测试<-brick(file.name) 我的数据非常大,很难上传。
我使用此代码读取了NetCDF文件。 NetCDF文件包含文件中的时间较长。我知道这一点是因为我可以提取它们(见下文)。但是,当我以砖块形式读取netCDF文件时,砖块的范围不能反映netCDF文件中的经时长度。它似乎只是将栅格居中于美国大陆的中心(请参见下面的第一幅图):
library(ncdf4)
library(raster)
test <- brick(file.name)
test
class : RasterBrick
dimensions : 141, 240, 33840, 7273 (nrow, ncol, ncell, nlayers)
resolution : 25000, 25000 (x, y)
extent : -3e+06, 3e+06, -1762500, 1762500 (xmin, xmax, ymin, ymax)
crs : NA
source : C:/Users/anfangen/Box/Environmental-Data/Model-Pollen-Data/Raw-Data/RAGcount_1997-2016.nc
names : X1997.01.02.00.00.00, X1997.01.03.00.00.00, X1997.01.04.00.00.00, X1997.01.05.00.00.00, X1997.01.06.00.00.00, X1997.01.07.00.00.00, X1997.01.08.00.00.00, X1997.01.09.00.00.00, X1997.01.10.00.00.00, X1997.01.11.00.00.00, X1997.01.12.00.00.00, X1997.01.13.00.00.00, X1997.01.14.00.00.00, X1997.01.15.00.00.00, X1997.01.16.00.00.00, ...
Date/time : 1997-01-02 00:00:00, 2016-12-29 00:00:00 (min, max)
varname : count
如果我使用来拉出经纬度,我可以看到它们存在:
test_nc_open <- nc_open(file_name.nc')
## Get the lat longs for the ragweed file. These are in matrix form. It is as yet unclear to me why we need them in this form.
lat <- ncvar_get(test_nc_open, varid = 'xlat')
lon <- ncvar_get(test_nc_open, varid = 'xlon')
lat
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
[1,] 18.86005 19.05895 19.25808 19.45742 19.65697 19.85674 20.05672 20.25690 20.45730 20.65790 20.85870 21.05970
[2,] 18.92987 19.12906 19.32847 19.52810 19.72794 19.92799 20.12826 20.32874 20.52942 20.73031 20.93141 21.13270
[3,] 18.99921 19.19868 19.39837 19.59828 19.79841 19.99875 20.19931 20.40007 20.60105 20.80223 21.00361 21.20520
[4,] 19.06806 19.26781 19.46778 19.66797 19.86839 20.06901 20.26985 20.47091 20.67217 20.87363 21.07531 21.27719
[5,] 19.13641 19.33644 19.53669 19.73717 19.93786 20.13877 20.33989 20.54123 20.74278 20.94453 21.14649 21.34866
[6,] 19.20427 19.40458 19.60511 19.80586 20.00683 20.20802 20.40943 20.61105 20.81288 21.01492 21.21716 21.41962
[7,] 19.27163 19.47221 19.67302 19.87405 20.07530 20.27677 20.47846 20.68036 20.88247 21.08479 21.28732 21.49006
我尝试手动设置范围,但是在绘制结果时,它与其他空间层不匹配:
## Get state boundaries
states <- shapefile("GIS Data/State_boundaries/cb_2018_us_state_20m.shp")
test <- brick(file.name)
[1] "vobjtovarid4: error #F: I could not find the requsted var (or dimvar) in the file!"
[1] "var (or dimvar) name: crs"
[1] "file name: file.name.nc"
test <-
setExtent(test, c(min(apply(lon, 2, min)),
max(apply(lon, 2, max)),
min(apply(lat, 2, min)),
max(apply(lat, 2, max)) ), keepres =
FALSE, snap = FALSE)
crs(test) <- crs(states)
plot(test[[1]])
plot(states, add=TRUE)
我不明白我在做什么错。我已经看过其他几个类似的问题,无法使用这些信息来解决这个问题。
print(test)
3 variables (excluding dimension variables):
float xlat[jx,iy]
long_name: Latitude on Cross Points
standard_name: latitude
units: degrees_north
grid_mapping: crs
float xlon[jx,iy]
long_name: Longitude on Cross Points
standard_name: longitude
units: degrees_east
grid_mapping: crs
float count[jx,iy,time]
cell_methods: time: point
grid_mapping: crs
coordinates: xlat xlon
units: particles m-3
standard_name: near-surface_particle_count
long_name: Near-surface particle count
3 dimensions:
time Size:7273 *** is unlimited ***
long_name: time
standard_name: time
units: hours since 1949-12-01 00:00:00 UTC
calendar: gregorian
bounds: time_bnds
iy Size:141
long_name: y-coordinate in Cartesian system
standard_name: projection_y_coordinate
units: m
axis: Y
_CoordinateAxisType: GeoY
jx Size:240
long_name: x-coordinate in Cartesian system
standard_name: projection_x_coordinate
units: m
axis: X
_CoordinateAxisType: GeoX
答案 0 :(得分:0)
不清楚您为什么要做自己的事情。在这种情况下,您要寻找的解决方案取决于您的目标。
该文件的坐标参考系(lons)不是lon / lat。似乎它没有指定它是什么,或者,如果是,raster
则不理解它。无论提供文件的人是谁,您都可以从crs中获取信息。要查看文件中是否有信息,您可以执行print(test)
该文件还存储单元格的经度和纬度。但是这些不在常规网格上,因此您不能使用它们。如果您确实需要栅格数据为lon / lat,则可以使用
x <- projectRaster(test, "+proj=longlat +datum=WGS84")
但是这会导致精度损失,因此最好避免使用。要从栅格数据中按点或面提取值,应首先将其转换为栅格数据的crs。您可以使用sp::spTransform
。之后,您可以使用raster::extract
因此,使用SpatialPoints p
,您可以执行类似的操作(但是使用正确的crs,在这种情况下,utm 43肯定是错误的)
putm <- spTransform(p, CRS("+proj=utm +zone=43 +datum=WGS84"))
e <- extract(test, putm)