{"id":1112911,"date":"2025-01-08T17:42:55","date_gmt":"2025-01-08T09:42:55","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1112911.html"},"modified":"2025-01-08T17:42:58","modified_gmt":"2025-01-08T09:42:58","slug":"python%e5%a6%82%e4%bd%95%e8%af%bb%e5%8f%96%e6%a0%85%e6%a0%bc%e6%95%b0%e6%8d%ae%e7%9a%84%e8%b1%a1%e5%85%83%e5%80%bc","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1112911.html","title":{"rendered":"python\u5982\u4f55\u8bfb\u53d6\u6805\u683c\u6570\u636e\u7684\u8c61\u5143\u503c"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25074733\/2f12f745-1fcf-49f1-8f16-c54a90cdd8ed.webp\" alt=\"python\u5982\u4f55\u8bfb\u53d6\u6805\u683c\u6570\u636e\u7684\u8c61\u5143\u503c\" \/><\/p>\n<p><p> <strong>Python\u8bfb\u53d6\u6805\u683c\u6570\u636e\u7684\u8c61\u5143\u503c\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528GDAL\u5e93\u3001Rasterio\u5e93\u4ee5\u53ca\u4f7f\u7528NumPy\u5e93\u7684\u6570\u7ec4\u64cd\u4f5c\u3002<\/strong>\u8fd9\u51e0\u79cd\u65b9\u6cd5\u5404\u6709\u4f18\u52a3\uff0c\u672c\u6587\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u65b9\u6cd5\u6765\u8bfb\u53d6\u6805\u683c\u6570\u636e\u7684\u8c61\u5143\u503c\uff0c\u5176\u4e2d\uff0cRasterio\u5e93\u7531\u4e8e\u5176\u7b80\u5355\u6613\u7528\u4e14\u529f\u80fd\u5f3a\u5927\uff0c\u8f83\u4e3a\u63a8\u8350\u4f7f\u7528\u3002<\/p>\n<\/p>\n<p><p>\u4e00\u3001\u4f7f\u7528GDAL\u5e93\u8bfb\u53d6\u6805\u683c\u6570\u636e<\/p>\n<\/p>\n<p><p>GDAL\uff08Geospatial Data Abstraction Library\uff09\u662f\u4e00\u4e2a\u7528\u4e8e\u8bfb\u53d6\u548c\u5199\u5165\u5730\u7406\u7a7a\u95f4\u6570\u636e\u7684\u5f00\u6e90\u5e93\u3002\u5b83\u652f\u6301\u591a\u79cd\u6805\u683c\u6570\u636e\u683c\u5f0f\uff0c\u5982GeoTIFF\u3001HDF\u7b49\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528GDAL\u5e93\u8bfb\u53d6\u6805\u683c\u6570\u636e\u8c61\u5143\u503c\u7684\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5GDAL\u5e93<\/li>\n<\/ol>\n<p><p>\u5728\u4f7f\u7528GDAL\u5e93\u4e4b\u524d\uff0c\u9700\u8981\u5148\u5b89\u88c5\u8be5\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u901a\u8fc7pip\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install gdal<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u5bfc\u5165GDAL\u5e93\u5e76\u6253\u5f00\u6805\u683c\u6570\u636e\u6587\u4ef6<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\">from osgeo import gdal<\/p>\n<h2><strong>\u6253\u5f00\u6805\u683c\u6570\u636e\u6587\u4ef6<\/strong><\/h2>\n<p>dataset = gdal.Open(&#39;path_to_your_raster_file.tif&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"3\">\n<li>\u83b7\u53d6\u6805\u683c\u6570\u636e\u7684\u57fa\u672c\u4fe1\u606f<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\"># \u83b7\u53d6\u6805\u683c\u6570\u636e\u7684\u5bbd\u5ea6\u548c\u9ad8\u5ea6<\/p>\n<p>width = dataset.RasterXSize<\/p>\n<p>height = dataset.RasterYSize<\/p>\n<h2><strong>\u83b7\u53d6\u6805\u683c\u6570\u636e\u7684\u6ce2\u6bb5\u6570<\/strong><\/h2>\n<p>band_count = dataset.RasterCount<\/p>\n<h2><strong>\u83b7\u53d6\u6805\u683c\u6570\u636e\u7684\u5730\u7406\u53d8\u6362\u4fe1\u606f\u548c\u6295\u5f71\u4fe1\u606f<\/strong><\/h2>\n<p>geotransform = dataset.GetGeoTransform()<\/p>\n<p>projection = dataset.GetProjection()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"4\">\n<li>\u8bfb\u53d6\u6805\u683c\u6570\u636e\u7684\u8c61\u5143\u503c<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\"># \u83b7\u53d6\u7b2c\u4e00\u4e2a\u6ce2\u6bb5<\/p>\n<p>band = dataset.GetRasterBand(1)<\/p>\n<h2><strong>\u8bfb\u53d6\u6ce2\u6bb5\u6570\u636e<\/strong><\/h2>\n<p>data = band.ReadAsArray()<\/p>\n<h2><strong>\u6253\u5370\u8c61\u5143\u503c<\/strong><\/h2>\n<p>print(data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u4e0a\u8ff0\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528GDAL\u5e93\u8bfb\u53d6\u6805\u683c\u6570\u636e\u7684\u8c61\u5143\u503c\u3002GDAL\u5e93\u529f\u80fd\u5f3a\u5927\uff0c\u4f46\u5176\u63a5\u53e3\u76f8\u5bf9\u590d\u6742\uff0c\u5bf9\u4e8e\u521d\u5b66\u8005\u6765\u8bf4\u53ef\u80fd\u4e0d\u592a\u53cb\u597d\u3002<\/p>\n<\/p>\n<p><p>\u4e8c\u3001\u4f7f\u7528Rasterio\u5e93\u8bfb\u53d6\u6805\u683c\u6570\u636e<\/p>\n<\/p>\n<p><p>Rasterio\u662f\u4e00\u4e2a\u7528\u4e8e\u8bfb\u53d6\u548c\u5199\u5165\u5730\u7406\u7a7a\u95f4\u6805\u683c\u6570\u636e\u7684Python\u5e93\uff0c\u57fa\u4e8eGDAL\u5e93\u6784\u5efa\uff0c\u4f46\u5176\u63a5\u53e3\u66f4\u52a0\u7b80\u6d01\u6613\u7528\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528Rasterio\u5e93\u8bfb\u53d6\u6805\u683c\u6570\u636e\u8c61\u5143\u503c\u7684\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5Rasterio\u5e93<\/li>\n<\/ol>\n<p><p>\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u901a\u8fc7pip\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install rasterio<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u5bfc\u5165Rasterio\u5e93\u5e76\u6253\u5f00\u6805\u683c\u6570\u636e\u6587\u4ef6<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\">import rasterio<\/p>\n<h2><strong>\u6253\u5f00\u6805\u683c\u6570\u636e\u6587\u4ef6<\/strong><\/h2>\n<p>with rasterio.open(&#39;path_to_your_raster_file.tif&#39;) as dataset:<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"3\">\n<li>\u83b7\u53d6\u6805\u683c\u6570\u636e\u7684\u57fa\u672c\u4fe1\u606f<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\"># \u83b7\u53d6\u6805\u683c\u6570\u636e\u7684\u5bbd\u5ea6\u548c\u9ad8\u5ea6<\/p>\n<p>width = dataset.width<\/p>\n<p>height = dataset.height<\/p>\n<h2><strong>\u83b7\u53d6\u6805\u683c\u6570\u636e\u7684\u6ce2\u6bb5\u6570<\/strong><\/h2>\n<p>band_count = dataset.count<\/p>\n<h2><strong>\u83b7\u53d6\u6805\u683c\u6570\u636e\u7684\u5730\u7406\u53d8\u6362\u4fe1\u606f\u548c\u6295\u5f71\u4fe1\u606f<\/strong><\/h2>\n<p>transform = dataset.transform<\/p>\n<p>crs = dataset.crs<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"4\">\n<li>\u8bfb\u53d6\u6805\u683c\u6570\u636e\u7684\u8c61\u5143\u503c<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\"># \u8bfb\u53d6\u7b2c\u4e00\u4e2a\u6ce2\u6bb5\u7684\u6570\u636e<\/p>\n<p>data = dataset.read(1)<\/p>\n<h2><strong>\u6253\u5370\u8c61\u5143\u503c<\/strong><\/h2>\n<p>print(data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u4e0a\u8ff0\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Rasterio\u5e93\u8bfb\u53d6\u6805\u683c\u6570\u636e\u7684\u8c61\u5143\u503c\u3002\u76f8\u6bd4\u4e8eGDAL\u5e93\uff0cRasterio\u5e93\u7684\u63a5\u53e3\u66f4\u52a0\u7b80\u6d01\uff0c\u4f7f\u7528\u8d77\u6765\u66f4\u52a0\u65b9\u4fbf\u3002<\/p>\n<\/p>\n<p><p>\u4e09\u3001\u4f7f\u7528NumPy\u5e93\u8fdb\u884c\u6570\u7ec4\u64cd\u4f5c<\/p>\n<\/p>\n<p><p>\u5728\u8bfb\u53d6\u6805\u683c\u6570\u636e\u7684\u8c61\u5143\u503c\u540e\uff0c\u6211\u4eec\u901a\u5e38\u9700\u8981\u8fdb\u884c\u4e00\u4e9b\u6570\u7ec4\u64cd\u4f5c\u6765\u5904\u7406\u6570\u636e\u3002NumPy\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u79d1\u5b66\u8ba1\u7b97\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u7ec4\u64cd\u4f5c\u51fd\u6570\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u6570\u7ec4\u64cd\u4f5c\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5NumPy\u5e93<\/li>\n<\/ol>\n<p><p>\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u901a\u8fc7pip\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u5bfc\u5165NumPy\u5e93\u5e76\u8fdb\u884c\u6570\u7ec4\u64cd\u4f5c<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u8ba1\u7b97\u8c61\u5143\u503c\u7684\u6700\u5927\u503c\u3001\u6700\u5c0f\u503c\u548c\u5e73\u5747\u503c<\/strong><\/h2>\n<p>max_value = np.max(data)<\/p>\n<p>min_value = np.min(data)<\/p>\n<p>mean_value = np.mean(data)<\/p>\n<h2><strong>\u6253\u5370\u7ed3\u679c<\/strong><\/h2>\n<p>print(f&#39;Max value: {max_value}&#39;)<\/p>\n<p>print(f&#39;Min value: {min_value}&#39;)<\/p>\n<p>print(f&#39;Mean value: {mean_value}&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"3\">\n<li>\u8fdb\u884c\u6570\u7ec4\u7684\u57fa\u672c\u8fd0\u7b97<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\"># \u5c06\u8c61\u5143\u503c\u4e58\u4ee5\u4e00\u4e2a\u5e38\u6570<\/p>\n<p>scaled_data = data * 2<\/p>\n<h2><strong>\u5c06\u8c61\u5143\u503c\u52a0\u4e0a\u4e00\u4e2a\u5e38\u6570<\/strong><\/h2>\n<p>offset_data = data + 10<\/p>\n<h2><strong>\u8ba1\u7b97\u8c61\u5143\u503c\u7684\u5e73\u65b9\u6839<\/strong><\/h2>\n<p>sqrt_data = np.sqrt(data)<\/p>\n<h2><strong>\u6253\u5370\u7ed3\u679c<\/strong><\/h2>\n<p>print(scaled_data)<\/p>\n<p>print(offset_data)<\/p>\n<p>print(sqrt_data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u4e0a\u8ff0\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u5bf9\u8bfb\u53d6\u5230\u7684\u6805\u683c\u6570\u636e\u8c61\u5143\u503c\u8fdb\u884c\u5404\u79cd\u6570\u7ec4\u64cd\u4f5c\uff0c\u4ee5\u6ee1\u8db3\u6570\u636e\u5904\u7406\u7684\u9700\u6c42\u3002<\/p>\n<\/p>\n<p><p>\u56db\u3001\u5904\u7406\u591a\u6ce2\u6bb5\u6805\u683c\u6570\u636e<\/p>\n<\/p>\n<p><p>\u6805\u683c\u6570\u636e\u901a\u5e38\u5305\u542b\u591a\u4e2a\u6ce2\u6bb5\uff0c\u4f8b\u5982\u536b\u661f\u5f71\u50cf\u53ef\u80fd\u5305\u542b\u7ea2\u3001\u7eff\u3001\u84dd\u3001\u8fd1\u7ea2\u5916\u7b49\u591a\u4e2a\u6ce2\u6bb5\u3002\u4ee5\u4e0b\u662f\u5904\u7406\u591a\u6ce2\u6bb5\u6805\u683c\u6570\u636e\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<ol>\n<li>\u8bfb\u53d6\u591a\u6ce2\u6bb5\u6570\u636e<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\">with rasterio.open(&#39;path_to_your_raster_file.tif&#39;) as dataset:<\/p>\n<p>    # \u8bfb\u53d6\u6240\u6709\u6ce2\u6bb5\u7684\u6570\u636e<\/p>\n<p>    data = dataset.read()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u83b7\u53d6\u7279\u5b9a\u6ce2\u6bb5\u7684\u6570\u636e<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\"># \u8bfb\u53d6\u7b2c\u4e00\u4e2a\u6ce2\u6bb5\u7684\u6570\u636e<\/p>\n<p>band1 = data[0]<\/p>\n<h2><strong>\u8bfb\u53d6\u7b2c\u4e8c\u4e2a\u6ce2\u6bb5\u7684\u6570\u636e<\/strong><\/h2>\n<p>band2 = data[1]<\/p>\n<h2><strong>\u6253\u5370\u7ed3\u679c<\/strong><\/h2>\n<p>print(band1)<\/p>\n<p>print(band2)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"3\">\n<li>\u8fdb\u884c\u591a\u6ce2\u6bb5\u6570\u636e\u7684\u7ec4\u5408\u548c\u8fd0\u7b97<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\"># \u8ba1\u7b97\u5f52\u4e00\u5316\u690d\u88ab\u6307\u6570\uff08NDVI\uff09<\/p>\n<h2><strong>NDVI = (NIR - RED) \/ (NIR + RED)<\/strong><\/h2>\n<p>nir_band = data[3]<\/p>\n<p>red_band = data[0]<\/p>\n<p>ndvi = (nir_band - red_band) \/ (nir_band + red_band)<\/p>\n<h2><strong>\u6253\u5370\u7ed3\u679c<\/strong><\/h2>\n<p>print(ndvi)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u4e0a\u8ff0\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u5904\u7406\u591a\u6ce2\u6bb5\u6805\u683c\u6570\u636e\uff0c\u5e76\u8fdb\u884c\u6ce2\u6bb5\u4e4b\u95f4\u7684\u7ec4\u5408\u548c\u8fd0\u7b97\uff0c\u4ee5\u63d0\u53d6\u6709\u7528\u7684\u4fe1\u606f\u3002<\/p>\n<\/p>\n<p><p>\u4e94\u3001\u53ef\u89c6\u5316\u6805\u683c\u6570\u636e<\/p>\n<\/p>\n<p><p>\u5728\u5904\u7406\u6805\u683c\u6570\u636e\u540e\uff0c\u6211\u4eec\u901a\u5e38\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u53ef\u89c6\u5316\uff0c\u4ee5\u4fbf\u66f4\u76f4\u89c2\u5730\u7406\u89e3\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528Matplotlib\u5e93\u8fdb\u884c\u6805\u683c\u6570\u636e\u53ef\u89c6\u5316\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5Matplotlib\u5e93<\/li>\n<\/ol>\n<p><p>\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u901a\u8fc7pip\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install