LandScan 数据于1997年启动的一项研究计划，其目的是改进用于灾害后果评估的人口估算方法。与传统人口普查仅关注居住地不同，LandScan 提供全天（24小时平均）的人口分布模型，捕捉人口在一天内活动的空间范围。该数据基于地理空间科学、遥感技术和机器学习算法，通过多变量的区域模型，将行政边界内的人口普查数据高分辨率分解至像素级。LandScan Global 每年更新一次，覆盖全球范围，具有极高的空间分辨率和可靠性，适用于自然灾害、突发事件和其他多尺度地理分析。此外，为满足更高精度需求，美国范围内还推出了 LandScan USA，其模型包括人口的昼夜变化。1. 数据可通过官网申请下载，支持每年栅格数据获取。数据链接：https://landscan.ornl.gov/about2. 以下GEE代码可以导出每年的人口栅格数据，并生成年际变化折线图。同学们可根据研究需求调整区域和时间段。![]()
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var geometry = table;
Map.centerObject(geometry, 6);
var dataset = ee.ImageCollection('projects/sat-io/open-datasets/ORNL/LANDSCAN_GLOBAL');
var annualPopulation = ee.FeatureCollection([]);
var popcount_intervals = '<RasterSymbolizer>' + ' <ColorMap type="intervals" extended="false" >' + '<ColorMapEntry color="#CCCCCC" quantity="0" label="No Data"/>' + '<ColorMapEntry color="#FFFFBE" quantity="5" label="1-5"/>' + '<ColorMapEntry color="#FEFF73" quantity="25" label="6-25"/>' + '<ColorMapEntry color="#FEFF2C" quantity="50" label="26-50"/>' + '<ColorMapEntry color="#FFAA27" quantity="100" label="51-100"/>' + '<ColorMapEntry color="#FF6625" quantity="500" label="101-500"/>' + '<ColorMapEntry color="#FF0023" quantity="2500" label="501-2500"/>' + '<ColorMapEntry color="#CC001A" quantity="5000" label="2501-5000"/>' + '<ColorMapEntry color="#730009" quantity="185000" label="5001-185000"/>' + '</ColorMap>' + '</RasterSymbolizer>';
for (var i = 2000; i <= 2023; i++) { var startDate = ee.Date.fromYMD(i, 1, 1); var endDate = ee.Date.fromYMD(i, 12, 31);
var yearlyData = dataset.filterDate(startDate, endDate).mean(); var yearlyPopulation = yearlyData.clip(geometry).set({ 'year': i, 'system:time_start': startDate.millis() });
Map.addLayer(yearlyPopulation.sldStyle(popcount_intervals), {}, 'Population ' + i);
var meanPopulation = yearlyPopulation.reduceRegion({ reducer: ee.Reducer.mean(), geometry: geometry, scale: 1000, maxPixels: 1e13 }).get('b1');
var feature = ee.Feature(null, { 'year': i, 'Population_mean': meanPopulation });
annualPopulation = annualPopulation.merge(ee.FeatureCollection([feature]));
Export.image.toDrive({ image: yearlyPopulation, description: i + "_Population", fileNamePrefix: i + "_Population", folder: 'Annual_Population', scale: 1000, region: geometry, crs: "EPSG:4326", maxPixels: 1e13 });}
var chart = ui.Chart.feature.byFeature(annualPopulation, 'year', 'Population_mean') .setChartType('LineChart') .setOptions({ title: 'Annual Mean Population Count (2000-2023)', hAxis: {title: 'Year'}, vAxis: {title: 'Mean Population Count'}, lineWidth: 2, pointSize: 4, colors: ['black'] });
print(chart);
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