GEE | 多源蒸散发ET年数据对比分析

var ET_region = table;
var collectionFLDAS = ee.ImageCollection("NASA/FLDAS/NOAH01/C/GL/M/V001")  .filterDate('2001-01-01', '2020-12-31')  .select('Evap_tavg');
var collectionMODIS = ee.ImageCollection("MODIS/006/MOD16A2")  .filterDate('2001-01-01', '2020-12-31')  .select('ET');
var collectionPML = ee.ImageCollection("CAS/IGSNRR/PML/V2_v018")  .filterDate('2001-01-01', '2020-12-31');
var collectionTerraClimate = ee.ImageCollection("IDAHO_EPSCOR/TERRACLIMATE")  .filterDate('2001-01-01', '2020-12-31')  .select('aet');
function getYearlyET(collection, datasetName, bandName, factor) {  var range = collection.reduceColumns(ee.Reducer.minMax(), ['system:time_start']);  var diff = ee.Date(range.get('max')).difference(ee.Date(range.get('min')), 'year');    var yearlyData = ee.List.sequence(0, diff).map(function(n) {    var start = ee.Date(range.get('min')).advance(n, 'year');    var end = start.advance(1, 'year');        var yearlyImage = collection      .filterDate(start, end)      .sum()      .multiply(factor)      .set('system:time_start', start);        var year = ee.Date(yearlyImage.get('system:time_start')).get('year');    var meanValue = yearlyImage.reduceRegion({      reducer: ee.Reducer.mean(),      geometry: ET_region,      scale: 50000    }).get(bandName);        return ee.Feature(null, {      'Year': year,      'Dataset': datasetName,      'ET (mm/year)': meanValue    });  });    return ee.List(yearlyData);}
var yearlyFLDAS = getYearlyET(collectionFLDAS, 'FLDAS', 'Evap_tavg', 24 * 60 * 60 * 30);var yearlyMODIS = getYearlyET(collectionMODIS, 'MODIS', 'ET', 0.1);var yearlyTerraClimate = getYearlyET(collectionTerraClimate, 'TerraClimate', 'aet', 0.1);
function getYearlyPML() {  var range = collectionPML.reduceColumns(ee.Reducer.minMax(), ['system:time_start']);  var diff = ee.Date(range.get('max')).difference(ee.Date(range.get('min')), 'year');    var yearlyData = ee.List.sequence(0, diff).map(function(n) {    var start = ee.Date(range.get('min')).advance(n, 'year');    var end = start.advance(1, 'year');        var yearlyImage = collectionPML      .filterDate(start, end)      .map(function(image) {        return image.expression(          '(Ec + Es + Ei) * 8', {            'Ec': image.select('Ec'),            'Es': image.select('Es'),            'Ei': image.select('Ei')          }).rename('ET');      })      .sum()      .set('system:time_start', start);        var year = ee.Date(yearlyImage.get('system:time_start')).get('year');    var meanValue = yearlyImage.reduceRegion({      reducer: ee.Reducer.mean(),      geometry: ET_region,      scale: 50000    }).get('ET');        return ee.Feature(null, {      'Year': year,      'Dataset': 'PML',      'ET (mm/year)': meanValue    });  });    return ee.List(yearlyData);}
var yearlyPML = getYearlyPML();
var allYearlyET = ee.List(yearlyFLDAS)  .cat(yearlyMODIS)  .cat(yearlyTerraClimate)  .cat(yearlyPML);
var etCollection = ee.FeatureCollection(allYearlyET);
function printRegressionSlope(featureCollection, datasetName) {  var regression = featureCollection    .filter(ee.Filter.eq('Dataset', datasetName))    .reduceColumns({      selectors: ['Year', 'ET (mm/year)'],      reducer: ee.Reducer.linearFit()    });    var slope = regression.get('scale');  print('Slope of ' + datasetName + ' (mm):', slope);}
printRegressionSlope(etCollection, 'FLDAS');printRegressionSlope(etCollection, 'MODIS');printRegressionSlope(etCollection, 'PML');printRegressionSlope(etCollection, 'TerraClimate');
function addLinearRegression(featureCollection, datasetName) {  var regression = featureCollection    .filter(ee.Filter.eq('Dataset', datasetName))    .reduceColumns({      selectors: ['Year', 'ET (mm/year)'],      reducer: ee.Reducer.linearFit()    });    var slope = regression.get('scale');  var intercept = regression.get('offset');    return featureCollection.map(function(feature) {    var year = feature.getNumber('Year');    var predictedET = ee.Number(slope).multiply(year).add(intercept);    return feature.set(datasetName + '_predicted', predictedET);  });}
etCollection = addLinearRegression(etCollection, 'FLDAS');etCollection = addLinearRegression(etCollection, 'MODIS');etCollection = addLinearRegression(etCollection, 'PML');etCollection = addLinearRegression(etCollection, 'TerraClimate');
var chartData = etCollection.map(function(feature) {  var year = feature.getNumber('Year');  var dataset = feature.getString('Dataset');  var et = feature.getNumber('ET (mm/year)');  var predictedET = feature.getNumber(dataset + '_predicted');    return ee.Feature(null, {    'Year': year,    'Dataset': dataset,    'ET (mm/year)': et,    'Predicted ET (mm/year)': predictedET  });});
var chart = ui.Chart.feature.groups({  features: chartData,  xProperty: 'Year',  yProperty: 'ET (mm/year)',  seriesProperty: 'Dataset'}).setChartType('LineChart').setOptions({  title: 'Annual ET Trends (2001-2020)',  hAxis: {title: 'Year'},  vAxis: {title: 'ET (mm)'},  lineWidth: 2,  pointSize: 4,  series: {    0: {lineDashStyle: [1, 1]},    1: {lineDashStyle: [2, 2]},    2: {lineDashStyle: [4, 4]},    3: {lineDashStyle: [8, 8]}  }});
print(chart);