使用栅格输出问题的模型预测

问题描述

我正在尝试使用栅格预测空间范围内的结果,类似于 in the section on model prediction here

模型结构如下

m1 <- glm(wb_bin ~ data1$evi_sc,family="binomial",data=data1)

我的预测变量的栅格堆栈:

evi_sc1 <- raster("prediction_rasters/evi_sc.tif")
predras <- stack(evi_sc1)
plot(predras)

the raster I'm using to predict

但是,当我进行如下预测时,我收到的是数字预测而不是预期的预测图,以及随之而来的错误

p <- predict(predras,m1)
Error in p[-naind,] <- predv : 
  number of items to replace is not a multiple of replacement length
In addition: Warning message:
'newdata' had 854 rows but variables found have 516 rows 

str(p)
num [1:516] 1 0 0 1 0 1 1 0 0 0 ...

我仔细检查了 mydata 变量都包含 516 个观察值,所以我不确定 854 行错误来自哪里。

我是否遗漏了一个步骤,我应该输入模型的空间范围,以便可以链接栅格预测和模型?

DATA: 
dput(data1$wb_bin)
c(1L,0L,1L,1L)

> dput(data1$evi_sc)
c(0.47,0.46,0.5,0.65,0.58,0.43,0.44,0.47,0.59,0.57,0.64,0.45,0.41,0.54,0.51,0.62,0.52,0.4,0.53,0.61,0.56,0.55,0.48,0.49,0.42,0.63,0.6,0.73,0.69,0.68,0.71,0.7,0.67,0.66,0.55
)

解决方法

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