在 rgeos 中简化多边形并在 SpatialPolygonsDataFrame 中维护数据

Simplifying polygons in rgeos and maintaining data in SpatialPolygonsDataFrame

背景

我对使用 gSimplify function available through the rgeos 包简化多边形很感兴趣。

可重现的例子

可以使用以下代码生成可重现的示例:

# Data sourcing -----------------------------------------------------------

# Download an read US state shapefiles
tmp_shps <- tempfile()
tmp_dir <- tempdir()
download.file(
    "http://www2.census.gov/geo/tiger/GENZ2014/shp/cb_2014_us_state_20m.zip",
    tmp_shps
)
unzip(tmp_shps, exdir = tmp_dir)

# Libs
require(rgdal)
require(rgeos)

# Read
us_shps <- readOGR(dsn = tmp_dir, layer = "cb_2014_us_state_20m")

# Simplified --------------------------------------------------------------

# Simplifiy
us_shps_smpl <- gSimplify(spgeom = us_shps,
                          tol = 200,
                          topologyPreserve = TRUE)

预览

par(mfrow = c(2,1))
plot(us_shps_smpl, main = "Simplified")
plot(us_shps, main = "Original")

问题

除了简化多边形之外,gSimplify 函数更改了结果对象的 classes:

>> class(us_shps)
[1] "SpatialPolygonsDataFrame"
attr(,"package")
[1] "sp"
>> class(us_shps_smpl)
[1] "SpatialPolygons"
attr(,"package")
[1] "sp"

>> names(us_shps)
[1] "STATEFP"  "STATENS"  "AFFGEOID" "GEOID"    "STUSPS"   "NAME"     "LSAD"     "ALAND"    "AWATER"  
>> names(us_shps_smpl)
 [1] "0"  "1"  "2"  "3"  "4"  "5"  "6"  "7"  "8"  "9"  "10" "11" "12" "13" "14" "15" "16" "17" "18" "19"
[21] "20" "21" "22" "23" "24" "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36" "37" "38" "39"
[41] "40" "41" "42" "43" "44" "45" "46" "47" "48" "49" "50" "51"

问题

sf 包完全基于数据框,因此其几何操作始终保留附加到每个要素的数据。该包还没有赶上 R 中的所有标准空间包,但是当您需要更多功能时,可以很容易地在 sfsp 对象之间来回切换。

此处,st_simplify() 完成工作,但您需要先投影多边形:

library(sf)

# Download and read example data
tmp_shps <- tempfile()
tmp_dir <- tempdir()
download.file(
  "http://www2.census.gov/geo/tiger/GENZ2014/shp/cb_2014_us_state_20m.zip",
  tmp_shps
)
unzip(tmp_shps, exdir = tmp_dir)

us_shps <- st_read(paste(tmp_dir, "cb_2014_us_state_20m.shp", sep = "/"))

# st_simplify needs a projected CRS
us_shps_merc <- st_transform(us_shps, 3857)
simple_us_merc <- st_simplify(us_shps_merc)

# Change back to original CRS
simple_us <- st_transform(simple_us_merc, st_crs(us_shps))

# Change to sp object, if you like
simple_us_sp <- as(st_zm(simple_us), "Spatial")