Iterating over years for features in public feature collection using GEE?

Question

I want to calculate the surfaces deforested every year for every protected area in Democratic Republic of the Congo. I am building from the script provided as answer by Rodrigo Principe in reply to this similar question. But this example used a private shapefile loaded in assets. When I try to reproduce this solution with a public dataset (in-land protected areas in DRC, so my question somehow completes the official GEE tutorial on quantigfying deforestation in DRC), it doesn't work : output "areas" remain desesperatelly empty. The code bellow is the same as proposed by Rodrigo Principe, except the lines marked with an"// EDIT" comment. Does anyone knows how to fix it?

// Load and filter the Hansen data
// EDIT : The source in following line has been updated to load v1_3
var gfc2014 = ee.Image('UMD/hansen/global_forest_change_2015_v1_3')
              // END EDIT
              .select(['treecover2000','loss','gain','lossyear']);

// list for filter iteration
var years = ee.List.sequence(1, 14)

// turn your scale into a var in case you want to change it
var scale = 100

//add country districts as a feature collection
// EDIT: loads public source+filters inland protected areas in DRC 
var distr = ee.FeatureCollection('WCMC/WDPA/current/polygons');
// Filter to keep only inland PA in 2 countries
var distr = distr.filter(ee.Filter.and(
    ee.Filter.eq("ISO3", "COD"),
    ee.Filter.eq("MARINE", "0")));
// END EDIT

//look at tree cover, find the area
var treeCover = gfc2014.select(['treecover2000']);
var areaCover = treeCover.multiply(ee.Image.pixelArea())
                .divide(10000).select([0],["areacover"])

// total loss area
var loss = gfc2014.select(['loss']);
var areaLoss = loss.gt(0).multiply(ee.Image.pixelArea())
               .divide(10000).select([0],["arealoss"]);

// total gain area
var gain = gfc2014.select(['gain'])
var areaGain = gain.gt(0).multiply(ee.Image.pixelArea())
               .divide(10000).select([0],["areagain"]);

// final image
var total = gfc2014.addBands(areaCover)
            .addBands(areaLoss)
            .addBands(areaGain)

Map.addLayer(total,{},"total")

// Map cover area per feature
var districtSums = areaCover.reduceRegions({
  collection: distr,
  reducer: ee.Reducer.sum(),
  scale: scale,
});


var addVar = function(feature) {

  // function to iterate over the sequence of years
  var addVarYear = function(year, feat) {
    // cast var
    year = ee.Number(year).toInt()
    feat = ee.Feature(feat)

    // actual year to write as property
    var actual_year = ee.Number(2000).add(year)

    // filter year:
    // 1st: get mask
    var filtered = total.select("lossyear").eq(year)
    // 2nd: apply mask
    filtered = total.updateMask(filtered)

    // reduce variables over the feature
    var reduc = filtered.reduceRegion({
      geometry: feature.geometry(),
      reducer: ee.Reducer.sum(),
      scale: scale,
      maxPixels: 1e9 // EDIT : added to allow large areas
    })

    // get results
    var loss = ee.Number(reduc.get("arealoss"))
    var gain = ee.Number(reduc.get("areagain"))

    // set names
    var nameloss = ee.String("loss_").cat(actual_year)
    var namegain = ee.String("gain_").cat(actual_year)

    // alternative 1: set property only if change greater than 0
    var cond = loss.gt(0).or(gain.gt(0))
    return ee.Algorithms.If(cond, 
                            feat.set(nameloss, loss, namegain, gain),
                            feat)

    // alternative 2: always set property
    // set properties to the feature
    // return feat.set(nameloss, loss, namegain, gain)
  }

  // iterate over the sequence
  var newfeat = ee.Feature(years.iterate(addVarYear, feature))

  // return feature with new properties
  return newfeat
}

// Map over the FeatureCollection
var areas = districtSums.map(addVar);

Map.addLayer(areas, {}, "areas")

print(areas)

Answer 1

It does work, to prove it, I modified a little bit the code to show a chart. Just click on one feature and it shows 2 charts: loss and gain. If there are 2 overlapping features, it just plots for the first.

