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somm-doe/greencities.js

Forked from funkeinteraktiv/greencities.js
Last active April 28, 2019 10:54
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  1. somm-doe revised this gist Apr 28, 2019. 1 changed file with 17 additions and 7 deletions.
    24 changes: 17 additions & 7 deletions greencities.js
    View file
    Original file line number Diff line number Diff line change
    @@ -70,7 +70,11 @@ cities = cities.map(function(feature){
    });

    // export data as geojson
    Export.table(cities, 'greencities_export', { fileFormat: 'GeoJSON' });
    Export.table.toDrive({
    collection: cities,
    description: 'greencities_export',
    fileFormat: 'GeoJSON'
    });

    // add clipped layer to the map
    Map.addLayer(
    @@ -86,20 +90,26 @@ var ndviRGB = resultCollectionReduced.visualize({
    });

    // export colored shape of germany
    Export.image(ndviRGB, 'germany_ndvi', {
    Export.image.toDrive({
    image: ndviRGB,
    description: 'germany_ndvi',
    folder: 'folder_name',
    scale: 30,
    region: germany.geometry(),
    maxPixels: 130000000000
    maxPixels: 130000000000,
    });



    // helper functions

    function getLandsatByYear(year) {
    return landsats
    .filter(ee.Filter.lte('from', year)
    .and(ee.Filter.gt('to', year)))
    .filter(ee.Filter.and(
    // filter where passed year is lower than or equal 'from' property
    ee.Filter.lte('from', year),
    // and filter where passed year is greater than 'to' property
    ee.Filter.gt('to', year)
    ))
    // return first matching in order to return a single object
    .first();
    }

  2. Berliner Morgenpost revised this gist May 9, 2016. No changes.
  3. Berliner Morgenpost renamed this gist May 9, 2016. 1 changed file with 0 additions and 0 deletions.
    0 gistfile1.txt → greencities.js
    View file
    File renamed without changes.
  4. Berliner Morgenpost revised this gist May 9, 2016. No changes.
  5. Berliner Morgenpost created this gist May 9, 2016.
    135 changes: 135 additions & 0 deletions gistfile1.txt
    View file
    Original file line number Diff line number Diff line change
    @@ -0,0 +1,135 @@
    // tables with germany shape and the cities we are using in our application
    var germany = ee.FeatureCollection('ft:1KDrYXBDlAx1fhcfmWRx7u_qqN2O_gwBNInjnGmnZ')
    var cities = ee.FeatureCollection('ft:1w4PgU3okfzwKFEIpH32oPMlOtei6hUWa9tkXv5Rt');

    // landsat properties we need to create our image collection over different years
    // we use a feature collection here, because we can easily filter it
    var landsats = ee.FeatureCollection([
    ee.Feature(null, { collection: ee.ImageCollection('LANDSAT/LT5_L1T_TOA'), nir: 'B4', red: 'B3', from: 1984, to: 1992 }),
    ee.Feature(null, { collection: ee.ImageCollection('LANDSAT/LT4_L1T_TOA'), nir: 'B4', red: 'B3', from: 1992, to: 1994 }),
    ee.Feature(null, { collection: ee.ImageCollection('LANDSAT/LT5_L1T_TOA'), nir: 'B4', red: 'B3', from: 1994, to: 1999 }),
    ee.Feature(null, { collection: ee.ImageCollection('LANDSAT/LE7_L1T_TOA'), nir: 'B4', red: 'B3', from: 1999, to: 2003 }),
    ee.Feature(null, { collection: ee.ImageCollection('LANDSAT/LT5_L1T_TOA'), nir: 'B4', red: 'B3', from: 2003, to: 2012 }),
    ee.Feature(null, { collection: ee.ImageCollection('LANDSAT/LE7_L1T_TOA'), nir: 'B4', red: 'B3', from: 2012, to: 2013 }),
    ee.Feature(null, { collection: ee.ImageCollection('LANDSAT/LC8_L1T_TOA'), nir: 'B5', red: 'B4', from: 2013, to: 2016 })
    ]);

