如何找到逐像素标准偏差? [英] How can I find the pixel-wise standard deviation?

问题描述

我有 20 个具有相同分辨率和范围的栅格.这是一个时间序列，每个栅格是一年.

I have 20 rasters with same resolution and extent. It's a time series and each raster is for one year.

我想计算所有栅格的像素标准偏差.到目前为止，我使用的是栅格包.

And I want to calculate the pixel-wise standard deviation of all rasters.So far, I am using the raster package.

qq2<-list(maxras1,maxras2,maxras3,maxras4,maxras5,maxras6,maxras7,maxras8,maxras9,maxras10)
qq2stack<-stack(qq2)
qq2mean<-mean(qq2stack)
qq2sd<-sd(qq2stack)

均值有效.但是标准偏差给了我这个错误:

The mean works. But standard deviation is giving me this error:

Error in as.double(x) : 
  cannot coerce type 'S4' to vector of type 'double'

推荐答案

不幸的是，正如您在我上面的评论后注意到的那样，逐像素分析可能很慢.我认为您接下来要尝试的是并行化该过程.假设您有一个多核处理器，您可以利用 calc() 及其内置的多进程优化:

Unfortunately, as you note after my comment above, per-pixel analyses can be slow. I think the next thing for you to try is to parallelize the process. Assuming you have a multi-core processor you can take advantage of calc() and its built-in multi-process optimization:

cores <- 4
beginCluster(cores, type='SOCK')
calc(qq2stack, fun=sd)
endCluster()

如果您的操作/硬件环境支持，这将导致显着的加速.显然，您也可以根据自己的架构增加进程数.

This would result in a significant speed-up if your operating/hardware environment supports it. Obviously, you can increase the number of processes as well depending on your architecture.

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