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Global_Urban_Extent_from_Landsat.js
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Global_Urban_Extent_from_Landsat.js
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// Global Urban Extent from Landsat
// by Dr. Paolo Gamba
// https://groups.google.com/d/msg/google-earth-engine-developers/guLCR1NvNnI/wQfARABvBgAJ
// Global script multi years 2.0
// ====================================== //
// Parameters to be set //
// ====================================== //
// General options
var area = "Center Asia"; // the name of the region in "Global Shape Table":
// North America, Center South America,
// North South America, South South America,
// Europe, North Africa, Center South Africa,
// Center Africa, Souht Africa Oceania
// Russia Japan, Center Asia, India, South Est Asia
// Indonesia, Indochina
//
var convex_hull = false; // apply the convex hull to the polygon of the chosen area
// NB: it must be true for Russia Japan and Oceania
//
var country_name = "Turkey"; // the name of selected country in Google "Countries of the World" table
// (set "" if you want to use the entire area instead of this country alone)
var province_name = ""; // selected province of Indonesia
// (set "" if you want to use the entire Indonesia or China, not use for other countries!)
var center_on = "Istanbul"; // Name of city on which center the zoom
// (set "" if you want to zoom on entire area)
var year = 2015; // starting year of the collection
var number_of_years =30; // total number of years to analyze (MAX 30)
var step = 10; // step progress (e.g. 1 year in 1 year, 2 years in 2 years, ecc.)
var collection_type = "greenest"; // greenest or standard or simplecomposite
var sensor = "L8"; // L5, L7, L8 or L45 (only before 1995!)
var cloud_cover = 1; // % of cloud cover
var waterfilter = true; // enable/disable water filter in classification
var zoom = 7; // level of zoom (center_on automatically set zoom+
// NDVI options
var mask_ndvi = false; // enable/disable the ndvi mask
var th_ndvi_high = 0.5; // 1st threshold for ndvi, put at zero all points in classification over this value
var th_ndvi_low = -0.5; // 2st threshold for ndvi, put at zero all points in classification under this value
// Elevation options
var mask_slope = false; // enable/disable the slope mask
var th_slope = 10; // threshold for slope in degrees, put at zero all points in classification over this value
var mask_dem = false; // enable/disable the slope mask
var th_dem = 2000; // threshold for slope in degrees, put at zero all points in classification over this value
var use_geometry = false; // if false apply dem mask to all image, if true only inside the rectangle
var dem_geometry = ee.Geometry.Rectangle(106.67450,-6.79826, 107.08649,-7.11452);
// Morphology options
var morphology_on = false; // enable/disable morphology
var operator = 'Window.min'; // 'Window.min' -> erode; 'Window.max' -> dilate
var radius1 = 400; // radius of the kernel closing/opening
var radius2 = 50; // radius of final closing;
var kernelType = 'circle'; // 'circle', 'square', 'cross', 'plus', 'octagon' or 'diamond'
var units = 'meters'; // units of measure: 'meters' or 'pixels'
var iterations = 1;
var class_or_flag = true; // enable/disable the new and method correction
var class_morph_radius = 7;
// Ground Truth
var GT_enable = false; // enable/disable ground truth
var GT_region = 'Southeast Asia'; // the name of the region in Universe of cities Table:
// Eastern Asia & Pacific
// Southeast Asia
// Western Asia
// South & Central Asia
// Europe & Japan
// Northern Africa
// Sub-Saharan Africa
// Land Rich Developed Count (north america)
// Latin America & the Carib
// Classifier parameters
var ts_type = 0; // set the type of training set to use:
// 0 -> fusion table(s) IMPORTANT! GO TO LINE 1081 TO SET WHICH FUSION TABLES TO USE
// 1 -> globcover random points
// 2 -> universe of cities random points
var multiclassifier = false; // false for single classification true for three classifiers
var multi_random = false; // if true generate 3 random sets instead of one using the seeds of the next line
// (WORKS ONLY FOR ts_type = 2)
var seeds = new Array(0,1,2);
var classifiers = new Array(5,9,6); // CHOOSE CLASSIFIER(S): (IMPORTANT! if multiclassifier is false only the first one is used)
// 0 = "FastNaiveBayes"
// 1 = "GmoMaxEnt"
// 2 = "Winnow"
// 3 = "MultiClassPerceptron"
// 4 = "Pegasos"
// 5 = "Cart"
// 6 = "RifleSerialClassifier" (aka Random Forest)
// 7 = "IKPamir"
// 8 = "VotingSvm"
// 9 = "MarginSvm"
var compute_area = false; // compute area of classified data
var area_scale = 300; // scale factor for area computation
// RANDOM POINTS TRAINING SET PARAMETERS
var num_points = 500; // num points to generate
// Globcover random points parameters
var lng = -48.90564; // coordinates of the quad
var lat = -0.890311;
var radius1 = 500; // radius of the kernel
var kernelType1 = 'square'; //'circle', 'square', 'cross', 'plus', 'octagon' or 'diamond'
// Universe of cities paramters:
// load universe of cities polygons (NOT CHANGE THIS LINE!)
