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fixed error in ecs sssi table, added calc for pubs and grocery stores to other wilderness categories

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Jeremy Kidwell 2019-03-28 09:36:31 +00:00
parent 5fdf5cad8b
commit ec980c423d
2 changed files with 27 additions and 3 deletions
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mapping_draft-hpc_optimised_wilderness.Rmd
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@ -493,6 +493,7 @@ scenicareas_buf500 <- st_buffer(scenicareas_simplified, dist = 500)
# plot(lnd[ sel, ], col = "turquoise", add = TRUE) # add selected zones to map # plot(lnd[ sel, ], col = "turquoise", add = TRUE) # add selected zones to map
# from https://gotellilab.github.io/Bio381/StudentPresentations/SpatialDataTutorial.html # from https://gotellilab.github.io/Bio381/StudentPresentations/SpatialDataTutorial.html
# TODO: integrate pre-calc here into calculations further down which are still recalculating these figures
ecs_sf_sssi <- st_within(ecs_sf, sssi_simplified) ecs_sf_sssi <- st_within(ecs_sf, sssi_simplified)
ecs_sf_sssi50m <- st_within(ecs_sf, sssi_buf50) ecs_sf_sssi50m <- st_within(ecs_sf, sssi_buf50)
ecs_sf_sssi500m <- st_within(ecs_sf, sssi_buf500) ecs_sf_sssi500m <- st_within(ecs_sf, sssi_buf500)
@ -514,6 +515,8 @@ ecs_sf_scenicareas500m <- st_within(ecs_sf, scenicareas_buf500)
ecs_sf_scenicareasbeyond500m <- !(st_within(ecs_sf, scenicareas_buf500)) ecs_sf_scenicareasbeyond500m <- !(st_within(ecs_sf, scenicareas_buf500))
# 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 # 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
# TODO: implement parallel computing to distribute execution of loopable calculations below
# See: https://nceas.github.io/oss-lessons/parallel-computing-in-r/parallel-computing-in-r.html
# Generate dataframe based on SSSI buffers # Generate dataframe based on SSSI buffers
@ -581,23 +584,30 @@ permaculture_wildland_row <- c(sum(apply(st_within(permaculture_sf, wildland_sim
wildland_counts <- rbind(wildland_counts, permaculture_wildland_row) wildland_counts <- rbind(wildland_counts, permaculture_wildland_row)
grocery_wildland_row <- c(sum(apply(st_within(poi_grocery_sf, wildland_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(poi_grocery_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(poi_grocery_sf, wildland_buf500, sparse=FALSE), 1, any))) grocery_wildland_row <- c(sum(apply(st_within(poi_grocery_sf, wildland_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(poi_grocery_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(poi_grocery_sf, wildland_buf500, sparse=FALSE), 1, any)))
wildland_counts <- rbind(wildland_counts, grocery_wildland_row)
pubs_wildland_row <- c(sum(apply(st_within(poi_pubs_sf, wildland_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(poi_pubs_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(poi_pubs_sf, wildland_buf500, sparse=FALSE), 1, any))) pubs_wildland_row <- c(sum(apply(st_within(poi_pubs_sf, wildland_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(poi_pubs_sf, wildland_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(poi_pubs_sf, wildland_buf500, sparse=FALSE), 1, any)))
wildland_counts <- rbind(wildland_counts, pubs_wildland_row)
colnames(wildland_counts) <- c("Within Wildland Areas", "...50m", "...500m") colnames(wildland_counts) <- c("Within Wildland Areas", "...50m", "...500m")
# Generate dataframe from rows based on percentages of totals # Generate dataframe from rows based on percentages of totals
ecs_wildland_row_pct <- ecs_wildland_row/length(ecs_sf) ecs_wildland_row_pct <- ecs_wildland_row/length(ecs)
pow_wildland_row_pct <- pow_wildland_row/length(pow_pointX) pow_wildland_row_pct <- pow_wildland_row/length(pow_pointX)
dtas_wildland_row_pct <- dtas_wildland_row/length(dtas) dtas_wildland_row_pct <- dtas_wildland_row/length(dtas)
transition_wildland_row_pct <- transition_wildland_row/length(transition) transition_wildland_row_pct <- transition_wildland_row/length(transition)
permaculture_wildland_row_pct <- permaculture_wildland_row/length(permaculture) permaculture_wildland_row_pct <- permaculture_wildland_row/length(permaculture)
grocery_wildland_row_pct <- grocery_wildland_row/length(poi_grocery)
