今天來分享下如何利用GEE提取點的土壤濕度，首先介紹一個數據集NASA/GLDAS/V021/NOAH/G025/T3H，里面包含很多數據集，包括氣象、土壤、氣溫等數據，

例如：

CanopInt_inst植物冠層地表水含量、

ECanop_tavg樹冠水分蒸發

ESoil_tavg裸土蒸發量

Snowf_tavg雪速率

SoilMoi0_10cm_inst土壤濕度

SoilTMP0_10cm_inst土壤溫度

Tair_f_inst氣溫

Wind_f_inst風速

GEE調用代碼如下：

var roi = /* color: #d63000 */ee.Geometry.Point([121.3664979892787, 37.45796001127996]); // Create a chart for SoilMoi100_200cm_inst trend in point 1. Map.centerObject(roi,7) var dataset = ee.ImageCollection('NASA/GLDAS/V021/NOAH/G025/T3H').filterBounds(roi).filterDate('2006-01-01', '2016-12-31').select('SoilMoi100_200cm_inst');var radius_lst = ee.List([250, 500, 1000, 1500, 2000]);var colByRadius = ee.List(radius_lst).map(function (radius) {var months = ee.List.sequence(1, 12);var start_year = 2006;var start_date = '2006-01-01';var end_year = 2016;var end_date = '2016-12-31';var years = ee.List.sequence( start_year, end_year);var ptsbuff = ee.FeatureCollection(roi).map(function (radius, bounds) {return function(pt) {pt = ee.Feature(pt);return bounds ? pt.buffer(radius).bounds() : pt.buffer(radius);};}(radius, false));var byMonthYear = years.map(function (y) {return months.map(function(m) {var w = dataset.filter(ee.Filter.calendarRange(y, y, 'year')).filter(ee.Filter.calendarRange(m, m, 'month')).mean();var pointMean = w.reduceRegion({reducer:ee.Reducer.first(), geometry:ptsbuff, scale:500}); // set the dictionary as property and cast to an ee.Image, as setMulti returns an ee.Element.return ee.Feature(null).set("value",pointMean.get("SoilMoi100_200cm_inst")).set("year",y).set("month",m).set("radius", radius);});}).flatten();return byMonthYear;}).flatten();Export.table.toDrive({collection:ee.FeatureCollection(colByRadius), description:"csvExport"})

?導出結果：

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聲明：僅供學習使用！

GEE demo：

https://code.earthengine.google.com/699a662afe7028ac818e03c04b3a5753

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總結

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