var cities_table = ee.FeatureCollection('ft:1pQ-PrIEGrYa2Y3v9tsN1xwfYuqRIqOoDPARgpwzS');
// Choose the city or the cities to use
var selectedCities = cities_table.filter(ee.Filter.eq('MAIN_CITY', 'Istanbul')); // use this line only if there is one city!
/*var selectedCities = cities_table.filter(ee.Filter.or(ee.Filter.eq('MAIN_CITY', 'Kunming'), // use this command lines if there are more then one city
ee.Filter.eq('MAIN_CITY', 'Yuxi'),
ee.Filter.eq('MAIN_CITY', 'Qujing')));
*/
var use_all_cities = true; // set true to use all the cities of the current provice
// instead of the selected ones
// ====================================== //
// Loading basic data //
// ====================================== //
// LOAD POLYGONS
// find area in the world
var shapes = ee.FeatureCollection("ft:1rYMVQMw3hTr8IC2d3Ad8nHzHmQy8iBJCqAN20l_O");
var filter = shapes.filter(ee.Filter.eq('Area', area));
// Find Countries in the world
var countries = ee.FeatureCollection('ft:1tdSwUL7MVpOauSgRzqVTOwdfy17KDbw-1d9omPw');
var country = countries.filter(ee.Filter.eq('Country', country_name));
// Find provinces in the selected country
var province = "";
var provinces_table = "";
if(country_name === "Indonesia")
{
// find province of Indonesia
provinces_table = ee.FeatureCollection('ft:1ep1h4bOMUOEg0jwjmmn78T-L32zLbILZotS2lwUC');
province = provinces_table.filter(ee.Filter.eq('name', province_name));
}
else if(country_name === "China")
{
// Find Province of China
provinces_table = ee.FeatureCollection('ft:1h7DGU8yXMYqULLM3F4AsvLPOXiR5WTRswSgWLeHH');
province = provinces_table.filter(ee.Filter.eq('NAME_1', province_name));
}
// load main polygon
var choosen_zone = (province==="") ? ((country_name === "") ? filter : country) : province ;
var polygon1 = choosen_zone.geometry();
if(convex_hull===true && (choosen_zone === filter))
polygon1 = polygon1.convexHull();
// classifier types
var classifier_array = [ee.Classifier.naiveBayes(), ee.Classifier.gmoMaxEnt(), ee.Classifier.winnow(),
ee.Classifier.perceptron(), ee.Classifier.pegasosLinear(),
ee.Classifier.cart(), ee.Classifier.randomForest(),
ee.Classifier.ikpamir(), ee.Classifier.svm(), ee.Classifier.svm("Margin")];
// classifier names
var classifier_names = ["NaiveBayes", "GmoMaxEnt", "Winnow", "MultiClassPerceptron", "PegasosLinear",
"Cart", "RandomForest", "IKPamir", "Svm", "MarginSvm"];
// load elevation data
if(mask_slope===true || mask_dem===true)
var dem = ee.Image("CGIAR/SRTM90_V4");
// Load ground truth data
if(GT_enable===true)
{
var GT_regions = ee.FeatureCollection('ft:1pQ-PrIEGrYa2Y3v9tsN1xwfYuqRIqOoDPARgpwzS');
var GT_selectedRegions = GT_regions.filter(ee.Filter.eq('REGION', GT_region));
}
if(use_all_cities === true)
{
/*
// Universe of cities paramters:
// Join the two collection on their geometries if they're within 2km.
