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使发生数据和气候栅格中的 SpatialGridDataFrame 相互匹配

[英]Make SpatialGridDataFrame from occurrence data and climate raster match each other

 原文  2022-01-24 15:00:55  4   2    r/ spatial/ sp

问题描述

我有两个SpatialGridDataFrame ，一个来自物种发生数据，另一个来自气候数据栅格。 我需要使两个网格相互匹配以执行物种多样性 model。 我正在努力使两个对象的网格拓扑相同，这是运行我将使用的 function 所必需的。

以下是我的可重复性数据的子集：

bioclim <- structure(list(x = c(-83.5543059413, -83.545972608, -83.5376392747, 
-83.5293059414, -83.5209726081, -83.5126392748, -83.5043059415, 
-83.4959726082, -83.4876392749, -83.4793059416, -83.4709726083, 
-83.462639275, -83.4543059417, -83.4459726084, -83.4376392751, 
-83.4293059418, -83.4209726085, -83.4126392752, -83.5543059413, 
-83.545972608, -83.5376392747, -83.5293059414, -83.5209726081, 
-83.5126392748, -83.5043059415, -83.4959726082, -83.4876392749, 
-83.4793059416, -83.4709726083, -83.462639275, -83.4543059417, 
-83.4459726084, -83.4376392751, -83.4293059418, -83.4209726085, 
-83.4126392752, -83.4043059419, -83.5543059413, -83.545972608, 
-83.5376392747, -83.5293059414, -83.5209726081, -83.5126392748, 
-83.5043059415, -83.4959726082, -83.4876392749, -83.4793059416, 
-83.4709726083, -83.462639275, -83.4543059417, -83.4459726084, 
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-83.4043059419, -83.3959726086, -83.3876392753, -83.5543059413, 
-83.545972608, -83.5376392747, -83.5293059414, -83.5209726081, 
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-83.4793059416, -83.4709726083, -83.462639275, -83.4543059417, 
-83.4459726084, -83.4376392751, -83.4293059418, -83.4209726085, 
-83.4126392752, -83.4043059419, -83.3959726086, -83.3876392753, 
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-83.4293059418, -83.4209726085, -83.4126392752, -83.4043059419, 
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8.43736071740001), CHELSA_bio1_1981.2010_V.2.1 = c(24.55, 24.55, 
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26.15, 26.15, 26.05, 26.05, 26.05, 26.15, 26.15, 26.15, 26.05, 
25.65)), row.names = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 
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494L, 495L, 496L, 497L, 498L, 499L, 500L, 501L, 502L, 503L, 504L, 
505L, 506L), class = "data.frame")

occ_df <- structure(list(lon = c(-83.41, -83.51, -83.41143, -83.525, -83.46, 
-83.46, -83.43, -83.49, -83.41, -83.44, -83.46944, -83.427778, 
-83.516667, -83.433609, -83.411431, -83.55, -83.516805), lat = c(8.54, 
8.56, 8.540221, 8.540278, 8.51, 8.52, 8.52, 8.45, 8.52, 8.52, 
8.51805, 8.525, 8.566667, 8.531329, 8.540221, 8.45, 8.569294), 
    `Chrysochlamys glauca` = c(1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 
    0, 1, 1, 1, 1, 1, 0), `Ocotea atirrensis` = c(0, 1, 0, 0, 
    1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1)), class = c("tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -17L))

这是我目前拥有的

library(dplyr)

clim <- terra::rast(bioclim)
terra::crs(clim) <- "+proj=longlat +datum=WGS84 +no_defs"

clim_sg_df <- raster::raster(clim) %>% 
  as("SpatialGridDataFrame")


occ <- occ_df %>% 
  # rounding lon/lat to fix inconstant coordinate intervals when using gridded()
  mutate(across(
    matches("lon|lat"),
    ~ round(.x, 2) 
  ))

sp::coordinates(occ) <- ~ lon + lat
sp::proj4string(occ) <- "+proj=longlat +datum=WGS84 +no_defs"
sp::gridded(occ) <- TRUE
occ_sg_df <- as(occ_sp, "SpatialGridDataFrame")

# terra::plot(clim_sg_df)
# terra::plot(occ_sg_df, add = TRUE)

我有两个主要问题。 首先，尽管投影相同，但我不能 plot 两个网格相互重叠，所以我怀疑我的代码有错误。 其次，两个对象之间的网格单元大小不同，我真的不知道如何使它们均匀化。

我需要让clim_sg_df和occ_sg_df匹配，以便以下条件返回TRUE ：

identical(as(occ_sg_df, "SpatialGrid"), as(clim_sg_df, "SpatialGrid"))

请注意，我需要保留栅格中的所有单元格并使用sp package，因为这是我将用于分析的函数所需要的。

2 个解决方案

解决方案1
 1 已采纳  2022-01-24 16:05:35

#here you have first raster created
clim <- terra::rast(bioclim)
terra::crs(clim) <- "+proj=longlat +datum=WGS84 +no_defs"

#lets create another raster with exactly the same size
#lets clear it
#
occ <- clim
occ[] <- NA

occ_df <- occ_df %>% 
  # rounding lon/lat to fix inconstant coordinate intervals when using gridded()
  mutate(across(
    matches("lon|lat"),
    ~ round(.x, 2) 
  ))

sp::coordinates(occ_df) <- ~ lon + lat
sp::proj4string(occ_df) <- "+proj=longlat +datum=WGS84 +no_defs"

# lets create a vector object which later will be used for rasterization
occ_vec <- vect(occ_df)

# now the important step - rasterizing vector data over raster grid
#
occ <- rasterize(occ_vec, occ)

terra::plot(clim)
terra::plot(occ, add = TRUE )

由代表 package (v2.0.1) 于 2022 年 1 月 24 日创建

PS。 为了获得更好的可见性，您可以更改颜色，例如

terra::plot(occ, add = TRUE, col = "red" )

解决方案2
 0  2022-01-24 17:39:20

您不应该为此使用gridded ，而是使用rasterize 。 例如，这个栅格和这些点：

library(terra)
r <- rast(system.file("ex/elev.tif", package="terra"))
set.seed(123)
pts <- spatSample(r, 1000, xy=TRUE, na.rm=TRUE, replace=TRUE)
xy <- as.matrix(pts[, c("x", "y")])

你可以做

spp <- rasterize(xy, r)

或按单元格计算出现次数

spp <- rasterize(xy, r, 1, fun=sum)

如果您愿意，也可以使用raster::rasterize 。

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