In talbertc-usgs/NABatR: R Tools for Accessing and Manipulating North American Bat Monitoring Data

Import packages for building and cacheing out dataframes for CONUS, Alaska, Hawaii, Puerto Rico, Canada, and Mexico

library(leaflet)
library(leaflet.extras)
library(rgdal)
library(sp)
library(raster)
library(tidyr)
library(plotly)
out_put_dir = '/path/to/dir/to/save/csvs/'

CONUS

CONUS     = readOGR('/path/to/downloaded/conus_mastersample_10km_attributed/')
p = CONUS[CONUS$GRTS_ID %in% c(55478,2,5,90,15),]
p =  spTransform(CONUS, CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"))
p

leaflet() %>% addTiles() %>% addPolygons(data = subset(p, GRTS_ID < 2000))

grts_ids = p$GRTS_ID
grts_centerpoints = paste(p$lat,p$long,sep=',')
grts_lat_lons =  p %>% fortify() %>% select(long,lat,order,id) 
grts_lat_lons$latlon = paste(grts_lat_lons$lat,grts_lat_lons$long,sep=',') 
grts_lat_lons = select(grts_lat_lons,latlon,order,id)
number_of_points = dim(grts_lat_lons)[1] / dim(p)[1]

grts_ids_df_version = rep(grts_ids, each = number_of_points)

inter_df = data.frame(GRTS_ID = grts_ids_df_version, latlon = grts_lat_lons$latlon, 
  id = grts_lat_lons$id, order= grts_lat_lons$order, stringsAsFactors = FALSE)
inter_df_1 = inter_df %>% group_by(GRTS_ID) %>% spread(order, latlon)
inter_df_1

final_df =  inter_df_1 %>% select(GRTS_ID, '2','4','6','8')
names(final_df)[2] = 'lowerleft'
names(final_df)[3] = 'upperleft'
names(final_df)[4] = 'upperright'
names(final_df)[5] = 'lowerright'
final_df$center = grts_centerpoints
final_df
write.csv(final_df, file = paste0(out_put_dir, 'GRTS_coords_CONUS.csv'))

Hawaii

Hawaii = readOGR('/path/to/downloaded//HI_mastersample_5km_attributed/')
p = Hawaii
p =  spTransform(Hawaii, CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"))
p

leaflet() %>% addTiles() %>% addPolygons(data = subset(p, GRTS_ID < 2000))

grts_ids = p$GRTS_ID
grts_centerpoints = paste(p$lat,p$long,sep=',')
grts_lat_lons =  p %>% fortify() %>% select(long,lat,order,id) 
grts_lat_lons$latlon = paste(grts_lat_lons$lat,grts_lat_lons$long,sep=',') 
grts_lat_lons = select(grts_lat_lons,latlon,order,id)
number_of_points = dim(grts_lat_lons)[1] / dim(p)[1]

grts_ids_df_version = rep(grts_ids, each = number_of_points)

inter_df = data.frame(GRTS_ID = grts_ids_df_version, latlon = grts_lat_lons$latlon, 
  id = grts_lat_lons$id, order= grts_lat_lons$order, stringsAsFactors = FALSE)
inter_df_1 = inter_df %>% group_by(GRTS_ID) %>% spread(order, latlon)
inter_df_1

final_df =  inter_df_1 %>% select(GRTS_ID, '1','2','3','4')
names(final_df)[2] = 'lowerleft'
names(final_df)[3] = 'upperleft'
names(final_df)[4] = 'upperright'
names(final_df)[5] = 'lowerright'
final_df$center = grts_centerpoints
final_df
write.csv(final_df, file = paste0(out_put_dir, 'GRTS_coords_Hawaii.csv'))

ALASKA

Alaska     = readOGR('/path/to/downloaded//AK_mastersample_10km_attributed/')
p = Alaska
p =  spTransform(Alaska, CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"))
p

leaflet() %>% addTiles() %>% addPolygons(data = subset(p, GRTS_ID < 2000))

grts_ids = p$GRTS_ID
grts_centerpoints = paste(p$lat,p$long,sep=',')
grts_lat_lons =  p %>% fortify() %>% select(long,lat,order,id) 
grts_lat_lons$latlon = paste(grts_lat_lons$lat,grts_lat_lons$long,sep=',') 
grts_lat_lons = select(grts_lat_lons,latlon,order,id)
number_of_points = dim(grts_lat_lons)[1] / dim(p)[1]

grts_ids_df_version = rep(grts_ids, each = number_of_points)

inter_df = data.frame(GRTS_ID = grts_ids_df_version, latlon = grts_lat_lons$latlon, 
  id = grts_lat_lons$id, order= grts_lat_lons$order, stringsAsFactors = FALSE)
inter_df_1 = inter_df %>% group_by(GRTS_ID) %>% spread(order, latlon)
inter_df_1

final_df =  inter_df_1 %>% select(GRTS_ID, '2','4','6','8')
names(final_df)[2] = 'lowerleft'
names(final_df)[3] = 'upperleft'
names(final_df)[4] = 'upperright'
names(final_df)[5] = 'lowerright'
final_df$center = grts_centerpoints
final_df
write.csv(final_df, file = paste0(out_put_dir, 'GRTS_coords_Alaska.csv'))

