[英]Geopandas dataframe to select certain ID and find geometries within specified distance
我在 EPSG:2157 中创建了一个包含 15 个点特征的测试 shapefile,并将其导出为 geojson。 每个点都被分配了一个 ID - 例如 1, 2 ,3 等。它们看起来像这样:
{
"type": "FeatureCollection",
"features": [
{
"type": "Feature",
"properties": {
"id": "1"
},
"geometry": {
"type": "Point",
"coordinates": [
-5.905044078826904,
54.609987802465916
]
}
},
{
"type": "Feature",
"properties": {
"id": "11"
},
"geometry": {
"type": "Point",
"coordinates": [
-5.902683734893799,
54.60972062159888
]
}
}
]
}
etc
我现在想使用 Python 来本质上:
到目前为止,我已经尝试过geopandas
来让我按照https://gis.stackexchange.com/questions/349637/given-list-of-points-lat-long-how-to-find-all-points-within-给予半径
import geopandas as gpd
import pandas as pd
input_file = 'C:/test/points.geojson'
df = gpd.read_file(input_file)
df['lon'] = df['geometry'].x
df['lat'] = df['geometry'].y
gdf = gpd.GeoDataFrame(
df,
geometry=gpd.points_from_xy(
df["lon"],
df["lat"],
),
crs={"init":"EPSG:2157"},
)
print(gdf)
gdf_proj = gdf.to_crs({"init": "EPSG:3857"})
x = gdf_proj.buffer(10)
neighbours = gdf_proj["geometry"].intersection(x)
# print all the nearby points
print(gdf_proj[~neighbours.is_empty])
但这只是用所有 15 个 ID 和经度/纬度打印我的原始 geopandas 数据框,
我需要一种从数据帧中指定我想要的 ID 的方法,在其上设置 10 米缓冲区并从该打印剩余 14 个点 ID 中的任何一个以及与该点的距离。
我该怎么办?
这种方法首先计算到所选点的距离,然后过滤到搜索距离:
import geopandas as gpd
input_file = 'test.geojson'
gdf = gpd.read_file(input_file).to_crs('EPSG:3857')
my_id = 1
search_distance = 10
selected_feature = gdf.loc[gdf['id'].astype(int) == my_id]
result = (
gdf
.assign(distance=gdf.apply(lambda x: x.geometry.distance(selected_feature.geometry.iloc[0]), axis=1))
.query(f'distance <= {search_distance}')
)
print(result)
输出:
id geometry distance
0 1 POINT (-657346.500 7286537.676) 0.000000
1 2 POINT (-657339.334 7286538.871) 7.264817
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.