Python 两个地理坐标系之间的交点

我正在Geopanda库上做一些工作，我有一个包含多边形的形状文件和excel表格上的数据，我将其转换为点。我想将两个数据帧相交并将其导出到一个文件中。我也在两个投影上使用（WGS84），以便比较它们。 应该至少有一些点与多边形相交。 我的intersect GeoSeries没有给我任何适合多边形的点，但我不明白为什么

我检查了shapefile的单位是否真的是公里，而不是别的什么。我对GeoPlot并不精通，所以我不能真正确定GeopataFrame是什么样子

f = pd.read_excel(io = 'C:\\Users\\peilj\\meteo_sites.xlsx')

#Converting panda dataframe into a GeoDataFrame with CRS projection
geometry = [Point(xy) for xy in zip(df.geoBreite, df.geoLaenge)]
df = df.drop(['geoBreite', 'geoLaenge'], axis=1)
crs = "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs"
gdf = GeoDataFrame(df, crs=crs, geometry=geometry)

#Reading shapefile and creating buffer
gdfBuffer = geopandas.read_file(filename = 'C:\\Users\\peilj\\lkr_vallanUTM.shp')
gdfBuffer = gdfBuffer.buffer(100) #When the unit is kilometer

#Converting positions long/lat into shapely object
gdfBuffer = gdfBuffer.to_crs("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs")

#Intersection coordonates from polygon Buffer and points of stations
gdf['intersection'] = gdf.geometry.intersects(gdfBuffer)
#Problem: DOES NOT FIND ANY POINTS INSIDE STATIONS !!!!!!!

#Giving CRS projection to the intersect GeoDataframe
gdf_final = gdf.to_crs("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs")
gdf_final['intersection'] = gdf_final['intersection'].astype(int) #Shapefile does not accept bool

#Exporting to a file
gdf_final.to_file(driver='ESRI Shapefile', filename=r'C:\\GIS\\dwd_stationen.shp

所需文件： 有两件事：

创建点时，您需要交换

geobrete

和

geoLaenge

：

geometry=[拉链中xy的点（xy）（df.geoLaenge，df.geobrete）]

这是因为shapely遵循x，y逻辑，而不是lat，lon

至于检查交叉口，您可以执行以下操作：

gdf['inside'] = gdf['geometry'].apply(lambda shp: shp.intersects(gdfBuffer.dissolve('LAND').iloc[0]['geometry']))

它检测形状文件中的六个桩号：

gdf['inside'].sum()

输出：

6

因此，除了其他一些小的修复外，我们还得到：

import geopandas as gpd
from shapely.geometry import Point

df = pd.read_excel(r'C:\Users\peilj\meteo_sites.xlsx')

geometry = [Point(xy) for xy in zip(df.geoLaenge, df.geoBreite)]
crs = {'init': 'epsg:4326'}
gdf = gpd.GeoDataFrame(df, crs=crs, geometry=geometry)

gdfBuffer = gpd.read_file(filename = r'C:\Users\peilj\lkr_vallanUTM.shp')
gdfBuffer['goemetry'] = gdfBuffer['geometry'].buffer(100)

gdfBuffer = gdfBuffer.to_crs(crs)

gdf['inside'] = gdf['geometry'].apply(lambda shp: shp.intersects(gdfBuffer.dissolve('LAND').iloc[0]['geometry']))

两件事：

创建点时，您需要交换

geobrete

和

geoLaenge

：

geometry=[拉链中xy的点（xy）（df.geoLaenge，df.geobrete）]

这是因为shapely遵循x，y逻辑，而不是lat，lon

至于检查交叉口，您可以执行以下操作：

gdf['inside'] = gdf['geometry'].apply(lambda shp: shp.intersects(gdfBuffer.dissolve('LAND').iloc[0]['geometry']))

它检测形状文件中的六个桩号：

gdf['inside'].sum()

输出：

6

因此，除了其他一些小的修复外，我们还得到：

import geopandas as gpd
from shapely.geometry import Point

df = pd.read_excel(r'C:\Users\peilj\meteo_sites.xlsx')

geometry = [Point(xy) for xy in zip(df.geoLaenge, df.geoBreite)]
crs = {'init': 'epsg:4326'}
gdf = gpd.GeoDataFrame(df, crs=crs, geometry=geometry)

gdfBuffer = gpd.read_file(filename = r'C:\Users\peilj\lkr_vallanUTM.shp')
gdfBuffer['goemetry'] = gdfBuffer['geometry'].buffer(100)

gdfBuffer = gdfBuffer.to_crs(crs)

gdf['inside'] = gdf['geometry'].apply(lambda shp: shp.intersects(gdfBuffer.dissolve('LAND').iloc[0]['geometry']))