【PythonGIS】基于Geopandas和Shapely计算矢量面最短路径

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        在GIS进行空间分析时经常会需要计算最短路径，我也是最近在计算DPC的时候有这方面的需求，刚开始直接是用面的中心点求得距离，但其对不规则或空洞面很不友好。所以今天跟大家分享一下基于Geopandas和Shapely计算矢量面最短路径，这里的最短即点/边的最短！

原创作者：RS迷途小书童

博客地址：https://blog.csdn.net/m0_56729804?type=blog

# -*- coding: utf-8 -*-
"""
@Time ： 2024/7/3 9:52
@Auth ： RS迷途小书童
@File ：Vectors Data Short Distance.py
@IDE ：PyCharm
@Purpose：检查两个要素的最短路径
@Web：博客地址:https://blog.csdn.net/m0_56729804
"""
from shapely.geometry import Polygon
from shapely.ops import nearest_points
import matplotlib.pyplot as plt
import geopandas as gpddef check_short_distance_between_vector(shp_path=r"Y:\1.shp"):""":param shp_path: 输入面矢量文件，默认计算前两个要素的最短路径:return: 最近点1，最近点2，最短路径"""gdf = gpd.read_file(shp_path)list_geometry = []for index, row in gdf.iterrows():  # 循环矢量属性表geometry = row['geometry']list_geometry.append(geometry)# polygon1 = Polygon([(0, 0), (1, 0), (1, 1), (0, 1)])# polygon2 = Polygon([(2, 2), (3, 2), (3, 3), (2, 3)])polygon1, polygon2 = list_geometry[0], list_geometry[1]point1, point2 = nearest_points(polygon1, polygon2)  # 使用 nearest_points 函数找到两个多边形之间的最近点distance = point1.distance(point2)  # 计算两点之间的距离print(f"The shortest path between the two polygons is {distance} units.")print(f"The points are {point1} and {point2}.")fig, ax = plt.subplots()  # 可视化两个多边形和最短路径x1, y1 = polygon1.exterior.xyx2, y2 = polygon2.exterior.xyax.plot(x1, y1, color='blue', label='Polygon 1')  # 绘制多边形ax.plot(x2, y2, color='green', label='Polygon 2')ax.plot([point1.x, point2.x], [point1.y, point2.y], color='red', linestyle='--', label='Shortest Path')  # 绘制最短路径ax.scatter([point1.x, point2.x], [point1.y, point2.y], color='red')ax.legend()plt.xlabel('X')plt.ylabel('Y')plt.title('Shortest Path between Two Polygons')plt.grid(True)plt.show()return point1, point2, distanceif __name__ == "__main__":check_short_distance_between_vector()

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