如何找到轮廓图并以90个百分点突出显示？

发布于 2025-01-19 01:06:19 字数 493 浏览 0 评论 0原文

我有一个光栅图像，其值范围为 1 到 10。我想找到我的栅格数据的 90%。并且需要通过突出显示具有 90 百分位数的区域来找到等高线图。我想要我的栅格数据图附在下面。我正在 R 中进行分析。

   library(raster)
   library(cartography)
   library(sf)
   library(SpatialPosition)

   r <- raster("E:/data.tif", package="raster")
   plot(r)
   contour(r, add=TRUE)

我得到了这种类型的图像，但我想要带有阴影的图像（右侧）。非常感谢您帮助制作这张照片。

原文

I have a raster image whose value ranges from 1 to 10.
I want to find the 90 percentile of mine raster data. And need to find the contour graph by highlighting the area having the 90 percentile. I want a figure for my raster data is attached below. I am doing my analysis in R.

   library(raster)
   library(cartography)
   library(sf)
   library(SpatialPosition)

   r <- raster("E:/data.tif", package="raster")
   plot(r)
   contour(r, add=TRUE)

I got this type of image, but I wants the one with a shaded one (right side). Help on making this picture will be much appreciated.

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抱着落日 2025-01-26 01:06:19

显然，没有您的数据，但是我们可以制作这样的示例栅格：

r <- raster(t(volcano[,ncol(volcano):1]))

从现在开始，以下代码也应该与您自己的栅格一起使用。我们可以这样的数据中的第90世纪：

centile90 <- quantile(r[], 0.9)

现在，让我们将光栅转换为X，Y，Z数据框架：

df <- as.data.frame(as(r, "SpatialPixelsDataFrame"))
colnames(df) <- c("value", "x", "y")

我们可以使用功能丰富的ggplot2库来绘制数据。我们将绘制为填充的轮廓图，并在我们的第90世纪添加鲜艳的绿色轮廓：

library(ggplot2)

ggplot(df, aes(x, y, z = value)) +
  geom_contour_filled(bins = 10) +
  geom_contour(breaks = centile90, colour = "green",
               size = 2) +
  scale_fill_manual(values = hcl.colors(10, "YlOrRd", rev = TRUE)) +
  scale_x_continuous(expand = c(0, 0)) +
  scale_y_continuous(expand = c(0, 0)) +
  theme_classic() +
  theme(legend.position = "none")

Obviously, don't have your data, but we can make an example raster like this:

r <- raster(t(volcano[,ncol(volcano):1]))

From now on, the following code should work with your own raster too. We can get the 90th centile of our data like this:

centile90 <- quantile(r[], 0.9)

Now let's convert the raster to an x, y, z data frame:

df <- as.data.frame(as(r, "SpatialPixelsDataFrame"))
colnames(df) <- c("value", "x", "y")

We can use the feature-rich ggplot2 library for drawing the data. We will plot as a filled contour map and add a bright green contour at our 90th centile:

library(ggplot2)

ggplot(df, aes(x, y, z = value)) +
  geom_contour_filled(bins = 10) +
  geom_contour(breaks = centile90, colour = "green",
               size = 2) +
  scale_fill_manual(values = hcl.colors(10, "YlOrRd", rev = TRUE)) +
  scale_x_continuous(expand = c(0, 0)) +
  scale_y_continuous(expand = c(0, 0)) +
  theme_classic() +
  theme(legend.position = "none")