    // color palette preview: http://gka.github.io/palettes/#colors=#101721,#282e36,#2f423d,#345744,#376d4b,#398552,#399b58,#37b35e,#30cc64,#24e56a,#00ff70|steps=11|bez=0|coL=0
    var palette = ['#101721','#282e36', '#2f423d', '#345744', '#376d4b', '#398552', '#399b58', '#37b35e', '#30cc64', '#24e56a', '#00ff70'];

    var startYear = 2005;
    var endYear = 2015;
    var startDay = '-06-01';
    var endDay = '-07-31';
    var ndviThresholdMin = 0.45;
    var ndviThresholdMax = 0.8;
    var cloudCoverMax = 5;
    var yearList = ee.List.sequence(startYear, endYear);

    Map.setCenter(10.5, 51.3, 6);

    // create an image collection with images between
    // start- and endyear in summer months for germany
    var accumulateImages = function(year, imageCollection){
    var startDate = ee.Date(ee.String(ee.Number(year).toInt()).cat(startDay));
    var endDate = ee.Date(ee.String(ee.Number(year).toInt()).cat(endDay));
    var landsat = getLandsatByYear(year);

    var ndviCollection = ee.ImageCollection(landsat.get('collection'))
    .filterBounds(germany)
    .filterDate(startDate, endDate)
    .filterMetadata('CLOUD_COVER', 'less_than', cloudCoverMax)
    .map(addNDVI(landsat));

    return ee.ImageCollection(imageCollection).merge(ndviCollection);
    }

    var resultCollection = yearList.iterate(accumulateImages, ee.ImageCollection([]));
    resultCollection = ee.ImageCollection(resultCollection);

    print(resultCollection);


    // to crossvalidate our result, we can randomly filter out 10% of the images
    // resultCollection = resultCollection
    // .randomColumn('random')
    // .sort('random')
    // .limit(resultCollection.size().multiply(0.9).toInt());


    // create collection that only has the ndvi band
    // and reduce that collection to one image with the median reducer
    var resultCollectionReduced = ee.ImageCollection(resultCollection)
    .select('ndvi')
    .reduce(ee.Reducer.median());

    // add greenamount and center properties for all cities
    cities = cities.map(function(feature){
    feature = feature.set('center', ee.Feature(feature.centroid()).geometry().coordinates());
    return feature.set('greenamount', addGreenamount(resultCollectionReduced, 0.45, feature));
    });

    // export data as geojson
    Export.table(cities, 'greencities_export', { fileFormat: 'GeoJSON' });

    // add clipped layer to the map
    Map.addLayer(
    resultCollectionReduced.clip(germany),
    { min: ndviThresholdMin, max: ndviThresholdMax, palette: palette },
    'NDVI map'
    );

    var ndviRGB = resultCollectionReduced.visualize({
    min: ndviThresholdMin,
    max: ndviThresholdMax,
    palette: palette
    });

    // export colored shape of germany
    Export.image(ndviRGB, 'germany_ndvi', {
    scale: 30,
    region: germany.geometry(),
    maxPixels: 130000000000
    });



    // helper functions

    function getLandsatByYear(year) {
    return landsats
    .filter(ee.Filter.lte('from', year)
    .and(ee.Filter.gt('to', year)))
    .first();
    }

    // add greenamount for a specific threshold for a feature
    function addGreenamount(ndviReduced, threshold, feature){
    var ndviAll = ndviReduced.gte(-1);
    var ndviHigh = ndviReduced.gte(threshold);

    var allReducedSum = ndviAll.reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: feature.geometry(),
    scale: 30
    });

    var partReducedSum = ndviHigh.reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: feature.geometry(),
    scale: 30
    });

    var value_all = ee.Number(allReducedSum.get('ndvi_median'));
    var value_high = ee.Number(partReducedSum.get('ndvi_median'));

    return value_high.divide(value_all).multiply(100);
    }


    // returns an image with a new ndvi band with the given landsat bands
    function addNDVI(landsat) {
    return function(image) {
    return image.addBands(image.normalizedDifference([landsat.get('nir'), landsat.get('red')]).rename('ndvi'));
    }
    }