Code link: https://code.earthengine.google.com/7405deb2901a53729745cea43986e708

Code:

// Load and filter the Hansen data
// EDIT : The source in following line has been updated to load v1_3
var gfc2014 = ee.Image('UMD/hansen/global_forest_change_2015_v1_3')
              // END EDIT
              .select(['treecover2000','loss','gain','lossyear']);

// list for filter iteration
var years = ee.List.sequence(1, 14)

// turn your scale into a var in case you want to change it
var scale = 100

//add country districts as a feature collection
// EDIT: loads public source+filters inland protected areas in DRC 
var distr = ee.FeatureCollection('WCMC/WDPA/current/polygons');
// Filter to keep only inland PA in 2 countries
var distr = distr.filter(ee.Filter.and(
    ee.Filter.eq("ISO3", "COD"),
    ee.Filter.eq("MARINE", "0")));
// END EDIT

//look at tree cover, find the area
var treeCover = gfc2014.select(['treecover2000']);
var areaCover = treeCover.multiply(ee.Image.pixelArea())
                .divide(10000).select([0],["areacover"])

// total loss area
var loss = gfc2014.select(['loss']);
var areaLoss = loss.gt(0).multiply(ee.Image.pixelArea())
               .divide(10000).select([0],["arealoss"]);

// total gain area
var gain = gfc2014.select(['gain'])
var areaGain = gain.gt(0).multiply(ee.Image.pixelArea())
               .divide(10000).select([0],["areagain"]);

// final image
var total = gfc2014.addBands(areaCover)
            .addBands(areaLoss)
            .addBands(areaGain)

// Map cover area per feature
var districtSums = areaCover.reduceRegions({
  collection: distr,
  reducer: ee.Reducer.sum(),
  scale: scale,
});


var addVar = function(feature) {

  var nfeat = ee.Feature(ee.Feature(feature).geometry(), {})

  // function to iterate over the sequence of years
  var addVarYear = function(year, feat) {
    // cast var
    year = ee.Number(year).toInt()
    feat = ee.Feature(feat)
    //var nfeat = ee.Feature(feat.geometry(), {})

    // actual year to write as property
    var actual_year = ee.Number(2000).add(year)

    // filter year:
    // 1st: get mask
    var filtered = total.select("lossyear").eq(year)
    // 2nd: apply mask
    filtered = total.updateMask(filtered)

    // reduce variables over the feature
    var reduc = filtered.reduceRegion({
      geometry: feature.geometry(),
      reducer: ee.Reducer.sum(),
      scale: scale,
      maxPixels: 1e9 // EDIT : added to allow large areas
    })

    // get results
    var loss = ee.Number(reduc.get("arealoss"))
    var gain = ee.Number(reduc.get("areagain"))

    // set names
    var nameloss = ee.String("loss_").cat(actual_year)
    var namegain = ee.String("gain_").cat(actual_year)

    // alternative 1: set property only if change greater than 0
    var cond = loss.gt(0).or(gain.gt(0))
    //return ee.Algorithms.If(cond, 
    //                        feat.set(nameloss, loss, namegain, gain),
    //                        feat)

    // alternative 2: always set property
    // set properties to the feature
    //return ee.Feature(feat.geometry(), {nemeloss:loss, namegain: gain})
    return feat.set(nameloss, loss, namegain, gain)
  }

  // iterate over the sequence
  var newfeat = ee.Feature(years.iterate(addVarYear, nfeat))

  // return feature with new properties
  return newfeat
}

// Map over the FeatureCollection
var areas = districtSums.map(addVar);

Map.addLayer(areas, {}, "areas")

var allY = ee.List.sequence(2001, 2014)
var allN = ee.List(['gain', 'loss'])
var allG = allY.map(function(item) {return ee.String('gain_').cat(ee.Number(item).int().format())})
var allL = allY.map(function(item) {return ee.String('loss_').cat(ee.Number(item).int().format())})

var onclick = function(coord) {
  var filt = areas.filterBounds(ee.Geometry.Point(coord.lon, coord.lat))
  var feat = ee.Feature(filt.first())
  var char_gain = ui.Chart.feature.byProperty({'features': feat,
                                               'xProperties': allG.getInfo()})
  print(char_gain.setOptions({'title':'GAIN'}))
  var char_loss = ui.Chart.feature.byProperty({'features': feat,
                                               'xProperties': allL.getInfo()})
  print(char_loss.setOptions({'title':'LOSS'}))
}
Map.onClick(onclick)