Question

我已经编写了一个非常完美的代码（即使我确定它可以改进）。这段代码为我提供了CHIRPS项目的每月降雨数据。我对GEE非常陌生，我想知道是否有任何方法可以获取特定投资回报率上的每周数据，而不是每月数据。

特别是，我正在使用该函数创建每月数据的模板，但不知道对其进行修改以获取每周数据（函数ee.Date.FromYMD）

var startyear = 2008;
var endyear = 2017;

// Set date in ee date format
var startdate = ee.Date.fromYMD(startyear,1,1);
var enddate = ee.Date.fromYMD(endyear,12,31)

请参阅下面的完整代码。

var chirps = ee.ImageCollection('UCSB-CHG/CHIRPS/DAILY')


// import rainfall stations

// Define time range
var startyear = 2008;
var endyear = 2017;

// Set date in ee date format
var startdate = ee.Date.fromYMD(startyear,1,1);
var enddate = ee.Date.fromYMD(endyear,12,31)

// create list for years
var years = ee.List.sequence(startyear,endyear);

// make a list with months
var months = ee.List.sequence(1,12);

// Filter chirps
var Pchirps = chirps.filterDate(startdate, enddate)
  // Sort chronologically in descending order.
  .sort('system:time_start', false)
  .filterBounds(Rainfallstations)
  .select("precipitation");


// calculate the P for each month
var MonthlyChirps =  ee.ImageCollection.fromImages(
  years.map(function (y) {
  return months.map(function(m){
    var w = Pchirps.filter(ee.Filter.calendarRange(y, y, 'year'))
             .filter(ee.Filter.calendarRange(m, m, 'month'))
             .sum();
    return w.set('year', y)
             .set('month', m)
             .set('system:time_start',ee.Date.fromYMD(y,m,1)) 
             .set('date', ee.Date.fromYMD(y,m,1))
});
}).flatten());
// Collect region, image, value triplets.
var triplets = MonthlyChirps.map(function(image) {
  return image.reduceRegions({
    collection: Rainfallstations.select(['ADM2_NAME']), 
    reducer: ee.Reducer.mean(), 
    scale: 1000
  }).filter(ee.Filter.neq('mean', null))
    .map(function(f) { 
      return f.set('imageId', image.id()).setGeometry(null);
    });
}).flatten();
print(triplets.first());

// Format a table of triplets into a 2D table of rowId x colId.
var format = function(table, rowId, colId) {
  // Get a FeatureCollection with unique row IDs.
  var rows = table.distinct(rowId);
  // Join the table to the unique IDs to get a collection in which
  // each feature stores a list of all features having a common row ID. 
  var joined = ee.Join.saveAll('matches').apply({
    primary: rows, 
    secondary: table, 
    condition: ee.Filter.equals({
      leftField: rowId, 
      rightField: rowId
    })
  });

  return joined.map(function(row) {
      // Get the list of all features with a unique row ID.
      var values = ee.List(row.get('matches'))
        // Map a function over the list of rows to return a list of
        // column ID and value.
        .map(function(feature) {
          feature = ee.Feature(feature);
          return [feature.get(colId), feature.get('mean')];
        });
      // Return the row with its ID property and properties for
      // all matching columns IDs storing the output of the reducer.
      // The Dictionary constructor is using a list of key, value pairs.
      return row.select([rowId]).set(ee.Dictionary(values.flatten()));
    });
};

var table1 = format(triplets, 'imageId', 'ADM2_NAME');

var desc1 = 'table_demo_'; 
Export.table.toDrive({
  collection: table1, 
  description: desc1, 
  fileNamePrefix: desc1,
  fileFormat: 'CSV'
});

Google Earth Engine-每周数据CHIRPS

0 个答案: