为什么我无法使用 R 获得 state 的 worldclim 数据（平均温度和精确度）？

Question

I'd like to get the average temperature and precipitation for the state of Ceara in Brazil; I made a cropped area on the map as:

and I used the center lat/lon as lat=-5.49839 and lon=-39.32062 I got the caps of latitude and longitude as latinicial=-7.24614 (minimum latitude), latfinal=-3.76140 (maximum latitude), longinicial=-40.38084 (minimum longitude) and longfinal=-38.77385 (maximum longitude) then I've simulated a uniformly distributed temperature for both latitude and longitude which lies in their maxima and minima.

My code is given as follows:

library(raster)
library(sp)
library(rgeos)
library(rgdal)
library(dismo)
library(rgdal)
library(sf)
d=getData('worldclim',lat=-5.49839,lon=-39.32062,res=0.5,var='bio')
latinicial=-7.24614
latfinal=-3.76140
longinicial=-40.38084
longfinal=-38.77385
latitude=runif(100,latinicial,latfinal)
longitude=runif(100,longinicial,longfinal)
coord=data.frame(latitude,longitude)
points = SpatialPoints(coord, proj4string = d@crs)
d <- d[[c(1,12)]]
names(d)=c("Temp","Prec")
extract(d,coord)

But when I run it, I got NA values for all rows even though I'm showing you only 4 rows:

So, I'd like to know what happened to it. Why do I get NA values?

Answer 1

The problem is with the order of longitude and latitude in coords . When you put coords into SpatialPoints , it expects the order to be longitude then latitude , but you have it reversed. Once you fix that, then it will extract the data correctly. All the code above coord works fine. Also, if you are going to run this code multiple times, then I would recommend using set.seed . This will allow you to get the same values every time when you run the runif statements.

library(raster)
library(sp)

set.seed(243)
d = getData(
  'worldclim',
  lat = -5.49839,
  lon = -39.32062,
  res = 0.5,
  var = 'bio'
)
latinicial = -7.24614
latfinal = -3.76140
longinicial = -40.38084
longfinal = -38.77385
latitude = runif(100, latinicial, latfinal)
longitude = runif(100, longinicial, longfinal)
coord = data.frame(longitude, latitude)
points = SpatialPoints(coord, proj4string = d@crs)
d <- d[[c(1, 12)]]
names(d) = c("Temp", "Prec")
extract(d, coord)

Output

head()

       Temp Prec
  [1,]  239  655
  [2,]  267  832
  [3,]  256  541
  [4,]  269  740
  [5,]  242  784
  [6,]  233  981