var joinFilter = ee.Filter.intersects('geometry', null, 'geometry', null);
var selectedCities = ee.Join.simple().apply(cities_table, province, joinFilter);
*/
// Choose the city or the cities to use
var allCities = cities_table.filter(ee.Filter.eq('COUNTRY', country_name));
var allProvinceCities = allCities.map(function(f) {
return f.set("Inside",
ee.Algorithms.If((f.geometry()).containedIn(polygon1), true, false));
});
selectedCities = allProvinceCities.filterMetadata('Inside', 'equals', true);
}
// check for incorrect parameters
if(ts_type!==2)
multi_random = false;
if(sensor==="L45")
collection_type = "standard";
// color palette for classification
var palette_list = new Array( {palette: '000000, ff0000'},
{palette: '000000, ffff00'},
{palette: '000000, 00ff00'},
{palette: '000000, ff00ff'},
{palette: '000000, 00ffff'},
{palette: '000000, FFA500'},
{palette: '000000, 0000ff'},
{palette: '000000, 800000'},
{palette: '000000, 8A2BE2'},
{palette: '000000, FA8072'},
{palette: '000000, 32CD32'},
{palette: '000000, F4A460'},
{palette: '000000, 1E90FF'},
{palette: '000000, F0E68C'},
{palette: '000000, 228B22'},
{palette: '000000, FFD700'},
{palette: '000000, E6E6FA'},
{palette: '000000, A0522D'},
{palette: '000000, FFC0CB'},
{palette: '000000, 66CDAA'},
{palette: '000000, FF8C00'},
{palette: '000000, 9932CC'},
{palette: '000000, 7FFF00'},
{palette: '000000, 7FFF00'},
{palette: '000000, CD853F'},
{palette: '000000, FAEBD7'},
{palette: '000000, DDA0DD'},
{palette: '000000, 808000'},
{palette: '000000, FFDAB9'},
{palette: '000000, 4169E1'});
// task name
var task_name = ((country_name === "") ? area : country_name) + "_from_" + year + "_to_" + (year-number_of_years) + "_" +
(collection_type==="greenest" ? "_L7_Annual_Greenest_TOA" : ("_" + sensor + "_TOA_cloud_cover_" + cloud_cover + "%")) +
(multiclassifier===true ? "_3_Classifiers" : "_"+classifier_names[classifiers[0]]) +
(morphology_on===true ? "_with_morphology":"");
// ====================================== //
// Fusion Tables //
// ====================================== //
// Jakarta
var ft1 = ee.FeatureCollection("ft:1JYib5GQkiNTMnt2rpVteos0jQeYE9jVXIhCE8_M");
ft1 = ft1.remap([100,101,102,103,104,105,106,107,108,109,200,201,202,203,204,205,206,207,208,209,210,211,212,213],
[1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Kota Bandung
var ft2 = ee.FeatureCollection("ft:1Z0VTqrovwUR0iujsgw6Y44_tLpjkFUeyivn2f2A");
ft2 = ft2.remap([100,101,102,103,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220],
[1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Kota Manado
var ft3 = ee.FeatureCollection("ft:1Dd68TvI-rYwNe9BHhDkdcUnUg17PKeLUdtwqTR4");
ft3 = ft3.remap([100,101,102,103,104,200,201,202,300,301,302,400,401,402],[1,1,1,1,1,0,0,0,0,0,0,0,0,0],"Number");
// Kuala Lumpur
var ft4 = ee.FeatureCollection("ft:1d_HFpj2iM3S8KBHubF5WEERwXaGSChraPbONdC0");
ft4 = ft4.remap([100,101,102,103,104,105,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216],
[1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Kalimatan
var ft5 = ee.FeatureCollection("ft:1m3KKK0ApX90x1bLOy-WU_XNitj8fVtw19lXLWZU");
ft5 = ft5.remap([100,101,102,200,201,202,203,204,205,206,207,208,209,210,211],[1,1,1,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Surabaya
var ft6 = ee.FeatureCollection("ft:10IZ12uFHlmGZMuzgOkk3HuvAuHdM2Iu10O7MPxk");
ft6 = ft6.remap([100,101,102,103,104,105,106,107,200,201,202,203,204,205,206,207,208,209,210,211,212,213],
[1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// San Paolo
