将 'multifeature' GeoJSON 的特征转换为 R 空间对象

Question

通常您可以使用 trusty readOGR 将 geojson 文件读入 R，如图所示 here。

但是，对于多功能 geojson，这会失败。

可重现的例子：

downloader::download("https://github.com/Robinlovelace/Creating-maps-in-R/raw/master/data/test-multifeature.geojson", "test.geojson")
test <- rgdal::readOGR("test.geojson", "OGRGeoJSON") # fails with:

Error in ogrInfo(dsn = dsn, layer = layer, encoding = encoding, use_iconv = use_iconv,  : 
  Multiple incompatible geometries: wkbPoint: 98; wkbLineString: 660; wkbPolygon: 23

错误消息很清楚，并指出了解决方案：拆分功能。但是，除了使用正则表达式执行此操作外，我不知道该怎么做。

非常欢迎任何想法。

令人惊奇的是：GitHub displays the data natively on the browser，而 R 甚至（似乎）无法读入它！

另一种解决方法：

test <- geojsonio::geojson_read("test.geojson")

Answer 1

您可以在命令行上使用 ogr2ogr 将这个巨大的嵌合体拆分为可感知的东西：

ogr2ogr -where "OGR_GEOMETRY='LINESTRING'" \
     -f "GeoJSON" lines.geojson  test.geojson

点和多边形也类似。

几年前有一些关于将 OGR_SQL 实现到 readOGR 的讨论，那时您可以从 R 中执行此操作，但 Roger 不想这样做并且没有人愿意帮忙:(

创建拆分的 geojson 文件后，您可以将它们读入单个 rgeos::SpatialCollections 对象：

points=readOGR("points.geojson","OGRGeoJSON")
polys=readOGR("polygons.geojson","OGRGeoJSON")
lines=readOGR("lines.geojson","OGRGeoJSON")
require(rgeos)
g = SpatialCollections(points=points, lines=lines, polygons=polys)
plot(g)

如果您想尝试使用 geojsonio 进行一些尝试，那么您可以使用 Filter 来 select 列出几何集合中给定几何的元素

polygon_features = Filter(
    function(f){f$geometry$type=="Polygon"},
    test$features)

但是你仍然需要构建一些你可以进入单独的 R 实体的东西....

Answer 2

您可以使用各种 GDAL 函数的 require_geomType 参数来提取您需要的特征：

library(rgdal)

ogrListLayers("test.geojson")
## [1] "OGRGeoJSON"
## attr(,"driver")
## [1] "GeoJSON"
## attr(,"nlayers")
## [1] 1

# This fails but you can at least see the geoms it whines about
ogrInfo("test.geojson", "OGRGeoJSON")
## Error in ogrInfo("test.geojson", "OGRGeoJSON") : 
##   Multiple incompatible geometries: wkbPoint: 98; wkbLineString: 660; wkbPolygon: 23


ogrInfo("test.geojson", "OGRGeoJSON", require_geomType="wkbPoint")
## NOTE: keeping only 98 wkbPoint of 781 features
##     note that extent applies to all features
## Source: "test.geojson", layer: "OGRGeoJSON"
## Driver: GeoJSON number of rows 781 
##   selected geometry type: wkbPoint with 98 rows
## Feature type: wkbPoint with 2 dimensions
## Extent: (12.48326 41.88355) - (12.5033 41.89629)
## CRS: +proj=longlat +datum=WGS84 +no_defs  
## Number of fields: 78 
##                        name type length typeName
## 1                      area    4      0   String
## 2                   bicycle    4      0   String
## ...
## LONG LIST - 78 total


ogrInfo("test.geojson", "OGRGeoJSON", require_geomType="wkbLineString")
## NOTE: keeping only 660 wkbLineString of 781 features
##     note that extent applies to all features
## Source: "test.geojson", layer: "OGRGeoJSON"
## Driver: GeoJSON number of rows 781 
##   selected geometry type: wkbLineString with 660 rows
## Feature type: wkbLineString with 2 dimensions
## Extent: (12.48326 41.88355) - (12.5033 41.89629)
## CRS: +proj=longlat +datum=WGS84 +no_defs  
## Number of fields: 78 
##                        name type length typeName
## 1                      area    4      0   String
## 2                   bicycle    4      0   String
## ...
## LONG LIST - 78 total (same as above)


ogrInfo("test.geojson", "OGRGeoJSON", require_geomType="wkbPolygon")
## NOTE: keeping only 23 wkbPolygon of 781 features
##     note that extent applies to all features
## Source: "test.geojson", layer: "OGRGeoJSON"
## Driver: GeoJSON number of rows 781 
##   selected geometry type: wkbPolygon with 23 rows
## Feature type: wkbPolygon with 2 dimensions
## Extent: (12.48326 41.88355) - (12.5033 41.89629)
## CRS: +proj=longlat +datum=WGS84 +no_defs  
## Number of fields: 78 
##                        name type length typeName
## 1                      area    4      0   String
## 2                   bicycle    4      0   String
## ...
## LONG LIST - 78 total (same as above)


points <- readOGR("test.geojson", "OGRGeoJSON", require_geomType="wkbPoint")
## OGR data source with driver: GeoJSON 
## Source: "test.geojson", layer: "OGRGeoJSON"
## with 781 features;
## Selected wkbPoint feature type, with 98 rows
## It has 78 fields
## NOTE: keeping only 98 wkbPoint of 781 features

lines <- readOGR("test.geojson", "OGRGeoJSON", require_geomType="wkbLineString")
## OGR data source with driver: GeoJSON 
## Source: "test.geojson", layer: "OGRGeoJSON"
## with 781 features;
## Selected wkbLineString feature type, with 660 rows
## It has 78 fields
## NOTE: keeping only 660 wkbLineString of 781 features

polygons <- readOGR("test.geojson", "OGRGeoJSON", require_geomType="wkbPolygon")
## OGR data source with driver: GeoJSON 
## Source: "test.geojson", layer: "OGRGeoJSON"
## with 781 features;
## Selected wkbPolygon feature type, with 23 rows
## It has 78 fields
## NOTE: keeping only 23 wkbPolygon of 781 features

# prove they red in things
plot(lines, col="#7f7f7f")
plot(polygons, add=TRUE)
plot(points, add=TRUE, col="red")

Answer 3

几年后，一些替代方案 - library(geojsonsf) 和 library(sf) 都将读取 geojson 并转换为 sf 对象

url <- 'https://github.com/Robinlovelace/Creating-maps-in-R/raw/master/data/test-multifeature.geojson'

## these give the same result
sf <- geojsonsf::geojson_sf( url )
sf <- sf::st_read( url )

一起来看看

library(mapdeck)

set_token( "MAPBOX_TOKEN" )

mapdeck( style = mapdeck_style("light") ) %>%
    add_sf( sf )

将 'multifeature' GeoJSON 的特征转换为 R 空间对象

Convert features of a 'multifeature' GeoJSON into R spatial objects

r

geojson

gdal

rgdal

ropensci