嗨光栅战士！
在操作数据集数月之后，我对结果感到头疼。我是R和空间分析的新手，但在我的学习过程中非常开心。
这是我的问题：一旦我将区域功能应用于一组5个光栅对象（.tif），不知怎的，我在区域中得到重复的值，我认为它会变为零。此外，某些值出现在其他单元格中。
这是我的代码：
folder <- "my_directory"
#for one country
ET<-raster("my_directory/file_ET.tif")
ED<-raster("my_directory/file_ED.tif")
SH<-raster("my_directory/file_SH.tif")
SC<-raster("my_directory/file_SC.tif")
WH<-raster("my_directory/file_WH.tif")
#zones
lowbound<- seq(0,cellStats(ED,"max", na.rm=TRUE),1000)
upbound<-lowbound+1000
band<-upbound/1000
rclmat <- as.matrix(cbind(lowbound,upbound,band)) #to be used on reclassify
rclmat<-rclmat[1:length(rclmat[,1])-1,]
edb<- reclassify(ED, rclmat)
# zonal statistics # I already tried this: na.rm=FALSE, !anyDuplicated(sum_ET)) to avoid duplication – did not work
sum_ET<-zonal(ET,edb,"sum") #, na.rm=FALSE, !anyDuplicated(sum_ET))
stats<-cbind(band,upbound,sum_ET[,2], sum_SH[,2], sum_SC[,2], sum_WH[,2],perc_SH,perc_SC,perc_WH,perc_Tot)
我的结果：
upbound ET
1 1000 10523272.53
2 2000 5156046.27
3 3000 5053895.54
4 4000 4796505.3
5 5000 4392162.97
6 6000 4156065.87
31 31000 10523272.53
32 32000 5156046.27
33 33000 5053895.54
34 34000 4796505.3
35 35000 4392162.97
36 36000 4156065.87
从31到36与1到6的相同。
我的一位同事的结果 - 我与之比较
upbound ET
1 1000 10523272.53
2 2000 5156046.27
3 3000 5053895.54
4 4000 4796505.3
5 5000 4392162.97
6 6000 4156065.87
31 31000 0
32 32000 21247.26
33 33000 0
34 34000 0
35 35000 0
36 36000 23877.74
正如您所看到的，我获得了重复的值。
可在此处找到输入ET, ED files
非常感谢任何帮助。非常感谢
迭
答案 0 :(得分：1)
首先让我通过一个简单的例子解释代码中发生的事情：
# Create "zone" variable
zone=1:10
# Create ET dataframe, that does not have some zones:
dET <- data.frame(zone=c(1:5,7,8), ET=runif(7, min=1, max=10))
dET
# zone ET
# 1 1 5.776128
# 2 2 9.067579
# 3 3 9.874737
# 4 4 7.846662
# 5 5 3.588964
# 6 7 3.843509
# 7 8 8.916714
#merge zone vector and the second column from dET dataframe:
# As you can see some values in the second columnd of the result are repeated to match
# the length of the zone vector and the value that originally belonged to 7th zone was moved into 6th zone
# since there was no 6th zone in the dataframe
cbind(zone, dET[,2])
# zone
# [1,] 1 5.776128
# [2,] 2 9.067579
# [3,] 3 9.874737
# [4,] 4 7.846662
# [5,] 5 3.588964
# [6,] 6 3.843509
# [7,] 7 8.916714
# [8,] 8 5.776128
# [9,] 9 9.067579
# [10,] 10 9.874737
#Instead you should use merge and then fill the missing values with zeros:
result <- merge(data.frame(zone=zone), dET, by="zone", all=TRUE)
result
# zone ET
# 1 1 5.776128
# 2 2 9.067579
# 3 3 9.874737
# 4 4 7.846662
# 5 5 3.588964
# 6 6 NA
# 7 7 3.843509
# 8 8 8.916714
# 9 9 NA
# 10 10 NA
result$ET[is.na(result$ET)] <- 0
# zone ET
# 1 1 5.776128
# 2 2 9.067579
# 3 3 9.874737
# 4 4 7.846662
# 5 5 3.588964
# 6 6 0.000000
# 7 7 3.843509
# 8 8 8.916714
# 9 9 0.000000
# 10 10 0.000000
以下是修改代码的方法。在这里，我只使用了两个文件ED和ET。所有其他应该以相同的方式进行修改：
library(raster)
library(rgdal)
ED<-raster("file_ED.tif")
ET<-raster("file_ET.tif")
lowbound<- seq(0,cellStats(ED,"max", na.rm=TRUE),1000)
upbound<-lowbound+1000
band<-upbound/1000
rclmat <- as.matrix(cbind(lowbound,upbound,band)) #to be used on reclassify
# Commented the following line since cellStats(ED,"max", na.rm=TRUE)=35125.57
# so you should not remove the values in the range 35K-36K
#rclmat<-rclmat[1:length(rclmat[,1])-1,]
ener_dens_band<- reclassify(ED, rclmat)
sum_ET<-zonal(ET,ener_dens_band,"sum")
# Let's look at the tail of the result:
tail(sum_ET)
# zone sum
# [25,] 26 27011.60
# [26,] 27 53905.17
# [27,] 28 18490.15
# [28,] 29 19322.07
# [29,] 32 21247.26
# [30,] 36 23877.74
# As you can see some zones are missing: 30, 31, 33-35
# So they need to be added
sum_ET <- merge(data.frame(zone=1:36), sum_ET, by="zone", all=TRUE)
sum_ET$sum[is.na(sum_ET$sum) ] <- 0
tail(sum_ET, n=10)
# zone sum
# 27 27 53905.17
# 28 28 18490.15
# 29 29 19322.07
# 30 30 0.00
# 31 31 0.00
# 32 32 21247.26
# 33 33 0.00
# 34 34 0.00
# 35 35 0.00
# 36 36 23877.74
您需要为其他列重复相同的操作，然后您可以使用cbind将它们全部放在一个数据框中。