matplotlib<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u5bfc\u5165Matplotlib\u5e93\u5e76\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\">import matplotlib.pyplot as plt<\/p>\n<h2><strong>\u53ef\u89c6\u5316\u5355\u6ce2\u6bb5\u6570\u636e<\/strong><\/h2>\n<p>plt.imshow(data[0], cmap=&#39;gray&#39;)<\/p>\n<p>plt.colorbar()<\/p>\n<p>plt.title(&#39;Band 1&#39;)<\/p>\n<p>plt.show()<\/p>\n<h2><strong>\u53ef\u89c6\u5316\u591a\u6ce2\u6bb5\u6570\u636e\uff08RGB\u5408\u6210\uff09<\/strong><\/h2>\n<p>rgb_data = np.dstack((data[0], data[1], data[2]))<\/p>\n<p>plt.imshow(rgb_data)<\/p>\n<p>plt.title(&#39;RGB Composite&#39;)<\/p>\n<p>plt.show()<\/p>\n<h2><strong>\u53ef\u89c6\u5316NDVI\u6570\u636e<\/strong><\/h2>\n<p>plt.imshow(ndvi, cmap=&#39;RdYlGn&#39;)<\/p>\n<p>plt.colorbar()<\/p>\n<p>plt.title(&#39;NDVI&#39;)<\/p>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u4e0a\u8ff0\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Matplotlib\u5e93\u5bf9\u6805\u683c\u6570\u636e\u8fdb\u884c\u53ef\u89c6\u5316\uff0c\u4ee5\u4fbf\u66f4\u76f4\u89c2\u5730\u7406\u89e3\u548c\u5206\u6790\u6570\u636e\u3002<\/p>\n<\/p>\n<p><p>\u603b\u7ed3<\/p>\n<\/p>\n<p><p>\u672c\u6587\u8be6\u7ec6\u4ecb\u7ecd\u4e86<strong>\u5982\u4f55\u4f7f\u7528Python\u8bfb\u53d6\u6805\u683c\u6570\u636e\u7684\u8c61\u5143\u503c<\/strong>\uff0c\u5305\u62ec\u4f7f\u7528GDAL\u5e93\u3001Rasterio\u5e93\u4ee5\u53caNumPy\u5e93\u7684\u6570\u7ec4\u64cd\u4f5c\u3002\u6b64\u5916\uff0c\u672c\u6587\u8fd8\u4ecb\u7ecd\u4e86\u5904\u7406\u591a\u6ce2\u6bb5\u6805\u683c\u6570\u636e\u548c\u5bf9\u6570\u636e\u8fdb\u884c\u53ef\u89c6\u5316\u7684\u65b9\u6cd5\u3002\u901a\u8fc7\u8fd9\u4e9b\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u66f4\u597d\u5730\u7406\u89e3\u548c\u5904\u7406\u6805\u683c\u6570\u636e\uff0c\u4ee5\u6ee1\u8db3\u5b9e\u9645\u5e94\u7528\u7684\u9700\u6c42\u3002<\/p>\n<\/p>\n<p><p>\u5e0c\u671b\u672c\u6587\u5bf9\u60a8\u6709\u6240\u5e2e\u52a9\uff0c\u5982\u679c\u6709\u4efb\u4f55\u95ee\u9898\u6216\u5efa\u8bae\uff0c\u8bf7\u968f\u65f6\u4e0e\u6211\u8054\u7cfb\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u8bfb\u53d6\u6805\u683c\u6570\u636e\u7684\u8c61\u5143\u503c\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u8bfb\u53d6\u6805\u683c\u6570\u636e\u7684\u8c61\u5143\u503c\u901a\u5e38\u9700\u8981\u4f7f\u7528\u4e13\u95e8\u7684\u5e93\uff0c\u5982Rasterio\u6216GDAL\u3002\u8fd9\u4e9b\u5e93\u80fd\u591f\u5904\u7406\u591a\u79cd\u6805\u683c\u6570\u636e\u683c\u5f0f\uff0c\u5e76\u63d0\u4f9b\u7b80\u5355\u7684API\u6765\u8bbf\u95ee\u8c61\u5143\u503c\u3002\u901a\u8fc7\u5b89\u88c5\u8fd9\u4e9b\u5e93\u5e76\u4f7f\u7528\u76f8\u5e94\u7684\u51fd\u6570\uff0c\u4f60\u53ef\u4ee5\u8f7b\u677e\u63d0\u53d6\u6307\u5b9a\u5750\u6807\u7684\u8c61\u5143\u503c\u3002<\/p>\n<p><strong>\u8bfb\u53d6\u6805\u683c\u6570\u636e\u65f6\u9700\u8981\u6ce8\u610f\u54ea\u4e9b\u6570\u636e\u683c\u5f0f\uff1f<\/strong><br \/>\u6805\u683c\u6570\u636e\u53ef\u4ee5\u5b58\u50a8\u4e3a\u591a\u79cd\u683c\u5f0f\uff0c\u5982GeoTIFF\u3001JPEG\u3001PNG\u7b49\u3002\u5728\u9009\u62e9\u8bfb\u53d6\u65b9\u6cd5\u65f6\uff0c\u786e\u4fdd\u4f7f\u7528\u7684\u5e93\u652f\u6301\u8be5\u683c\u5f0f\u3002GeoTIFF\u683c\u5f0f\u56e0\u5176\u5305\u542b\u5730\u7406\u4fe1\u606f\u800c\u88ab\u5e7f\u6cdb\u4f7f\u7528\uff0c\u9002\u5408\u5904\u7406\u5730\u7406\u7a7a\u95f4\u5206\u6790\u3002<\/p>\n<p><strong>\u5728\u5904\u7406\u6805\u683c\u6570\u636e\u65f6\u5982\u4f55\u63d0\u9ad8\u8bfb\u53d6\u6548\u7387\uff1f<\/strong><br \/>\u5f53\u5904\u7406\u5927\u89c4\u6a21\u6805\u683c\u6570\u636e\u65f6\uff0c\u53ef\u4ee5\u8003\u8651\u4f7f\u7528\u5206\u5757\u8bfb\u53d6\u7684\u65b9\u6cd5\u3002\u8fd9\u79cd\u65b9\u5f0f\u4e0d\u4ec5\u53ef\u4ee5\u51cf\u5c11\u5185\u5b58\u4f7f\u7528\uff0c\u8fd8\u80fd\u63d0\u9ad8\u8bfb\u53d6\u901f\u5ea6\u3002\u6b64\u5916\uff0c\u4f7f\u7528\u5408\u9002\u7684\u6570\u636e\u7c7b\u578b\u6765\u5b58\u50a8\u548c\u5904\u7406\u8c61\u5143\u503c\uff0c\u4f8b\u5982\u4f7f\u7528numpy\u6570\u7ec4\uff0c\u6709\u52a9\u4e8e\u63d0\u5347\u6027\u80fd\u3002<\/p>\n<p><strong>\u662f\u5426\u53ef\u4ee5\u901a\u8fc7Python\u8bfb\u53d6\u7f51\u7edc\u4e0a\u7684\u6805\u683c\u6570\u636e\uff1f<\/strong><br \/>\u662f\u7684\uff0cPython\u80fd\u591f\u4ece\u7f51\u7edc\u4e0a\u8bfb\u53d6\u6805\u683c\u6570\u636e\u3002\u4f7f\u7528Rasterio\u6216\u5176\u4ed6\u5e93\u65f6\uff0c\u53ef\u4ee5\u76f4\u63a5\u63d0\u4f9bURL\u4f5c\u4e3a\u8f93\u5165\u3002\u8fd9\u79cd\u65b9\u6cd5\u975e\u5e38\u9002\u5408\u5904\u7406\u5f00\u653e\u6570\u636e\u96c6\u6216\u4e91\u5b58\u50a8\u4e2d\u7684\u6805\u683c\u6587\u4ef6\uff0c\u65b9\u4fbf\u7528\u6237\u8fdb\u884c\u8fdc\u7a0b\u5206\u6790\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u8bfb\u53d6\u6805\u683c\u6570\u636e\u7684\u8c61\u5143\u503c\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528GDAL\u5e93\u3001Rasterio\u5e93\u4ee5\u53ca\u4f7f\u7528NumPy\u5e93\u7684\u6570\u7ec4\u64cd\u4f5c\u3002\u8fd9 [&hellip;]","protected":false},"author":3,"featured_media":1112917,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1112911"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1112911"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1112911\/revisions"}],"predecessor-version":[{"id":1112918,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1112911\/revisions\/1112918"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1112917"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1112911"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1112911"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1112911"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}