今天来分享一下如何在GEE中基于哨兵二号数据计算植被覆盖度，并分级制图。
以宁夏回族自治区为研究区
代码如下：
var roi = ee.FeatureCollection("users/lilei655123/Ningxia");Map.centerObject(roi,7)//boundaryvar styling = {color:"red",fillColor:"00000000"};Map.addLayer(roi.style(styling),{},"geometry")function maskS2clouds(image) {var qa = image.select('QA60');// Bits 10 and 11 are clouds and cirrus, respectively.var cloudBitMask = 1 << 10;var cirrusBitMask = 1 << 11;// Both flags should be set to zero, indicating clear conditions.var mask = qa.bitwiseAnd(cloudBitMask).eq(0).and(qa.bitwiseAnd(cirrusBitMask).eq(0));return image.updateMask(mask).divide(10000);}var S2 = ee.ImageCollection('COPERNICUS/S2_SR').filterDate('-07-01', '-09-30').filterBounds(roi)// Pre-filter to get less cloudy granules..filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE',10)).map(maskS2clouds).median();//ndvivar NDVI1 = S2.expression('(NIR-R)/(NIR+R)',{'R': S2.select(['B4']),'NIR': S2.select(['B8']),})var imgFVC = ((NDVI1.subtract(ee.Image(0.05))).divide((ee.Image(0.95)).subtract(ee.Image(0.05)))).float();var FVC=((imgFVC.lt(0)).multiply(0)).add(((imgFVC.gt(0)).and(imgFVC.lte(1))).multiply(imgFVC)).add((imgFVC.gt(1)).multiply(1))var FVC_Class=FVC.where(FVC.lt(0.2),1).where(((FVC.gte(0.2)).and(FVC.lt(0.4))),2).where(((FVC.gte(0.4)).and(FVC.lt(0.6))),3).where(((FVC.gte(0.6)).and(FVC.lt(0.8))),4).where(FVC.gt(0.8),5)Map.addLayer(FVC_Class.clip(roi),{min:1,max:5,palette:['DCDCDC','FFEBCD','99B718','529400','011301']},'FVC_Class')var visualization = {min: 0.0,max: 0.3,bands: ['B4', 'B3', 'B2'],};Map.addLayer(S2.clip(roi), visualization, 'RGB');
显示结果如下：
感谢关注，欢迎转发！
声明：仅供学习使用！
