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+/**
+ * Sentinel-2 哨兵二号数据下载 —— 以下载 2025 年湖北省无云RGB三波段影像为例
+ *
+ * GEE 最新代码: https://code.earthengine.google.com/15b61c853c281deb3ef8fc416224c405
+ *
+ * @author CVEO Team
+ * @date 2025-12-08
+ *
+ * 1. 加载 Sentinel-2 数据与 Cloud Score+ 云掩膜
+ * 2. 合成年度无云影像
+ * 3. 导出COG云优化并填补缺失值的GeoTIFF影像分块
+ */
+
+// 加载研究区域和影像
+var region_name = "湖北省";
+var region_name_en = "Hubei";
+var region = allCites.filter(ee.Filter.eq("省", region_name));
+var year = 2025;
+var start_date = year + "-01-01";
+var end_date = year + "-12-31";
+var cloud_threshold = 5; // 5% 云量
+// Use 'cs' or 'cs_cdf', depending on your use case; see docs for guidance.
+var QA_BAND = "cs_cdf";
+// The threshold for masking; values between 0.50 and 0.65 generally work well.
+// Higher values will remove thin clouds, haze & cirrus shadows.
+var CLEAR_THRESHOLD = 0.8;
+// Sentinel-2的B8A波段(20m)可能更适合代表近红外波段
+// var s2Bands = ["B2", "B3", "B4", "B8", "B11", "B12"];
+var s2Bands = ["B2", "B3", "B4", "B8A", "B11", "B12"];
+var commonBands = ["Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2"];
+var region_geo = region.geometry();
+var bounds = region_geo.bounds();
+var common_filter = ee.Filter.and(
+  ee.Filter.bounds(bounds),
+  ee.Filter.date(start_date, end_date)
+);
+
+/**
+ * 基于 Cloud Score+ 云掩膜
+ * @param {ee.Image} image Sentinel-2 image
+ * @return {ee.Image} cloud masked Sentinel-2 image
+ */
+function maskS2cloudsByCS(image) {
+  var cloudMask = image.select(QA_BAND).gte(CLEAR_THRESHOLD);
+  image = image.updateMask(cloudMask);
+  return image
+    .copyProperties(image)
+    .copyProperties(image, ["system:time_start", "system:index", "system:id"]);
+}
+
+// 加载Sentinel-2 L2A数据与Cloud Score+云掩膜
+// Cloud Score+ image collection.
+// Note Cloud Score+ is produced from Sentinel-2 level 1C data and can be applied to either L1C or L2A collections.
+var S2csPlus = ee.ImageCollection("GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED");
+var S2dataset = ee
+  .ImageCollection("COPERNICUS/S2_SR_HARMONIZED")
+  .filter(common_filter)
+  .filter(ee.Filter.lt("CLOUDY_PIXEL_PERCENTAGE", cloud_threshold))
+  .select(s2Bands, commonBands)
+  .linkCollection(S2csPlus, [QA_BAND])
+  .map(maskS2cloudsByCS);
+var s2_img = ee.Image(S2dataset.median());
+var s2_img_rgb = s2_img.select(["Red", "Green", "Blue"]);
+var s2_img_frgb = s2_img.select(["NIR", "Red", "Green"]);
+
+var true_rgb_vis = {
+  bands: ["Red", "Green", "Blue"],
+  min: 0.0,
+  max: 3000,
+};
+
+var false_rgb_vis = {
+  min: 0.0,
+  max: 4000,
+  gamma: 1.4,
+  bands: ["NIR", "Red", "Green"],
+};
+
+var styling = {
+  color: "red",
+  fillColor: "00000000",
+};
+
+Map.centerObject(region, 7);
+Map.addLayer(s2_img_frgb, false_rgb_vis, year + " Sentinel-2 False RGB", false);
+Map.addLayer(s2_img_rgb, true_rgb_vis, year + " Sentinel-2 True RGB");
+Map.addLayer(region.style(styling), {}, region_name);
+
+// 导出裁剪处理后的Sentinel-2 RGB影像
+var fileName = region_name_en + "_Sentinel-2_" + year;
+// 区域过大, 需要先将 s2_img 划分为四块网格分开下载
+var coords = ee.List(bounds.coordinates().get(0));
+
+var minX = ee.Number(ee.List(coords.get(0)).get(0));
+var minY = ee.Number(ee.List(coords.get(0)).get(1));
+var maxX = ee.Number(ee.List(coords.get(2)).get(0));
+var maxY = ee.Number(ee.List(coords.get(2)).get(1));
+
+var midX = minX.add(maxX).divide(2);
+var midY = minY.add(maxY).divide(2);
+
+var grid1 = ee.Geometry.Rectangle([minX, minY, midX, midY]);
+var grid2 = ee.Geometry.Rectangle([midX, minY, maxX, midY]);
+var grid3 = ee.Geometry.Rectangle([minX, midY, midX, maxY]);
+var grid4 = ee.Geometry.Rectangle([midX, midY, maxX, maxY]);
+
+var grids = [grid1, grid2, grid3, grid4];
+
+for (var i = 0; i < grids.length; i++) {
+  var grid_region = grids[i];
+  // 明确设置数据类型为Float32, 否则默认类型为Float64, 会占用更多内存
+  // 并对缺失值进行填充, 否则默认为nan不便于后续本地处理
+  var clipped_img = s2_img_rgb.clip(grid_region).toFloat().unmask(-9999.0);
+  var grid_fileName = fileName + "_grid_" + (i + 1);
+  Export.image.toDrive({
+    image: clipped_img,
+    description: grid_fileName,
+    folder: "Sentinel-2",
+    region: grid_region,
+    scale: 10,
+    maxPixels: 1e13, // GEE 最多支持 1e8 像素, 当超过时会自动分块
+    fileFormat: "GeoTIFF",
+    // 导出COG云优化的GeoTIFF影像, 并明确设置缺失值为-9999.0
+    formatOptions: {
+      cloudOptimized: true,
+      noData: -9999.0,
+    },
+  });
+}