//直接导入研究区范围就好，本文以yjq为例
var roi = ee.FeatureCollection(yjq);

//去云函数
function maskL8sr(image) {
  // Bits 3 and 5 are cloud shadow and cloud, respectively.
  var cloudShadowBitMask = (1 << 3);
  var cloudsBitMask = (1 << 5);
  // Get the pixel QA band.
  var qa = image.select('pixel_qa');
  // Both flags should be set to zero, indicating clear conditions.
  var mask = qa.bitwiseAnd(cloudShadowBitMask).eq(0)
                 .and(qa.bitwiseAnd(cloudsBitMask).eq(0));
  return image.updateMask(mask);
}

//计算NDVI函数
function NDVI(img){
  var ndvi = img.normalizedDifference(["B5","B4"]);
  return ndvi;
}

//去云、裁剪、时间选取
var l_8 = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR').map(maskL8sr);
var img = ee.Image(l_8.filterBounds(roi)
                         .filterDate("2020-1-01","2020-12-31").mean()).clip(roi);
//计算ndvi
var ndvi = NDVI(img);

// 设置ndvi的显示颜色
var visParam = {
  min : -0.2,
  max :1,
  palette:'FFFFFF, CE7E45, DF923D, F1B555, FCD163, 99B718, 74A901, 66A000, 529400,' +
   '3E8601, 207401, 056201, 004C00, 023B01, 012E01, 011D01, 011301'
};

// 设置中心点、加载roi和ndvi图层
Map.centerObject(roi,7);
Map.setCenter(110.9461, 29.4101);
Map.addLayer(roi,{},'cilixian_bound',1,1)
Map.addLayer(ndvi,visParam,"NDVI")

//导出数据
Export.image.toDrive({
   image: ndvi,
   description: 'cilixian_NDVI_6', //数据名
   folder:'cilixian_NDVI', //存储文件夹
   scale: 30, //分辨率
   region:roi,
   maxPixels:1e13,
 });

print("over")