简化rgeos中的多边形并在SpatialPolygonsDataFrame中维护数据

Question

Background

我有兴趣使用gSimplify软件包提供的rgeos函数来简化多边形。

Reproducible example

使用以下代码可以生成可重现的示例：

# 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)

预习

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

Problem

除了简化多边形之外，gSimplify函数还更改了结果对象的类：

>> 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

• 如何安全地重新连接原始对象中最初可用的数据并将生成的SpatialPolygons对象转换为SpatialPolygonsDataFrame
• 我认为一种方法只涉及attaching data frame;但这取决于元素的顺序不变。还有其他更好的方法（理想情况下保留初始对象类）吗？

Answer 1

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。该软件包尚未赶上R中的所有标准空间软件包，但是当您需要更多功能时，在sf和sp对象之间来回相当容易。

在这里，st_simplify()完成了工作，但您需要首先投影多边形：

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")