import geopandas as gpd
from pyproj import CRS
import pandas as pd


BASE_DIR = 'D:/demo'

# 輸入的WGS84 GeoJSON文件列表
geojson_files = [f"{BASE_DIR}/file1.geojson", f"{BASE_DIR}/file2.geojson", f"{BASE_DIR}/file3.geojson"]

# 目標(biāo)坐標(biāo)系的EPSG代碼，使用一個(gè)西安80高斯投影舉例
target_epsg = 2363

# 創(chuàng)建一個(gè)空的GeoDataFrame
merged_gdf = gpd.GeoDataFrame()

# 定義WGS84和目標(biāo)坐標(biāo)系之間的坐標(biāo)轉(zhuǎn)換
wgs84_crs = CRS.from_epsg(4326)
target_crs = CRS.from_epsg(target_epsg)

# 逐個(gè)讀取、轉(zhuǎn)換和合并GeoJSON文件
for geojson_file in geojson_files:
    gdf = gpd.read_file(geojson_file, crs=wgs84_crs)
    # 為每個(gè)geodataframe新添加字符類型的字段name，并將文件名賦值給字段name
    gdf['name'] = geojson_file[-13:-8]
    gdf = gdf.to_crs(target_crs)
    merged_gdf = pd.concat([merged_gdf, gdf], ignore_index=True)

# 過濾掉面積小于100的要素
gdf_filtered = merged_gdf[merged_gdf["area"] >= 100]
# 保存為shp文件
gdf_filtered.to_file(output_shp, driver='ESRI Shapefile', encoding='utf-8')

# shp to GeoJson
import geopandas as gpd
data = gpd.read_file('中國省級區(qū)域20200720.shp')
data.to_file("中國省級區(qū)域20200720.json", driver='GeoJSON', encoding="utf-8")

# GeoJson to shp
data = gpd.read_file('中國省級區(qū)域20200720.json')
data.to_file('中國省級區(qū)域20200720', driver='ESRI Shapefile', encoding='utf-8')