var ft7 = ee.FeatureCollection("ft:1W-iBNcXotAJt06PO0EdANfOveMX8P9Sd_zxUK-w");
ft7 = ft7.remap([100,101,200,300,400,500,600,700,701,800,900,901,1000,1001,1100],[1,1,0,0,1,0,0,0,0,1,0,0,0,0,1],"Number");
// Rio
var ft8 = ee.FeatureCollection("ft:1TvLP4Xe3bJ-dwDyvxudiDxn1BUZieNmDlKelpDU");
ft8 = ft8.remap([100,101,200,201,202],[1,1,0,0,0],"Number");
// Recife
var ft9 = ee.FeatureCollection("ft:199COLkTjEFiYW09eF7kS6bCj6Ju-iWUk4pXwOhk");
ft9 = ft9.remap([100,101,200,201,202,203,204,205,206,207,208,209,210,211,212,213],[1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
//Curitiba
var ft10 = ee.FeatureCollection("ft:1lE5JidkBcWPtOf7jDurRezkTv72Ak4ECcCFw6I8");
ft10 = ft10.remap([100,101,200,201,202,203,204,205,206,207,208,209,210,211,212,213],[1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Buonos Aires
var ft11 = ee.FeatureCollection("ft:1-z1IpdYWOQe-d3xMTkxViQmWJCNfiX7stOWSf9s");
ft11 = ft11.remap([100,101,102,103,200,201,202,203,204,205], [1,1,1,1,0,0,0,0,0,0],"Number");
// Mexico City
var ft12 = ee.FeatureCollection("ft:1zgrzKKI2IUU_NcCIGzfSF9-GmTepsQTknlYNHok");
ft12 = ft12.remap([100,101,102,200,201,202,203,204,205,206,207], [1,1,1,0,0,0,0,0,0,0,0],"Number");
// Shanghai
var ft13 = ee.FeatureCollection("ft:1DUtGpGJzKiEf63LkUjJj7imQAiK0cxvawP2YQno");
ft13 = ft13.remap([100,101,102,200,201,202,203,204,300,301,400,401],[1,1,1,0,0,0,0,0,0,0,0,0],"Number");
// Jiangsu
var ft14 = ee.FeatureCollection("ft:1h4dMswHa9OPy4pFsHva8fSOi7ZtfhbkDQgbB3UE");
ft14 = ft14.remap([100,101,200,201,300,301,302,303,400,401],[1,1,0,0,0,0,0,0,0,0],"Number");
// Cairo
var ft15 = ee.FeatureCollection("ft:1S5DPVKswvcIczNqZLZXi3-YipExJ7Ez3ySFd3FE");
ft15 = ft15.remap([100,101,102,200,201,202,203,204], [1,1,1,0,0,0,0,0],"Number");
// Kinshasa-Brazzaville
var ft16 = ee.FeatureCollection("ft:1VmkJ_EKhOdcNjsyeJuH7Wt7AGzjZK0Il3NKJVFE");
ft16 = ft16.remap([100,101,102,200,201,202,203,204], [1,1,1,0,0,0,0,0],"Number");
// Istambul
var ft17 = ee.FeatureCollection("ft:1SI9e9QIEg2T7ZuBpVmz06VsSbK-Zx4Y-uNnTymo");
ft17 = ft17.remap([100,101,102,103,104,105,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216],
[1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Karachi
var ft18 = ee.FeatureCollection("ft:1MXNLNoQji75DduserB14ca88O1E2u_ZqrRDAcAI");
ft18 = ft18.remap([100,101,102,103,200,201,202,203,204], [1,1,1,1,0,0,0,0,0],"Number");
// Londra
var ft19 = ee.FeatureCollection("ft:1-ILTTjz3lvURZ7VC8q-zA0MvSln6bDz2dyj9KTc");
ft19 = ft19.remap([100,101,102,103,200,201,202,203,204,205,206,207,208,209,210,211,212,213],
[1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Manila
var ft20 = ee.FeatureCollection("ft:1VfVvegIbUX-Goi0tqjrLV2AJMxjFR9x5zXlW51c");
ft20 = ft20.remap([100,101,102,200,201,202,203,204,205], [1,1,1,0,0,0,0,0,0],"Number");
// Mumbai
var ft21 = ee.FeatureCollection("ft:13IcqxzMwTjePC2cCeVcKZy6d6_sM1CqrbPWEGkY");
ft21 = ft21.remap([100,101,102,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216],
[1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// New York
var ft22 = ee.FeatureCollection("ft:1zzRtyA3nIlwQJJl6en4cm6gjrjuOI3iB_N5B9qg");
ft22 = ft22.remap([100,101,102,200,201,202,203,204,205,206,207,208,209,210], [1,1,1,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Osaka
var ft23 = ee.FeatureCollection("ft:1gmLE5_GpE5aeamLRPaWgAcTmbzPNROXsLvexNvM");
ft23 = ft23.remap([100,101,102,103,200,201,202,203,204,205,206,207,208], [1,1,1,1,0,0,0,0,0,0,0,0,0],"Number");
// Seul
var ft24 = ee.FeatureCollection("ft:1hjcTW0AD0qApNiT9LDieZua94UbofkK6Dfd5IRg");
ft24 = ft24.remap([100,101,102,103,104,105,200,202,203,204,205,206,207], [1,1,1,1,1,1,0,0,0,0,0,0,0],"Number");
