Section 7 Getting distance to water

Here we cover adding data related to landscape features: 1. Distance to the nearest water source 2. Temperature measured by LANDSAT

7.1 Load libraries

# load libraries
library(dplyr)
library(purrr)
library(lubridate)
library(readr)
library(glue)
library(stringr)

# spatial
library(sf)

# plotting
library(ggplot2)
library(ggthemes)
library(viridis)

7.2 Load water features

We load water features from an OpenStreetMap (OpenStreetMap contributors 2017) dump accessed in mid 2018.

# load rivers, or linear water features
rivers = st_read("data/river_crop/kruger_rivers_cropped.shp")

# load waterholes or point features
wh = st_read("data/waterholes/")

# read the extent of elephant data
ext = st_read("data/ele_ext")

# filter waterholes by the extent
wh = filter(wh, CURRENT=="Open") %>%
  st_crop(ext) %>%
  st_union()

7.3 Load elephant data

# load elephant data and make it sf on UTM coords
data = read_csv("data/elephant_data.csv")
data_sf = st_as_sf(data, coords = c("xutm", "yutm")) %>%
  `st_crs<-`(32736)

# get distance to waterholes and rivers
distwh = as.numeric(st_distance(data_sf, wh))

river_season = list(distr_seasonal = rivers %>% filter(is.na(seasonal)),
                    distr = (rivers)) %>%
  map(st_union)

distr_seasonal = map(river_season, function(l){
  return(as.numeric(st_distance(data_sf, l)))
})

7.4 Add distance to water by season

# add distance to rivers data
data = mutate(data,
              distr = distr_seasonal[["distr"]],
              distr_s = distr_seasonal[["distr_seasonal"]],
              distwh = distwh)

# calculate mindw, the minimum distance to water
data = data %>%
  mutate(mindw = case_when(
    season =="dry"~ifelse(distr_s < distwh, distr_s, distwh),
    season == "wet"~ifelse(distr < distwh, distr, distwh),
    T~as.double(NA)
))

7.5 Write data to file

write_csv(data, "data/elephant_data.csv")

Farr, Tom G., Paul A. Rosen, Edward Caro, Robert Crippen, Riley Duren, Scott Hensley, Michael Kobrick, et al. 2007. “The Shuttle Radar Topography Mission.” Reviews of Geophysics 45 (2). https://doi.org/10.1029/2005RG000183.

Gorelick, Noel, Matt Hancher, Mike Dixon, Simon Ilyushchenko, David Thau, and Rebecca Moore. 2017. “Google Earth Engine: Planetary-Scale Geospatial Analysis for Everyone.” Remote Sensing of Environment 202: 18–27. https://doi.org/10.1016/j.rse.2017.06.031.

OpenStreetMap contributors. 2017. Planet Dump Retrieved from https://planet.osm.org.

Schmidt, Gail, Calli B. Jenkerson, Jeffrey Masek, Eric Vermote, and Feng Gao. 2013. “Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) Algorithm Description.” USGS Numbered Series 2013-1057. Open-File Report. Reston, VA: U.S. Geological Survey. http://pubs.er.usgs.gov/publication/ofr20131057.

References

OpenStreetMap contributors. 2017. Planet Dump Retrieved from https://planet.osm.org.