使用多多边形 Shapefile - GeoPandas 从大陆海岸线移除岛屿

Question

我想从澳大利亚海岸线上移除所有断开连接的岛屿。我已将国家/地区导入为 Shapefile，并且可以使用硬编码边界删除区域。但是，绕过整个海岸线以移除所有断开连接的岛屿将是低效的。使用 GeoPandas 有没有更快的方法？

import geoplot as gplt
import geopandas as gpd

Oz = gpd.read_file('OZ.shp')

#polygon = Polygon([(140, -40), (150, -40), (150, -45), (140,-45)])
#Oz_clip = gpd.clip(Oz, polygon)

Answer 1

使用了这里的几何图形：https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/access-and-downloads/digital-boundary-files
这包含一个由 6624 个多边形组成的多边形
已将多边形扩展为多边形，然后创建了一个 geodataframe，包括每个多边形的面积
您现在可以采用按最大面积多边形 head() 或面积超过阈值的多边形

import geopandas as gpd

gdf = gpd.read_file(
    "https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/access-and-downloads/digital-boundary-files/AUS_2021_AUST_SHP_GDA2020.zip"
)

# expand polygons and move to UTM geometry
polys = (
    gpd.GeoSeries(
        gdf.dropna()["geometry"].apply(lambda g: g.geoms).explode(), crs=gdf.crs
    )
    .to_crs(gdf.estimate_utm_crs())
    .simplify(100)
    .reset_index(drop=True)
)

# now build geodataframe limited by biggest area polygons
gdfm = (
    gpd.GeoDataFrame(data={"area": polys.area / 10**6}, geometry=polys, crs=polys.crs)
    .sort_values("area", ascending=0)
    # .head(3) # only one tasmania will be excluded
    .loc[lambda d: d["area"].gt(5000)]  # filter by size of polygon
    .reset_index()
)

# visualise
gdfm.explore(height=300, width=500)

    index   area    geometry
0   6411    7.787225e+06    POLYGON ((1023611.393 5771135.050, 1021232.002...
1   6373    6.490288e+04    POLYGON ((1497821.632 5153803.332, 1498006.176...
2   554 5.826181e+03    POLYGON ((26191.908 8735865.816, 26640.856 873..

使用多多边形 Shapefile - GeoPandas 从大陆海岸线移除岛屿

Remove islands from mainland coastline using a multipolygon Shapefile - GeoPandas

python

shapefile

geopandas