// Vietnam Dong Hoi
var ft25 = ee.FeatureCollection("ft:1btvyTxRJjrigjoYWt3rB8DakxRkhQPPIbRZp_xo");
ft25 = ft25.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114],[1,1,1,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Vietnam Ca Mau
var ft26 = ee.FeatureCollection("ft:1PM7cL_rCRf3cOTzVcWijydFXgWLsnuivyX5PYHw");
ft26 = ft26.remap([100,101,102,103,104,105,106,107,108,109],[1,1,1,0,0,0,0,0,0,0],"Number");
// Vietnam sud Ca Mau
var ft27 = ee.FeatureCollection("ft:1ELY75GK8n-6qYQkh87lKrrElQAvJOKhY3s8OM84");
ft27 = ft27.remap([100,101,102,103,104,105,106,107,108,109,110],[1,1,0,0,0,0,0,0,0,0,0],"Number");
// Vietnam confine cina
var ft28 = ee.FeatureCollection("ft:1-mKabryrKX81T86HEkOQeK9ywbnDwuUKxoPrCJY");
ft28 = ft28.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116],[1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Vietnam Ho Chi Minh
var ft29 = ee.FeatureCollection("ft:1B-wKLMVl1gJPvB-LG3et4F9ydAKI5A2gghk2eU4");
ft29 = ft29.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117],[1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Vietnam Da Nang
var ft30 = ee.FeatureCollection("ft:1jQKQJgEoYOKqihLXBEgkiFZ3JoA0jl238Uu4sc8");
ft30 = ft30.remap([100,101,102,103,104,105,106,107,108,109,110,111,112],[1,1,1,0,0,0,0,0,0,0,0,0,0],"Number");
// Vietnam Quang Tri
var ft31 = ee.FeatureCollection("ft:11INXL4EThmczTQuNvH28i33fyKNnEujsKvTxKZQ");
ft31 = ft31.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118],[1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Vietnam Phuroc Hoi
var ft32 = ee.FeatureCollection("ft:19tpEczaE170ez6x5ViPNDqeB7-rfoDFSv9mYVKM");
ft32 = ft32.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121],[1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Vietnam Est Ho Chi Minh
var ft33 = ee.FeatureCollection("ft:1Un2B568D-aG_T30POwgWnIW6NGXFlq6wNs0XhOY");
ft33 = ft33.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113],[1,1,1,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Vietnam Phan Rang
var ft34 = ee.FeatureCollection("ft:16sOtBxUs6lFjIj2426190MO79dObrr51Ksyh0WI");
ft34 = ft34.remap([100,101,102,103,104,105,106,107,108,109],[1,1,1,0,0,0,0,0,0,0],"Number");
// Vietnam Sud Hanoi
var ft35 = ee.FeatureCollection("ft:14TVtC6AD5SVoZF0PlHFS0eV-21BvfBgRbzEx1jQ");
ft35= ft35.remap([100,101,102,103,104,105,106,107,108,109,110,111,112],[1,1,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Vietnam Ho Chi Minh 2
var ft36 = ee.FeatureCollection("ft:1amd1UCF4ZYYFv7wipfM7P8c1jtcnC3CKlus23a0");
ft36 = ft36.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115],[1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Vietnam Hanoi
var ft37 = ee.FeatureCollection("ft:1lnHpA_ZlFoJ1ADqvLRno1PJV31PlTlsUXU9zwVQ");
ft37 = ft37.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115],[1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Africa
var ft38 = ee.FeatureCollection("ft:1Kh31mKZjrcJWXzG1MEQA00mW0-GJ8qyW4jGhlmw");
ft38 = ft38.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,
118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,
136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153],
[1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Dallas
var ft39 = ee.FeatureCollection("ft:10VY57FR5fcevkinyMiYvhv-bfzu-1w7bAWuV59XS");
ft39 = ft39.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,
122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142],
[1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Los Angeles
var ft40 = ee.FeatureCollection("ft:1xTuZ0Cja5BvyEysVGU36rTQolhk_Ad31-UWrD8a5");
