永久基本农田查询生成geojson数据

11-04更新

网站目前已经不在直接返回JSON数据了，查看网页使用了sm2加密，找到这个私钥直接进行模拟就可以了

请求数据中还增加了个token目前看来是个固定值

这里使用gmssl库来模拟sm2解密，传入请求的数据以及私钥

from gmssl import sm2
def decrypt_geojson(data,key):

    if data and data.startswith("04"):
        data = data[2:]
    sm2_crypt = sm2.CryptSM2(public_key="", private_key=key,mode=1)
    features = sm2_crypt.decrypt(bytes.fromhex(data))
    features=features.decode('utf-8')
    jsondata=json.loads(features)
    features=jsondata["recordsets"][0]["features"]

    return features

1、网页查询突破500亩限制

网站提供了点查询和范围查询，但是限制了500亩范围,直接上才艺

查看网页源文件发现这个限制实际是在前端进行验证的,找到这段代码直接注释掉

另外还有个1000个要素的限制，按需酌情修改，小心被ban

注意的是这里直接修改网页js是无法生效的，需要在替换文件夹中进行修改

2、PYTHON获取矢量数据

从网页查询就能看出来这就是一个矢量叠加影像

分析网络请求发现范围查询返回的是一个json数据，这里面就包含了所有要素的边界坐标，只要提取这个坐标信息就可以在GIS软件中还原出来了

2.1 矩形范围查找

使用网页的绘制范围绘制一个矩形范围进行查找，可以看到网页请求携带了这4个顶点坐标，服务器根据这4个顶点坐标生成了多边形然后在数据库查找返回

由于500亩的查询范围和1000片图斑的限制都是在前端验证的，这里使用脚本可以无需验证判断

矩形范围查询的示例

expectCount：默认为1000，限制了最大查询图斑数量

epsgCode：默认为4490，坐标系为CGCS2000

spatialQueryMode：INTERSECT使用几何相交查询

points：在geometry对象中需要传入区域的顶点坐标，矩形直接使用两个顶点坐标即可

如果使用多边形多个顶点也是可以的，修改顶点个数即可，points属性中的id字段需要唯一生成

可以看到这里使用的是超图supermap

form_data = {
    'queryMode': 'SpatialQuery',
    'queryParameters': {
        'customParams': None,
        'prjCoordSys': {'epsgCode': 4490},
        'expectCount': n,
        'networkType': "LINE",
        'queryOption': "ATTRIBUTEANDGEOMETRY",
        'queryParams': [{'name': "pro31@yndk", 'attributeFilter': "1=1", 'fields': None}],
        'startRecord': 0,
        'holdTime': 10,
        'returnCustomResult': False,
        'returnFeatureWithFieldCaption': False
    },
    'geometry': {
        'id': 0,
        'style': None,
        'parts': [5],
        'points': [
            {'id': "SuperMap.Geometry_1", 'bounds': None, 'SRID': None, 'x': x1, 'y': y1, 'tag': None, 'type': "Point", 'geometryType': "Point"},
            {'id': "SuperMap.Geometry_2", 'bounds': None, 'SRID': None, 'x': x2, 'y': y1, 'tag': None, 'type': "Point", 'geometryType': "Point"},
            {'id': "SuperMap.Geometry_3", 'bounds': None, 'SRID': None, 'x': x2, 'y': y2, 'tag': None, 'type': "Point", 'geometryType': "Point"},
            {'id': "SuperMap.Geometry_4", 'bounds': None, 'SRID': None, 'x': x1, 'y': y2, 'tag': None, 'type': "Point", 'geometryType': "Point"},
            {'id': "SuperMap.Geometry_5", 'bounds': None, 'SRID': None, 'x': x1, 'y': y1, 'tag': None, 'type': "Point", 'geometryType': "Point"}
        ],
        'type': "REGION",
        'prjCoordSys': {'epsgCode': None}
    },
    'spatialQueryMode': "INTERSECT"
}

运行示例

if __name__ == "__main__":
    # 默认最大查询1000片，请酌情修改，查询太多可能会被ban，按需查询
    expectCount=1000
    # 保存文件路径
    file_path = 'yjnt2.geojson'
    # 默认按矩形查找，传入左上与右下坐标，建议查询范围不要太大，爱护服务器
    x1=121.333167
    y1=32.2544
    x2=121.33784
    y2=32.25190

    fetures=get_features(x1,y1,x2,y2,expectCount)
    download_geojson(file_path,fetures)

