哨兵2的NDVI时间序列数据下载

本文主要是介绍哨兵2的NDVI时间序列数据下载，对大家解决编程问题具有一定的参考价值，需要的程序猿们随着小编来一起学习吧！

1.导入哨兵2数据集

2.绘制下载区域

3.修改绘制区域与数据集名称

4.运行下面代码

//define ROI
var roi = ee.FeatureCollection(ROI)

//哨兵2去云处理
function s2_rmcloud(image) { 
  var qa = image.select('QA60'); 
  var cloudBitMask = 1 << 10; 
  var cirrusBitMask = 1 << 11; 
  var mask = qa.bitwiseAnd(cloudBitMask).eq(0) 
               .and(qa.bitwiseAnd(cirrusBitMask).eq(0)); 
  return image.updateMask(mask); 
} 

//在原影像中加入一个新的波段，命名为NDVI
var s2_ndvi = function(image) {
 return image.addBands(image.normalizedDifference(["B8", "B4"]).rename("NDVI"));
};

//选择某一年的NDVI时间序列数据集
var Year = '2020';
var DateTime = [Year+'-01-01', Year+'-03-31',Year+'-02-01', Year+'-02-28',Year+'-03-01', Year+'-03-31',
    Year+'-04-01', Year+'-04-30',Year+'-05-01', Year+'-05-31',Year+'-06-01', Year+'-06-30',
    Year+'-07-01', Year+'-07-31',Year+'-08-01', Year+'-08-31',Year+'-09-01', Year+'-09-30',
    Year+'-10-01', Year+'-10-31',Year+'-11-01', Year+'-11-30',Year+'-12-01', Year+'-12-31',];
//print(DateTime);


//定义批量导出函数
function exportImage(imgCol,region,fileName) {
      Export.image.toDrive({
        image: imgCol,
        description: "NDVI",
        fileNamePrefix: "ndvi"+fileName,
        scale: 10,
        region:region,
        crs: "EPSG:4326",
        maxPixels: 1e13
      });
    }

//过滤筛选哨兵2影像中NDVI，并导出。
for(var i=0;i<DateTime.length;i+=2){
var s2_nocloud = s2_col.map(s2_rmcloud)
                       .filterBounds(roi)
                       .filterDate(DateTime[i], DateTime[i+1])
                       .filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE', 12));
var ndvi = s2_nocloud.map(s2_ndvi).select("NDVI").reduce(ee.Reducer.mean());
var ndvi_clipped = ndvi.clipToCollection(roi);

exportImage(ndvi_clipped,roi,DateTime[i]);
}

var visParam = {min: 0, max: 1, palette: ['ffffff', '000000']};
Map.centerObject(roi,7);
Map.addLayer(roi,{color:'FFFF00'},"roi");
Map.addLayer(ndvi, visParam, "ndvi",false);
Map.addLayer(ndvi_clipped, visParam, "ndvi_clipped");

5.当导出run的列表全部显示后，打开浏览器的console命令行运行窗口，复制粘贴杨老师的批量点run代码，再enter，耐心等待即可。

runTasks = function() {
    const evt = new MouseEvent('click', {bubbles: true, cancelable: true, ctrlKey: true})
    $$('.run-button' ,$$('ee-task-pane')[0].shadowRoot).forEach(function(e) {
        e.dispatchEvent(evt)
    })
}
runTasks()

如图：
在这里插入图片描述
导入谷歌网盘。