library(mapview)
library(rgee)
library(googledrive)
library(sf)
#Import SA boundary
boundary <- read_sf(dsn = "C:/Users/Emily/Documents/Fall_2020/Geospatial_R/SouthAfricaDrought/data-raw", layer = "SouthAfrica_Boundary")
#Retrieve bounding box coordinates
boundary
ee_Initialize(email = 'evendene@gwmail.gwu.edu', drive = TRUE)
#Create polygon using bounding box coordinates
polygon <- ee$Geometry$Polygon(list(c(16.45189, -34.83417), c(32.94498, -34.83417), c(32.94498, -22.12503), c(16.45189, -22.12503), c(16.45189, -22.12503)))
#Turn this polygon into a feature collection
fc <- ee$FeatureCollection(polygon)
#Filter imagery
collection <- ee$ImageCollection("MODIS/006/MOD11A1")$
filterDate("2019-11-01", "2020-03-31")$
filterBounds(polygon)$
select('precipitation')
#See how many images are included in this collection
count <- collection$size()$getInfo()
count
#Export collection
downConfig = list(scale = 500, maxPixels = 1.0E13, driveFolder = 'SouthAfrica_Imagery')
img_lst = collection$toList(count)
usda_stars_time <- list()
for (index in seq_len(count)) {
image = ee$Image(img_lst$get(index-1))
name = image$get('system:index')$getInfo()
print(name)
usda_stars <- ee_as_stars(
image = image,
region = polygon,
scale = downConfig$scale,
maxPixels = downConfig$maxPixels,
container = downConfig$driveFolder
)
names(usda_stars) <- name
usda_stars[usda_stars==0] = NA
usda_stars_time[[index]] <- usda_stars
}
usda_stars_mosaic <- do.call(st_mosaic, usda_stars_time)
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