pubs_wildland_row_pct <- pubs_wildland_row/length(poi_pubs)
wildland_counts_pct <- rbind(ecs_wildland_row_pct, pow_wildland_row_pct) wildland_counts_pct <- rbind(ecs_wildland_row_pct, pow_wildland_row_pct)
wildland_counts_pct <- rbind(wildland_counts_pct, dtas_wildland_row_pct) wildland_counts_pct <- rbind(wildland_counts_pct, dtas_wildland_row_pct)
wildland_counts_pct <- rbind(wildland_counts_pct, transition_wildland_row_pct) wildland_counts_pct <- rbind(wildland_counts_pct, transition_wildland_row_pct)
wildland_counts_pct <- rbind(wildland_counts_pct, permaculture_wildland_row_pct) wildland_counts_pct <- rbind(wildland_counts_pct, permaculture_wildland_row_pct)
wildland_counts_pct <- rbind(wildland_counts_pct, grocery_wildland_row_pct)
wildland_counts_pct <- rbind(wildland_counts_pct, pubs_wildland_row_pct)
colnames(wildland_counts_pct) <- c("% Within wildlands", "% within 50m", "% within 500m") colnames(wildland_counts_pct) <- c("% Within wildlands", "% within 50m", "% within 500m")
# Merge into larger dataframe # Merge into larger dataframe
@ -620,22 +630,30 @@ permaculture_forestinv_row <- c(sum(apply(st_within(permaculture_sf, forestinv_s
forestinv_counts <- rbind(forestinv_counts, permaculture_forestinv_row) forestinv_counts <- rbind(forestinv_counts, permaculture_forestinv_row)
grocery_forestinv_row <- c(sum(apply(st_within(poi_grocery_sf, forestinv_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(poi_grocery_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(poi_grocery_sf, forestinv_buf500, sparse=FALSE), 1, any))) grocery_forestinv_row <- c(sum(apply(st_within(poi_grocery_sf, forestinv_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(poi_grocery_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(poi_grocery_sf, forestinv_buf500, sparse=FALSE), 1, any)))
forestinv_counts <- rbind(forestinv_counts, grocery_forestinv_row)
pubs_forestinv_row <- c(sum(apply(st_within(poi_pubs_sf, forestinv_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(poi_pubs_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(poi_pubs_sf, forestinv_buf500, sparse=FALSE), 1, any))) pubs_forestinv_row <- c(sum(apply(st_within(poi_pubs_sf, forestinv_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(poi_pubs_sf, forestinv_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(poi_pubs_sf, forestinv_buf500, sparse=FALSE), 1, any)))
forestinv_counts <- rbind(forestinv_counts, pubs_forestinv_row)
colnames(forestinv_counts) <- c("Within Woodlands", "...50m", "...500m") colnames(forestinv_counts) <- c("Within Woodlands", "...50m", "...500m")
# Generate dataframe from rows based on percentages of totals # Generate dataframe from rows based on percentages of totals
ecs_forestinv_row_pct <- ecs_forestinv_row/length(ecs_sf) # TODO: fix error generated by ecs_forestinv_row_pct using ecs_sf. Migrate all these to sf, but check for errors.
ecs_forestinv_row_pct <- ecs_forestinv_row/length(ecs)
pow_forestinv_row_pct <- pow_forestinv_row/length(pow_pointX) pow_forestinv_row_pct <- pow_forestinv_row/length(pow_pointX)
dtas_forestinv_row_pct <- dtas_forestinv_row/length(dtas) dtas_forestinv_row_pct <- dtas_forestinv_row/length(dtas)
transition_forestinv_row_pct <- transition_forestinv_row/length(transition) transition_forestinv_row_pct <- transition_forestinv_row/length(transition)
permaculture_forestinv_row_pct <- permaculture_forestinv_row/length(permaculture) permaculture_forestinv_row_pct <- permaculture_forestinv_row/length(permaculture)
grocery_forestinv_row_pct <- grocery_forestinv_row/length(poi_grocery)
pubs_forestinv_row_pct <- pubs_forestinv_row/length(poi_pubs)
forestinv_counts_pct <- rbind(ecs_forestinv_row_pct, pow_forestinv_row_pct) forestinv_counts_pct <- rbind(ecs_forestinv_row_pct, pow_forestinv_row_pct)
forestinv_counts_pct <- rbind(forestinv_counts_pct, dtas_forestinv_row_pct) forestinv_counts_pct <- rbind(forestinv_counts_pct, dtas_forestinv_row_pct)
forestinv_counts_pct <- rbind(forestinv_counts_pct, transition_forestinv_row_pct) forestinv_counts_pct <- rbind(forestinv_counts_pct, transition_forestinv_row_pct)
forestinv_counts_pct <- rbind(forestinv_counts_pct, permaculture_forestinv_row_pct) forestinv_counts_pct <- rbind(forestinv_counts_pct, permaculture_forestinv_row_pct)
