利用 Python 进行地理空间数据处理的九个工具

pip install geopandas
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import geopandas as gpd

# 读取 Shapefile
gdf = gpd.read_file("path/to/your/shp/file.shp")
print(gdf.head())

# 创建简单的几何对象
from shapely.geometry import Point

geometry = [Point(xy) for xy in zip(gdf['longitude'], gdf['latitude'])]
gdf = gpd.GeoDataFrame(gdf, geometry=geometry)

# 绘制地图
gdf.plot()
plt.show()
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pip install fiona
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import fiona

# 打开 Shapefile
with fiona.open("path/to/your/shp/file.shp", "r") as source:
    for feature in source:
        print(feature['properties'])
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pip install rasterio
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import rasterio

# 读取 TIFF 文件
with rasterio.open("path/to/your/tif/file.tif") as src:
    image = src.read()

print(image.shape)
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pip install shapely
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from shapely.geometry import Point, Polygon

# 创建点
point = Point(0, 0)

# 创建多边形
polygon = Polygon([(0, 0), (1, 1), (1, 0)])

# 检查点是否在多边形内
print(point.within(polygon))
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pip install pyproj
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import pyproj

# 定义两个坐标系统
crs_wgs84 = pyproj.CRS("EPSG:4326")  # WGS84
crs_utm32n = pyproj.CRS("EPSG:32632")  # UTM Zone 32N

# 创建转换器
transformer = pyproj.Transformer.from_crs(crs_wgs84, crs_utm32n, always_xy=True)

# 转换坐标
lon, lat = -71.160281, 42.258729
x, y = transformer.transform(lon, lat)

print(f"Transformed coordinates: ({x}, {y})")
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pip install descartes
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import geopandas as gpd
import matplotlib.pyplot as plt

# 读取 Shapefile
gdf = gpd.read_file("path/to/your/shp/file.shp")

# 绘制地图
ax = gdf.plot(figsize=(10, 10), edgecolor='k', facecolor='b')
plt.title("Sample Map")
plt.show()
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pip install rtree
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import rtree
import shapely.geometry

# 创建索引
index = rtree.index.Index()

# 添加几何对象
for i, point in enumerate([shapely.geometry.Point(x, y) for x, y in [(1, 1), (2, 2), (3, 3)]]):
    index.insert(i, point.bounds)

# 查询
query_point = shapely.geometry.Point(2.5, 2.5)
intersecting = list(index.intersection(query_point.buffer(0.5).bounds))

print(intersecting)
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pip install geopy
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from geopy.geocoders import Nominatim

geolocator = Nominatim(user_agent="geoapiExercises")

# 地理编码
location = geolocator.geocode("175 5th Avenue NYC")
print((location.latitude, location.longitude))

# 反向地理编码
reverse_location = geolocator.reverse((40.718225, -73.991074))
print(reverse_location.address)
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pip install folium
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import folium
import pandas as pd

# 读取数据
data = pd.read_csv("path/to/your/data.csv")
lat = data["Latitude"]
lon = data["Longitude"]

# 创建地图
m = folium.Map(location=[lat.mean(), lon.mean()], zoom_start=12)

# 添加标记
for lat, lon in zip(lat, lon):
    folium.Marker([lat, lon]).add_to(m)

# 显示地图
m.save("map.html")
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