Vjylku

I met one problem about export .csv and need suggestions about looping for my code. I'm trying to calculate the water areas and the statistics of each band for each water areas to see if there are seasonal changes.

1. The exported .csv file only have the columns ("GNIS_ID","AreaSqKm","waterArea") before join. I printed the variable, Join, and it does have all the column I need. How come they didn't show in the exported csv file? Did I miss something?




2. My next step will need to loop the code by month in order to export the water areas and their statistics by month from 2014 to 2018, I've been tried using map and with my code, but it didn't seem to work.

Sorry that this is my first GEE script, so it's very messy, if there is any better way to write it, please let me know, I appreciate a lot.

Thank you!

    var CollectMonth = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR')

      .filterBounds(HI_poly)

      .sort('CLOUD_COVER')

      .filterDate('2014-01-01', '2014-01-30')

      .map(function(image){return image.clip(USGS_WBD)})  // clip the images by the;

      print(CollectMonth);



    // Calculate Water Area

    var waterThreshold = 324;



    var WaterAreaFunction = function(image){

      //add the water band to the image

      var water = image.select(['pixel_qa']).rename('water');

      //get pixels equal the threshold

      var water01 = water.eq(waterThreshold);

      //mask those pixels from the image

      image = image.updateMask(water01).addBands(water);



      var area = ee.Image.pixelArea();

      var waterArea = water01.multiply(area).rename('waterArea');



      image = image.addBands(waterArea);



      var stats = waterArea.reduceRegion({

        reducer: ee.Reducer.sum(), 

        geometry: USGS_WBD, 

        scale: 30,

      });



      return image.set(stats);

    };



    var l8Mosaic = CollectMonth.map(WaterAreaFunction).mosaic().multiply(0.0001);

    var l8Mosaic_area = l8Mosaic.divide(1000000)



    //statistics

    var WBD_area = l8Mosaic_area.reduceRegions({

      collection: USGS_WBD,

      reducer: ee.Reducer.sum(),

      scale: 30 // resolution

    }).select(["GNIS_ID","AreaSqKm","waterArea"]);

    print("area:",WBD_area);



    var WBD_value = l8Mosaic.select(["B1","B2","B3","B4","B5","B6","B7"])

                            .rename(["B1_mean","B2_mean","B3_mean","B4_mean","B5_mean","B6_mean","B7_mean"])

    var WBD_mean = WBD_value.reduceRegions({

      collection: USGS_WBD,

      reducer: ee.Reducer.mean(),

      scale: 30 // resolution

    }).select(["GNIS_ID","B1_mean","B2_mean","B3_mean","B4_mean","B5_mean","B6_mean","B7_mean"])

    print("mean:",WBD_mean);



    var WBD_value = l8Mosaic.select(["B1","B2","B3","B4","B5","B6","B7"])

                            .rename(["B1_median","B2_median","B3_median","B4_median","B5_median","B6_median","B7_median"])

    var WBD_median = WBD_value.reduceRegions({

      collection: USGS_WBD,

      reducer: ee.Reducer.median(),

      scale: 30 // resolution

    }).select(["GNIS_ID","B1_median","B2_median","B3_median","B4_median","B5_median","B6_median","B7_median"])

    print("median:",WBD_median);



    var WBD_value = l8Mosaic.select(["B1","B2","B3","B4","B5","B6","B7"])

                            .rename(["B1_min","B2_min","B3_min","B4_min","B5_min","B6_min","B7_min"])

    var WBD_min = WBD_value.reduceRegions({

      collection: USGS_WBD,

      reducer: ee.Reducer.min(),

      scale: 30 // resolution

    }).select(["GNIS_ID","B1_min","B2_min","B3_min","B4_min","B5_min","B6_min","B7_min"])

    print("min:",WBD_min);



    var WBD_value = l8Mosaic.select(["B1","B2","B3","B4","B5","B6","B7"])

                            .rename(["B1_max","B2_max","B3_max","B4_max","B5_max","B6_max","B7_max"])

    var WBD_max = WBD_value.reduceRegions({

      collection: USGS_WBD,

      reducer: ee.Reducer.max(),

      scale: 30 // resolution

    }).select(["GNIS_ID","B1_max","B2_max","B3_max","B4_max","B5_max","B6_max","B7_max"])

    print("max:",WBD_max);



    var WBD_value = l8Mosaic.select(["B1","B2","B3","B4","B5","B6","B7"])

                            .rename(["B1_WBD10","B2_WBD10","B3_WBD10","B4_WBD10","B5_WBD10","B6_WBD10","B7_WBD10"])

    var WBD10 = WBD_value.reduceRegions({

      collection: USGS_WBD,

      reducer: ee.Reducer.percentile([10]),

      scale: 30 // resolution

    }).select(["GNIS_ID","B1_WBD10","B2_WBD10","B3_WBD10","B4_WBD10","B5_WBD10","B6_WBD10","B7_WBD10"])

    print("WBD10:",WBD10);



    var WBD_value = l8Mosaic.select(["B1","B2","B3","B4","B5","B6","B7"])