forestinv_counts_pct <- rbind(forestinv_counts_pct, grocery_forestinv_row_pct)
forestinv_counts_pct <- rbind(forestinv_counts_pct, pubs_forestinv_row_pct)
colnames(forestinv_counts_pct) <- c("% Within Woodlands", "% within 50m", "% within 500m") colnames(forestinv_counts_pct) <- c("% Within Woodlands", "% within 50m", "% within 500m")
# Merge into larger dataframe # Merge into larger dataframe
@ -658,23 +676,29 @@ permaculture_scenicareas_row <- c(sum(apply(st_within(permaculture_sf, scenicare
scenicareas_counts <- rbind(scenicareas_counts, permaculture_scenicareas_row) scenicareas_counts <- rbind(scenicareas_counts, permaculture_scenicareas_row)
grocery_scenicareas_row <- c(sum(apply(st_within(poi_grocery_sf, scenicareas_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(poi_grocery_sf, scenicareas_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(poi_grocery_sf, scenicareas_buf500, sparse=FALSE), 1, any))) grocery_scenicareas_row <- c(sum(apply(st_within(poi_grocery_sf, scenicareas_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(poi_grocery_sf, scenicareas_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(poi_grocery_sf, scenicareas_buf500, sparse=FALSE), 1, any)))
scenicareas_counts <- rbind(scenicareas_counts, grocery_scenicareas_row)
pubs_scenicareas_row <- c(sum(apply(st_within(poi_pubs_sf, scenicareas_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(poi_pubs_sf, scenicareas_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(poi_pubs_sf, scenicareas_buf500, sparse=FALSE), 1, any))) pubs_scenicareas_row <- c(sum(apply(st_within(poi_pubs_sf, scenicareas_simplified, sparse=FALSE), 1, any)), sum(apply(st_within(poi_pubs_sf, scenicareas_buf50, sparse=FALSE), 1, any)), sum(apply(st_within(poi_pubs_sf, scenicareas_buf500, sparse=FALSE), 1, any)))
scenicareas_counts <- rbind(scenicareas_counts, pubs_scenicareas_row)
colnames(scenicareas_counts) <- c("Within Scenic Areas", "...50m", "...500m") colnames(scenicareas_counts) <- c("Within Scenic Areas", "...50m", "...500m")
# Generate dataframe from rows based on percentages of totals # Generate dataframe from rows based on percentages of totals
ecs_scenicareas_row_pct <- ecs_scenicareas_row/length(ecs_sf) ecs_scenicareas_row_pct <- ecs_scenicareas_row/length(ecs)
pow_scenicareas_row_pct <- pow_scenicareas_row/length(pow_pointX) pow_scenicareas_row_pct <- pow_scenicareas_row/length(pow_pointX)
dtas_scenicareas_row_pct <- dtas_scenicareas_row/length(dtas) dtas_scenicareas_row_pct <- dtas_scenicareas_row/length(dtas)
transition_scenicareas_row_pct <- transition_scenicareas_row/length(transition) transition_scenicareas_row_pct <- transition_scenicareas_row/length(transition)
permaculture_scenicareas_row_pct <- permaculture_scenicareas_row/length(permaculture) permaculture_scenicareas_row_pct <- permaculture_scenicareas_row/length(permaculture)
grocery_scenicareas_row_pct <- grocery_scenicareas_row/length(poi_grocery)
pubs_scenicareas_row_pct <- pubs_scenicareas_row/length(poi_pubs)
scenicareas_counts_pct <- rbind(ecs_scenicareas_row_pct, pow_scenicareas_row_pct) scenicareas_counts_pct <- rbind(ecs_scenicareas_row_pct, pow_scenicareas_row_pct)
scenicareas_counts_pct <- rbind(scenicareas_counts_pct, dtas_scenicareas_row_pct) scenicareas_counts_pct <- rbind(scenicareas_counts_pct, dtas_scenicareas_row_pct)
scenicareas_counts_pct <- rbind(scenicareas_counts_pct, transition_scenicareas_row_pct) scenicareas_counts_pct <- rbind(scenicareas_counts_pct, transition_scenicareas_row_pct)
scenicareas_counts_pct <- rbind(scenicareas_counts_pct, permaculture_scenicareas_row_pct) scenicareas_counts_pct <- rbind(scenicareas_counts_pct, permaculture_scenicareas_row_pct)
scenicareas_counts_pct <- rbind(scenicareas_counts_pct, grocery_scenicareas_row_pct)
scenicareas_counts_pct <- rbind(scenicareas_counts_pct, pubs_scenicareas_row_pct)
colnames(scenicareas_counts_pct) <- c("% Within scenicareass", "% within 50m", "% within 500m") colnames(scenicareas_counts_pct) <- c("% Within scenicareass", "% within 50m", "% within 500m")
# Merge into larger dataframe # Merge into larger dataframe

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wilderness_layers.qgz
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