生成的geojson示例文件格式如下，可以直接导入gis软件生成矢量：

{
"type": "FeatureCollection",
"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:EPSG::4490" } },
"features": [
{ "type": "Feature", "properties": { "ID": 42025373 }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 120.705093603000023, 32.419247212000073 ], [ 120.704840518000083, 32.41916201600003 ], [ 120.70477883600006, 32.419255580000026 ], [ 120.70504355300011, 32.41934593700006 ], [ 120.705092870000044, 32.419260273000077 ], [ 120.705093603000023, 32.419247212000073 ] ] ] } },
{ "type": "Feature", "properties": { "ID": 42030018 }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 120.705383644000108, 32.419345331000045 ], [ 120.705348222000111, 32.419333024000025 ], [ 120.705307874000027, 32.41941844400003 ], [ 120.705290340000033, 32.419430172000034 ], [ 120.705333192000012, 32.419444799000075 ], [ 120.705383644000108, 32.419345331000045 ] ] ] } },
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]
}

成果展示

直接在GIS软件中加载，可以叠加谷歌影像等查看，能够缩放到更高的比例

10-11更新

感谢salierib的提醒，原先生成的geojson没有考虑面要素内部孔洞的问题

获取到的json数据中partTopo和parts对象区分了外部和内部顶点

这里修改判断是否存在孔洞使用polygon的holes传参

for part in parts:
    end_index = start_index + part
    ring = [(points[i]['x'], points[i]['y']) for i in range(start_index, end_index)]

    if not exterior_ring:  # 如果外部边界尚未设置，则这是外部边界
        exterior_ring = ring
    else:  # 否则，这是一个内部边界
        interior_rings.append(ring)
    start_index = end_index

# 如果没有内部边界，Polygon 只需要外部边界
if not interior_rings:
    polygon = Polygon(exterior_ring)
else:
# 创建Polygon对象，第一个参数是外部边界，第二个参数是一个内部边界的列表
    polygon = Polygon(exterior_ring, holes=interior_rings)

2.2多边形查询

由于网页端设置了500亩和1000片的查询限制，我们直接突破限制查询可能会带来不必要的麻烦

建议还是按照网页端查询的规则来，模拟更真实的请求

另外网页端对每天的查询次数，每个IP的查询次数都是有限制的，虽然都是在前端完成的

但是这些措施都是为了防止请多过多、数据量过大给服务器带来压力

按照500亩的范围来查询，想要获得一个较大的区域如何来实现呢

你可能已经想到了，直接切割为更小的单元来进行

获取给定多边形的最大坐标边界，计算出宽和高，按照最小的粒度计算需要切割的瓦片数（500亩大概是577*577的网格）
计算出每个瓦片对应的度数
根据行列号遍历获取每个网格顶点坐标，使用2.1的矩形下载

示例代码

这里通过读取geojson文件的几何来获取多边形的边界

if __name__ == '__main__':
    # 读取GeoJSON文件，获取第一个多边形，多个自行遍历
    file_path = 'example.geojson'
    gdf = gpd.read_file(file_path)
    polygon = gdf.geometry.iloc[0]

    # 定义栅格大小,限制面积500亩,这里设置为500*500米
    grid_size = 500

    # 设置保存路径
    savefile_path = 'download_example.geojson'

    #下载栅格
    failure_grids=download_by_girds(polygon, grid_size, savefile_path)

    #保存下载失败栅格坐标，后续可以直接使用矩形查找增加
    with open('failure_girds', 'w') as file:
        json.dump(failure_grids, file)

成果展示

完整的下载后可以按需裁剪为范围内

免责声明

本爬虫脚本仅用于个人学习和研究目的。使用者应遵守当地法律法规，尊重网站的使用规定，并对使用本脚本所产生的任何法律责任自行承担。作者不对因滥用本脚本而产生的任何后果负责。使用本脚本即代表您同意以上免责申明。

ruiduobao/yncx

永久基本农田查询生成geojson数据

11-04更新

1、网页查询突破500亩限制

2、PYTHON获取矢量数据

2.1 矩形范围查找

矩形范围查询的示例

成果展示

10-11更新

2.2多边形查询

示例代码

成果展示

免责声明