您正在寻找的过程称为多边形中的点，正如另一个答案提到的，您可以使用函数.within（）现在，用你已经有...
find all intersecting geometries between left and right, and calculate their intersections aggregate by unique records from the left and union (dissolve) intersecting records from the right, then use that union of right geometries to difference geometries in the left same thing but from right to le...
At one point during the operation, shapely/pygeos returns invalid polygon. The next step after that fails. Sometimes it helps to round coordinates but not in this case (code for that below for someone else who may find this). I am not sure how to fix that to be honest apart from addin...
我正在尝试实现一个应用程序,它使用Google 绘制Points、LineStrings和Polygons,这些坐标包含在存储在MongoDB实例中的GeoJson文件中。我正在使用Mongoose为我的数据构建模式并查询我的MongoDB数据库。 我想找出最近的点,CP到某个点,P0,给定P0's latitude and longitude,给出一个最大半径,distance,用来找到感兴趣的点。
You can clip the points using the smaller polygons, then subset the larger polygons using a lambda function to find which ones contain any remaining points, such as: import geopandas as gpd #read in data large = gpd.read_file(r'./polys.shp') small = gpd.read_file(r'./polys2.shp'...
(r"C:/GIS/data/Bakgrundskartor/Topografi_250/data/naturvard_sverige.gpkg", layer="skyddadnatur") joined = gpd.sjoin(left_df=df, right_df=df2, how="inner", predicate="intersects") #Find the intersecting polygons nonintersecting = df.loc[~df["tempid"].isin(joined["tempid"])] #...
Using the geopandas.clip tool I've been able to do the exact opposite of what I need to do: clip the data to keep (not remove) the intersecting portion of my lines: # Clip lines to keep only area within `polygons_gdf` clipped_gdf = gpd.clip(lines_gdf, polygons_gdf) #...
Original close reason(s) were not resolved Improve this question I am trying to find the largest intersecting area for each Polygon in a layer1 compared to the geometries in a layer2 in python. I use geopandas.overlay for it. However, the geometries in layer2 don't cover the entire ...
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# iterate over each row in df and identify intersecting polygonsforindex, rowindf.iterrows(): match_poly = df[df.geometry.intersects(titre_polyG['geometry'])] match_polyshows the rows ofdfwhere there is an intersection withtitre_polyG. ...