Rt提取气候因子

学习网址：https://blog.csdn.net/SUN5_The_answer/article/details/135131492
library(raster)
library(terra)
library(ncdf4)
occur <- read.csv("sample information1.csv", header=T, row.names = "Code")
objects(occur)
bio1 <- raster("wc2.1_10m_bio_1.tif")
crs.wgs <- "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"
crs(bio1) <- crs.wgs
occ <- SpatialPointsDataFrame(
  occur[,c('Lon','Lat')], 
  proj4string=CRS(crs.wgs), 
  data=occur
)
lo_bio1 <- raster::extract(bio1,occ)

for (i in 1:19) {
  var = raster(paste0("wc2.1_10m_bio_",i,".tif"))
  var_val = raster::extract(var, occ)
  occur = cbind(occur, var_val)
  colnames(occur)[i+2] <- paste0("bio",i)
}
write.csv(occur, 'bio_val.csv', quote = FALSE)
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