSE), 1, any)))
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scenicareas_counts <- rbind(ecs_scenicareas_row, pow_scenicareas_row)
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dtas_scenicareas_row <- c(sum(apply(st_within(dtas_sf, scenicareas_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, scenicareas_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(dtas_sf, scenicareas_buf500, sparse=FALSE), 1, any)))
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scenicareas_counts <- rbind(scenicareas_counts, dtas_scenicareas_row)
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transition_scenicareas_row <- c(sum(apply(st_within(transition_sf, scenicareas_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, scenicareas_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(transition_sf, scenicareas_buf500, sparse=FALSE), 1, any)))
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scenicareas_counts <- rbind(scenicareas_counts, transition_scenicareas_row)
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permaculture_scenicareas_row <- c(sum(apply(st_within(permaculture_sf, scenicareas_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, scenicareas_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(permaculture_sf, scenicareas_buf500, sparse=FALSE), 1, any)))
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scenicareas_counts <- rbind(scenicareas_counts, permaculture_scenicareas_row)
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colnames(scenicareas_counts) <- c("Within Scenic Areas", "...50m", "...500m")
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# Generate dataframe from rows based on percentages of totals
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ecs_scenicareas_row_pct <- ecs_scenicareas_row/length(ecs_sf)
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pow_scenicareas_row_pct <- pow_scenicareas_row/length(pow_pointX)
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dtas_scenicareas_row_pct <- dtas_scenicareas_row/length(dtas)
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transition_scenicareas_row_pct <- transition_scenicareas_row/length(transition)
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permaculture_scenicareas_row_pct <- permaculture_scenicareas_row/length(permaculture)
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scenicareas_counts_pct <- rbind(ecs_scenicareas_row_pct, pow_scenicareas_row_pct)
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scenicareas_counts_pct <- rbind(scenicareas_counts_pct, dtas_scenicareas_row_pct)
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scenicareas_counts_pct <- rbind(scenicareas_counts_pct, transition_scenicareas_row_pct)
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scenicareas_counts_pct <- rbind(scenicareas_counts_pct, permaculture_scenicareas_row_pct)
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colnames(scenicareas_counts_pct) <- c("% Within scenicareass", "% within 50m", "% within 500m")
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# Merge into larger dataframe
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scenicareas_counts_merged <- cbind(scenicareas_counts, scenicareas_counts_pct)
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```
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# Proximity to "Wilderness"
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@ -1173,10 +1217,16 @@ forestinv_counts_merged %>%
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kable(format = "html", col.names = colnames(forestinv_counts_merged), caption = "Group counts within woodlands") %>%
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kable_styling(bootstrap_options = c("striped", "hover", "condensed", full_width = F, "responsive"))
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scenicareas_counts_merged %>%
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kable(format = "html", col.names = colnames(scenicareas_counts_merged), caption = "Group counts within woodlands") %>%
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kable_styling(bootstrap_options = c("striped", "hover", "condensed", full_width = F, "responsive"))
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# Output CSV files for tables above
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write.csv(sssi_counts_merged, "derivedData/sssi_counts_merged.csv", row.names=TRUE)
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write.csv(wildland_counts_merged, "derivedData/wildland_counts_merged.csv", row.names=TRUE)
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write.csv(forestinv_counts_merged, "derivedData/forestinv_counts_merged.csv", row.names=TRUE)
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write.csv(scenicareas_counts_merged, "derivedData/scenicareas_counts_merged.csv", row.names=TRUE)
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```
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@ -1219,6 +1269,7 @@ tm_shape(sssi_simplified, bbox = scotland) +
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tm_shape(sssi_simplified, bbox = scotland) + tm_fill(col = "blue", alpha = 0.4, lwd=0.01, title = "Wilderness Areas") +
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tm_shape(wildland_simplified, bbox = scotland) + tm_fill(col = "green", alpha = 0.4, lwd=0.01) +
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tm_shape(forestinv_simplified, bbox = scotland) + tm_fill(col = "orange", alpha = 0.4, lwd=0.01) +
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tm_shape(scenicareas_simplified, bbox = scotland) + tm_fill(col = "orange", alpha = 0.4, lwd=0.01) +
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tm_shape(admin_lev1) + tm_borders(lwd=0.01) +
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# tm_scale_bar(breaks = c(0, 100, 200), size = 1) +
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tm_shape(ecs_sf) + tm_dots("red", size = .02, alpha = .4) +
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