Puerto Rico

Puerto_Rico     = readOGR('/path/to/downloaded/PR_mastersample_5km_attributed/')
p = Puerto_Rico
p =  spTransform(Puerto_Rico, CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"))
p
leaflet() %>% addTiles() %>% addPolygons(data = p)


grts_ids = p$GRTS_ID
grts_centerpoints = paste(p$lat,p$long,sep=',')
grts_lat_lons =  p %>% fortify() %>% select(long,lat,order,id) 
grts_lat_lons$latlon = paste(grts_lat_lons$lat,grts_lat_lons$long,sep=',') 
grts_lat_lons = select(grts_lat_lons,latlon,order,id)
number_of_points = dim(grts_lat_lons)[1] / dim(p)[1]

grts_ids_df_version = rep(grts_ids, each = number_of_points)

inter_df = data.frame(GRTS_ID = grts_ids_df_version, latlon = grts_lat_lons$latlon, 
  id = grts_lat_lons$id, order= grts_lat_lons$order, stringsAsFactors = FALSE)
inter_df_1 = inter_df %>% group_by(GRTS_ID) %>% spread(order, latlon)
inter_df_1

final_df =  inter_df_1 %>% select(GRTS_ID, '1','2','3','4')
names(final_df)[2] = 'lowerleft'
names(final_df)[3] = 'upperleft'
names(final_df)[4] = 'upperright'
names(final_df)[5] = 'lowerright'
final_df$center = grts_centerpoints
final_df
write.csv(final_df, file = paste0(out_put_dir, 'GRTS_coords_Puerto_Rico.csv'))

Mexico

Mexico     = readOGR('/path/to/downloaded/Mex_mastersample_10km_attributed//')
p = Mexico
p =  spTransform(Mexico, CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"))
p

leaflet() %>% addTiles() %>% addPolygons(data = subset(p, GRTS_ID < 2000))

grts_ids = p$GRTS_ID
grts_centerpoints = paste(p$lat,p$long,sep=',')
grts_lat_lons =  p %>% fortify() %>% select(long,lat,order,id) 
grts_lat_lons$latlon = paste(grts_lat_lons$lat,grts_lat_lons$long,sep=',') 
grts_lat_lons = select(grts_lat_lons,latlon,order,id)
number_of_points = dim(grts_lat_lons)[1] / dim(p)[1]

grts_ids_df_version = rep(grts_ids, each = number_of_points)

inter_df = data.frame(GRTS_ID = grts_ids_df_version, latlon = grts_lat_lons$latlon, 
  id = grts_lat_lons$id, order= grts_lat_lons$order, stringsAsFactors = FALSE)
inter_df_1 = inter_df %>% group_by(GRTS_ID) %>% spread(order, latlon)
inter_df_1

final_df =  inter_df_1 %>% select(GRTS_ID, '2','4','6','8')
names(final_df)[2] = 'lowerleft'
names(final_df)[3] = 'upperleft'
names(final_df)[4] = 'upperright'
names(final_df)[5] = 'lowerright'
final_df$center = grts_centerpoints
final_df
write.csv(final_df, file = paste0(out_put_dir, 'GRTS_coords_Mexico.csv'))

Canada

Canada     = readOGR('/path/to/downloaded/Can_mastersample_10km_attributed/')
p = Canada
p =  spTransform(Canada, CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"))
p

leaflet() %>% addTiles() %>% addPolygons(data = subset(p, GRTS_ID < 2000))

grts_ids = p$GRTS_ID
grts_centerpoints = paste(p$lat,p$long,sep=',')
grts_lat_lons =  p %>% fortify() %>% select(long,lat,order,id) 
grts_lat_lons$latlon = paste(grts_lat_lons$lat,grts_lat_lons$long,sep=',') 
grts_lat_lons = select(grts_lat_lons,latlon,order,id)
number_of_points = dim(grts_lat_lons)[1] / dim(p)[1]

grts_ids_df_version = rep(grts_ids, each = number_of_points)

inter_df = data.frame(GRTS_ID = grts_ids_df_version, latlon = grts_lat_lons$latlon, 
  id = grts_lat_lons$id, order= grts_lat_lons$order, stringsAsFactors = FALSE)
inter_df_1 = inter_df %>% group_by(GRTS_ID) %>% spread(order, latlon)
inter_df_1

final_df =  inter_df_1 %>% select(GRTS_ID, '2','4','6','8')
names(final_df)[2] = 'lowerleft'
names(final_df)[3] = 'upperleft'
names(final_df)[4] = 'upperright'
names(final_df)[5] = 'lowerright'
final_df$center = grts_centerpoints
final_df
write.csv(final_df, file = paste0(out_put_dir, 'GRTS_coords_Canada.csv'))

talbertc-usgs/NABatR documentation built on April 22, 2020, 8:23 p.m.