我一直致力于将KML文件加载到R中,以使用Leaflet / Shiny制作Web地图。导入非常简单(使用this sample KML):
library(rgdal)
sampleKml <- readOGR("D:/KML_Samples.kml", layer = ogrListLayers("D:/KML_Samples.kml")[1])
在此示例中,ogrListLayers
拉入所有kml图层,并且我仅对第一个元素/图层进行子集化。十分简单。
问题是使用这种方法读取KML图层只会拉入两个字段:&#34; Name&#34;和&#34;描述,&#34;如下所示:
> sampleKml <- readOGR("D:/KML_Samples.kml", layer = ogrListLayers("D:/KML_Samples.kml")[1])
OGR data source with driver: KML
Source: "D:/KML_Samples.kml", layer: "Placemarks"
with 3 features
It has 2 fields
> sampleKml@data
Name Description
1 Simple placemark Attached to the ground. Intelligently places itself at the height of the underlying terrain.
2 Floating placemark Floats a defined distance above the ground.
3 Extruded placemark Tethered to the ground by a customizable "tail"
因此,R将KML层读取为具有3个特征(3个不同点)和2个字段(列)的SpatialPointsDataFrame。但是,当我将图层拉入QGIS并读取其属性表时,除了名称和描述seen here之外,还有许多字段。
据我所知,&#39;姓名&#39;和&#39;描述&#39;是KML 地标,任何其他数据都被视为 ExtendedData 。我想将此扩展数据与地标数据一起导入。
有没有办法将所有这些KML图层字段/属性拉入R?最好是readOGR()
,但我对所有建议持开放态度。
答案 0 :(得分:2)
潜在的问题是Windows缺少LibKML库。我的解决方案是通过函数直接从KML中提取数据。
我遇到了同样的问题,经过一番搜索之后,看来这与LibKML和Windows有关。在我的Ubuntu计算机上执行相同的代码会产生不同的结果,即在加载保存的KML文件时检索了ExtendedData。
library(rgdal)
library(dplyr)
poly_df<-data.frame(x=c(1,1,0,0),y=c(1,0,0,1))
poly<-poly_df %>%
Polygon %>%
list %>%
Polygons(ID="1") %>%
list %>%
SpatialPolygons(proj4string = CRS("+init=epsg:4326")) %>%
SpatialPolygonsDataFrame(data=data.frame(test="this is a test"))
writeOGR(poly,"test.kml",driver="KML",layer="poly")
poly2<-readOGR("test.kml")
poly2@data
如果可以成功构建LibKML [1],则他/她将能够使用ExtendedData [2]加载KML文件。
在Windows上,需要使用Visual Studio 2005 [1]构建LibKML。不再支持此Visual Studio版本[3]。在[3]中,user2889419提供了指向2005版本的链接。
我下载并安装了该版本,但构建LibKML最终失败,并出现许多错误和警告(某些文件不存在)。这是我停下来的原因,因为我离我的舒适区很远,但想分享我的追逐结果。
我的解决方案是直接读取KML,然后在通过rgdal的readOGR加载空间对象的同时提取ExtendedData。我的假设是readOGR像提取例程一样从文件顶部开始。然后将两者合并,输出为SpatialPolygonsDataFrame。
起初我在从KML文件中提取节点时遇到了一些麻烦,因为我不了解名称空间的概念[4]。 (编辑以下功能是因为我遇到了其他来源的KML文件的麻烦。)
readKML <- function(file,keep_name_description=FALSE,layer,...) {
# Set keep_name_description = TRUE to keep "Name" and "Description" columns
# in the resulting SpatialPolygonsDataFrame. Only works when there is
# ExtendedData in the kml file.
sp_obj<-readOGR(file,layer,...)
xml1<-read_xml(file)
if (!missing(layer)) {
different_layers <- xml_find_all(xml1, ".//d1:Folder")
layer_names <- different_layers %>%
xml_find_first(".//d1:name") %>%
xml_contents() %>%
xml_text()
selected_layer <- layer_names==layer
if (!any(selected_layer)) stop("Layer does not exist.")
xml2 <- different_layers[selected_layer]
} else {
xml2 <- xml1
}
# extract name and type of variables
variable_names1 <-
xml_find_first(xml2, ".//d1:ExtendedData") %>%
xml_children()
while(variable_names1 %>%
xml_attr("name") %>%
is.na() %>%
any()&variable_names1 %>%
xml_children() %>%
length>0) variable_names1 <- variable_names1 %>%
xml_children()
variable_names <- variable_names1 %>%
xml_attr("name") %>%
unique()
# return sp_obj if no ExtendedData is present
if (is.null(variable_names)) return(sp_obj)
data1 <- xml_find_all(xml2, ".//d1:ExtendedData") %>%
xml_children()
while(data1 %>%
xml_children() %>%
length>0) data1 <- data1 %>%
xml_children()
data <- data1 %>%
xml_text() %>%
matrix(.,ncol=length(variable_names),byrow = TRUE) %>%
as.data.frame()
colnames(data) <- variable_names
if (keep_name_description) {
sp_obj@data <- data
} else {
try(sp_obj@data <- cbind(sp_obj@data,data),silent=TRUE)
}
sp_obj
}
我的解决方案是直接读取KML,然后在通过rgdal的readOGR加载空间对象的同时提取ExtendedData。我的假设是readOGR像提取例程一样从文件顶部开始。然后将两者合并,输出为SpatialPolygonsDataFrame。
library(tidyverse)
library(rgdal)
readKML<-function(file,keep_name_description=FALSE,...) {
# Set keep_name_description = TRUE to keep "Name" and "Description" columns
# in the resulting SpatialPolygonsDataFrame. Only works when there is
# ExtendedData in the kml file.
if (!grepl("\\.kml$",file)) stop("File is not a KML file.")
if (!file.exists(file)) stop("File does not exist.")
map<-readOGR(file,...)
f1<-readLines(file)
# get positions of ExtendedData in document
exdata_position<-grep("ExtendedData",f1) %>%
matrix(ncol=2,byrow = TRUE) %>%
apply(1,function(x) {
pos<-x[1]:x[2]
pos[2:(length(pos)-1)]
}) %>%
t %>%
as.data.frame
# if there is no ExtendedData return SpatialPolygonsDataFrame
if (ncol(exdata_position)==0) return(map)
# Get Name of different columns
extract1<-f1[exdata_position[1,] %>%
unlist]
names_of_data<-extract1 %>%
strsplit("name=\"") %>%
lapply(function(x) strsplit(x[[2]],split="\"") ) %>%
unlist(recursive = FALSE) %>%
lapply(function(x) return(x[1])) %>%
unlist
# Extract Extended Data
dat<-lapply(seq(nrow(exdata_position)),function(x) {
extract2<-f1[exdata_position[x,] %>%
unlist]
extract2 %>%
strsplit(">") %>%
lapply(function(x) strsplit(x[[2]],split="<") ) %>% unlist(recursive = FALSE) %>%
lapply(function(x) return(x[1])) %>%
unlist %>%
matrix(nrow=1) %>%
as.data.frame
}) %>%
do.call(rbind,.)
# Rename columns
colnames(dat)<-names_of_data
# Check if Name and Description should be dropped
if (keep_name_description) {
map@data<-cbind(map@data,dat)
} else {
map@data<-dat
}
map
}
[1] https://github.com/google/libkml/wiki/Building-and-installing-libkml
[2] https://github.com/r-spatial/sf/issues/499
[3] Where to download visual studio express 2005?
[4] Parsing XML in R: Incorrect namespaces