                            .rename(["B1_WBD90","B2_WBD90","B3_WBD90","B4_WBD90","B5_WBD90","B6_WBD90","B7_WBD90"])

    var WBD90 = WBD_value.reduceRegions({

      collection: USGS_WBD,

      reducer: ee.Reducer.percentile([90]),

      scale: 30 // resolution

    }).select(["GNIS_ID","B1_WBD90","B2_WBD90","B3_WBD90","B4_WBD90","B5_WBD90","B6_WBD90","B7_WBD90"])

    print("WBD90:",WBD90);



    var WBD_value = l8Mosaic.select(["B1","B2","B3","B4","B5","B6","B7"])

                            .rename(["B1_std","B2_std","B3_std","B4_std","B5_std","B6_std","B7_std"])

    var WBD_std = WBD_value.reduceRegions({

      collection: USGS_WBD,

      reducer: ee.Reducer.stdDev(),

      scale: 30 // resolution

    }).select(["GNIS_ID","B1_std","B2_std","B3_std","B4_std","B5_std","B6_std","B7_std"])

    print("std:",WBD_std);



    var WBD_value = l8Mosaic.select(["B1","B2","B3","B4","B5","B6","B7"])

                            .rename(["B1_variance","B2_variance","B3_variance","B4_variance","B5_variance","B6_variance","B7_variance"])

    var WBD_variance = WBD_value.reduceRegions({

      collection: USGS_WBD,

      reducer: ee.Reducer.variance(),

      scale: 30 // resolution

    }).select(["GNIS_ID","B1_variance","B2_variance","B3_variance","B4_variance","B5_variance","B6_variance","B7_variance"])

    print("variance:",WBD_variance);





    // =============== Join ============================

    // Join two collection

    // Use an equals filter to define how the collections match.

    var filter = ee.Filter.equals({

      leftField: 'GNIS_ID',

      rightField: 'GNIS_ID'

    });



    // Define the join.

    var innerJoin = ee.Join.inner();



    // Apply the join.

    var Join = innerJoin.apply(WBD_area, WBD_mean, filter);

    Join = Join.map(function(pair) {

      var f1 = ee.Feature(pair.get('primary'));

      var f2 = ee.Feature(pair.get('secondary'));

      return f1.set(f2.toDictionary());

    });



    // Apply the join.

    var Join = innerJoin.apply(Join, WBD_median,filter);

    Join = Join.map(function(pair) {

      var f1 = ee.Feature(pair.get('primary'));

      var f2 = ee.Feature(pair.get('secondary'));

      return f1.set(f2.toDictionary());

    });



    // // Apply the join.

    var Join = innerJoin.apply(Join, WBD_min,filter);

    Join = Join.map(function(pair) {

      var f1 = ee.Feature(pair.get('primary'));

      var f2 = ee.Feature(pair.get('secondary'));

      return f1.set(f2.toDictionary());

    });



    // // Apply the join.

    var Join = innerJoin.apply(Join, WBD_max,filter);

    Join = Join.map(function(pair) {

      var f1 = ee.Feature(pair.get('primary'));

      var f2 = ee.Feature(pair.get('secondary'));

      return f1.set(f2.toDictionary());

    });



    // // Apply the join.

    var Join = innerJoin.apply(Join, WBD10,filter);

    Join = Join.map(function(pair) {

      var f1 = ee.Feature(pair.get('primary'));

      var f2 = ee.Feature(pair.get('secondary'));

      return f1.set(f2.toDictionary());

    });



    // // Apply the join.

    var Join = innerJoin.apply(Join, WBD90,filter);

    Join = Join.map(function(pair) {

      var f1 = ee.Feature(pair.get('primary'));

      var f2 = ee.Feature(pair.get('secondary'));

      return f1.set(f2.toDictionary());

    });



    // // Apply the join.

    var Join = innerJoin.apply(Join, WBD_std,filter);

    Join = Join.map(function(pair) {

      var f1 = ee.Feature(pair.get('primary'));

      var f2 = ee.Feature(pair.get('secondary'));

      return f1.set(f2.toDictionary());

    });



    // // Apply the join.

    var Join = innerJoin.apply(Join, WBD_variance,filter);

    Join = Join.map(function(pair) {

      var f1 = ee.Feature(pair.get('primary'));

      var f2 = ee.Feature(pair.get('secondary'));

      return f1.set(f2.toDictionary());

    });

    print(Join)



    // Export the FeatureCollection.

    Export.table.toDrive({

      collection: Join,

      description: 'Monthly_Lansat8_SR',

      fileFormat: 'CSV'

    });