174 lines
5.8 KiB
JavaScript
174 lines
5.8 KiB
JavaScript
/**
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* Landsat 系列地表温度 (LST) 数据下载 —— 以年平均温度处理下载为例
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*
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* @author CVEO Team
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* @date 2026-01-15
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*
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* 1. 加载 Landsat-8, Landsat-9 SR 数据
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* 2. 合并 Landsat-8, Landsat-9 LST 数据
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* 3. 合成年度平均 Landsat LST 数据
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* 4. 导出 COG 云优化并填补缺失值的 GeoTIFF 影像 (大区域 GEE 自动分块下载)
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*/
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// 加载研究区域和影像
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var region_name = "应城市";
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var region_name_en = "Yingcheng";
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var region = Yingcheng;
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var crs = "EPSG:4526";
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// var region_name = "保康县";
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// var region_name_en = "Baokang";
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// var region = Baokang;
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// var crs = "EPSG:4525";
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var start_year = 2021;
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var end_year = 2025;
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var start_date = start_year + "-01-01";
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var end_date = end_year + "-12-31";
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var cloud_threshold = 90; // 最大云量阈值
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var LansatBands = ["ST_B10"];
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var commonBands = ["LST"];
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var region_geo = region.geometry();
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var bounds = region_geo.bounds();
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var common_filter = ee.Filter.and(
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ee.Filter.bounds(bounds),
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ee.Filter.date(start_date, end_date)
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);
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/**
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* Applies scaling factors.
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* @param {ee.Image} image Landsat SR image
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* @returns {ee.Image} Landsat SR image with scaled bands
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*/
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function applyScaleFactors(image) {
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var opticalBands = image.select("SR_B.").multiply(0.0000275).add(-0.2);
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var thermalBands = image.select("ST_B.*").multiply(0.00341802).add(149.0);
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return image
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.addBands(opticalBands, null, true)
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.addBands(thermalBands, null, true);
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}
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/**
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* 开尔文转摄氏度
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* @param {ee.Image} image Landsat LST image
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* @returns {ee.Image} Landsat LST image in Celsius
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*/
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function kelvinToCelsius(image) {
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return ee.Image(image.expression("B1 - 273.15", { B1: image.select(0) }))
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.rename("LST")
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.copyProperties(image)
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.copyProperties(image, ["system:time_start", "system:index", "system:id"]);
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}
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/**
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* Function to mask clouds using the Landsat QA_PIXEL and QA_RADSAT bands
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* @param {ee.Image} image Landsat SR image
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* @return {ee.Image} cloud masked and saturated Landsat SR image
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*/
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function maskLandsatclouds(image) {
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var qa = image.select("QA_PIXEL");
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var qa_radsat = image.select("QA_RADSAT");
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// Bits 3 and 4 are cloud and cloud shadow, respectively.
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var cloudBitMask = 1 << 3;
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var shadowBitMask = 1 << 4;
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// Both flags should be set to zero, indicating clear conditions.
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var mask = qa.bitwiseAnd(cloudBitMask).eq(0)
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.and(qa.bitwiseAnd(shadowBitMask).eq(0))
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.and(qa_radsat.eq(0));
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image = image.updateMask(mask);
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return image
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.copyProperties(image)
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.copyProperties(image, ["system:time_start", "system:index", "system:id"]);
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}
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// 加载 Landsat-8, Landsat-9 SR 数据
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var L8dataset = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2")
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.filter(common_filter)
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.filter(ee.Filter.lt("CLOUD_COVER", cloud_threshold));
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print(start_date + " - " + end_date + " Landsat-8 SR dataset", L8dataset);
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var L9dataset = ee.ImageCollection("LANDSAT/LC09/C02/T1_L2")
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.filter(common_filter)
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.filter(ee.Filter.lt("CLOUD_COVER", cloud_threshold));
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print(start_date + " - " + end_date + " Landsat-9 SR dataset", L9dataset);
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// 合并 Landsat-8, Landsat-9 LST 数据
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var LSTdataset = L8dataset.merge(L9dataset)
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.map(applyScaleFactors)
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.map(maskLandsatclouds)
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.select(LansatBands, commonBands)
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.map(kelvinToCelsius);
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print(start_date + " - " + end_date + " Landsat-8,9 LST dataset", LSTdataset);
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// 合成年度平均 Landsat LST 数据
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var years = ee.List.sequence(start_year, end_year);
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var months = ee.List.sequence(1, 12);
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var yearlyLST = ee.ImageCollection.fromImages(
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years.map(function (y) {
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return ee.ImageCollection.fromImages(
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months.map(function (m) {
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return LSTdataset
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.filter(ee.Filter.calendarRange(y, y, "year"))
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.filter(ee.Filter.calendarRange(m, m, "month"))
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.mean()
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.clip(bounds)
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.set("month", m)
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.set("year", y);
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})
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).mean().set("year", y);
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})
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);
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if (start_year == end_year) {
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var year_str = start_year;
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} else {
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var year_str = start_year + "-" + end_year;
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}
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print(year_str + " Annual Mean Landsat LST dataset", yearlyLST);
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var total_mean_LST = LSTdataset.select("LST").mean();
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print(year_str + " Total Year Mean Landsat LST Histogram", ui.Chart.image.histogram(total_mean_LST, region, 100, 258));
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var annual_mean_LST = yearlyLST.select("LST").mean();
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print(year_str + " Annual Mean Landsat LST Histogram", ui.Chart.image.histogram(annual_mean_LST, region, 100, 258));
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var lst_vis = {
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min: 2,
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max: 40,
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palette: [
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'040274', '040281', '0502a3', '0502b8', '0502ce', '0502e6',
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'0602ff', '235cb1', '307ef3', '269db1', '30c8e2', '32d3ef',
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'3be285', '3ff38f', '86e26f', '3ae237', 'b5e22e', 'd6e21f',
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'fff705', 'ffd611', 'ffb613', 'ff8b13', 'ff6e08', 'ff500d',
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'ff0000', 'de0101', 'c21301', 'a71001', '911003'
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],
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};
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var styling = {
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color: "blue",
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fillColor: "00000000",
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};
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Map.centerObject(region, 10);
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Map.addLayer(total_mean_LST, lst_vis, year_str + " Landsat Total Year Mean LST");
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Map.addLayer(annual_mean_LST, lst_vis, year_str + " Landsat Annual Mean LST");
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Map.addLayer(region.style(styling), {}, region_name);
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// 导出合并后的影像
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// 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
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// 并对缺失值进行填充, 否则默认为nan不便于后续本地处理
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var processed_img = annual_mean_LST.toFloat().unmask(-9999.0);
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print("Start exporting " + year_str + "Yearly Mean LST image (" + crs + ")", processed_img);
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Export.image.toDrive({
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image: processed_img,
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description: region_name_en + "_LST_" + year_str,
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folder: "LST",
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region: region, // 添加后会自动裁剪
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scale: 30,
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crs: crs,
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maxPixels: 1e13, // GEE 最多支持 1e8 像素, 当超过时会自动分块
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fileFormat: "GeoTIFF",
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// 导出COG云优化的GeoTIFF影像, 并明确设置缺失值为-9999.0
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formatOptions: {
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cloudOptimized: true,
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noData: -9999.0,
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},
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});
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