[Google Earth Engine：如何在使用Cloud Masking和Land Masking计算NDVI的过程中使用形状文件作为关注区域

Question

我正在尝试通过澳大利亚的云遮罩和陆地遮罩来计算年度NDVI。

我收到此错误

图像（错误）reduce.mean：映射错误（ID = 0）：Image.bitwiseAnd：按位操作数只能是整数。

我的代码是https://code.earthengine.google.com/?scriptPath=users%2Ftafzilamouly%2Ffpc%3AEXPLORE

Answer 1

我已通过将shapefile转换为几何图形解决了该问题。

但是，对于以下代码，我现在遇到“错误创建或提交任务请求有效负载大小超出限制：4194304字节”。

请注意，改变比例尺不是我的选择，我需要30 m比例尺。

var table = ee.FeatureCollection("users/tafzilamouly/QLD"),
    L5 = ee.ImageCollection("LANDSAT/LT05/C01/T1_SR"),
    hansen = ee.Image("UMD/hansen/global_forest_change_2018_v1_6");

//Filter region and time period

var L52009annual= L5.filterDate('2009-01-01',"2009-12-31")
//var L52009quarter= L5.filterDate('2009-04-01',"2009-06-30")
var AUS= ee.FeatureCollection(table)
var QLD= AUS.geometry()

var Australia2009annual= ee.ImageCollection(L52009annual).filterBounds(QLD)
//var Australia2009quarter= L52009quarter.clipToCollection(AUS)
//Map.addLayer(Australia2009annual, {}, 'Australia2009annual')
//Map.addLayer(Australia2009quarter, {}, 'Australia2009quarter')

//NDVI

var addNDVI= function addNDVI(image){
  var ndvi= image.normalizedDifference(['B4', 'B3']).rename('NDVI');
  return image.addBands(ndvi);
};

// Cloud mask
var cloudMaskL457 = function(image) {
  var qa = image.select('pixel_qa');
  // If the cloud bit (5) is set and the cloud confidence (7) is high
  // or the cloud shadow bit is set (3), then it's a bad pixel.
  var cloud = qa.bitwiseAnd(1 << 5)
          .and(qa.bitwiseAnd(1 << 7))
          .or(qa.bitwiseAnd(1 << 3))
  // Remove edge pixels that don't occur in all bands
  var mask2 = image.mask().reduce(ee.Reducer.min());
  return image.updateMask(cloud.not()).updateMask(mask2);
};

// land mask

var landMask = function(image) {
var datamask = hansen.select('datamask');
var mask = datamask.eq(1);
return image.updateMask(mask);
};

var NDVI2009annual= ee.ImageCollection(Australia2009annual)
    .map(addNDVI)
    .map(cloudMaskL457)
    .map(landMask)
    .mean()

//print(NDVI2009annual)

var NDVI= NDVI2009annual.select('NDVI')
var positiveNDVI2009annual= NDVI.mask(NDVI)
print(positiveNDVI2009annual)
Map.addLayer(positiveNDVI2009annual, {}, 'positiveNDVI2009annual')

Export.image.toDrive({
  image: positiveNDVI2009annual,
  description: 'NDVI_2009_annual',
  region: QLD,
  scale: 30,
  fileFormat: 'GeoTIFF',
  maxPixels: 33491829976,
  });