ft40 = ft40.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,
122,123,124,125,126,127,128,129,130,131,132],
[1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Toronto 1998
var ft41 = ee.FeatureCollection("ft:15h2EZU85KFxcnGCgAQq0S39g7Z-ea8iO0h5GJegi");
ft41 = ft41.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,
122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137],
[1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Toronto 1999
var ft42 = ee.FeatureCollection("ft:1lxJbARYUw5AV_ULv_Qd9aYswHdWGJQ8fJ4j31Nor");
ft42 = ft42.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,
122,123,124,125,126,127,128,129,130,131,132,133,134,135],
[1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Vancouver 1999
var ft43 = ee.FeatureCollection("ft:1ln312_c7nvpPMoA648yqqzNJDR0HCKLr9gj7PKUx");
ft43 = ft43.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,
123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,
146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163],
[1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Vancouver 2009
var ft44 = ee.FeatureCollection("ft:1ln312_c7nvpPMoA648yqqzNJDR0HCKLr9gj7PKUx");
ft44 = ft44.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,
123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139],
[1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Dakar - Senegal 2009
var ft45 = ee.FeatureCollection("ft:1KgybS5ROczVfioCUnxNVXZL1wUHVTuejCmQDeXTs");
ft45 = ft45.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113],[1,1,1,0,0,0,0,0,0,0,0,0,0,0],"Number");
// Lagos - Nigeria 2009
var ft46 = ee.FeatureCollection("ft:1PVyuUjUMpaYIBQqhHSAl9_KG32hStLv_-8g0Z8wE");
ft46 = ft46.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,
121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,
142,143,144,145,146,147,148,149,150,151,152],
[1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Bangui - Repubblica Centro Africana 2009
var ft47 = ee.FeatureCollection("ft:1vNMbsMDdhdmLuy39PFMnzicD11PFCyfScF6UeTTw");
ft47 = ft47.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,
122,123,124,125,126,127],
[1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Addis Abeba - Etiopia 2009
var ft48 = ee.FeatureCollection("ft:1AujUNqTt7yZBzlkHZmk0JCZyRxShE6HnO_4pJdDu");
ft48 = ft48.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117],
[1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Nairobi - Kenya 2009
var ft49 = ee.FeatureCollection("ft:1VTTiG4F3uiKhbMKbdjCe41So2Hgk5c7OKls9P4hZ");
ft49 = ft49.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,
121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141],
[1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Luanda - Angola 2009
var ft50 = ee.FeatureCollection("ft:1wAFG1OyRRugDsBcIiGl6e3m1k60Syggf9PbQjvwC");
ft50 = ft50.remap([100,101,102,103,104,105,106,107,108,109,110,111], [1,1,0,0,0,0,0,0,0,0,0,0], "Number");
// Antanananarivo - Madagascar 2009
var ft51 = ee.FeatureCollection("ft:1BUB0WKrrgj8oEa4Ct6PXynxlV86JemV55f1-2Mgm");
ft51 = ft51.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,],
[1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Casablanca - Marocco 2009
var ft52 = ee.FeatureCollection("ft:1w1xp3taWI5lXmrN96PkVvNgU8p8nPSx_MnJS26ey");
ft52 = ft52.remap([100,101,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,
121,122,123,124,125,126,127,128,129,130,131,132,133,134],
[1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Tamanrasset - Algeria 2009
var ft53 = ee.FeatureCollection("ft:1F5i8QzejxFjH3o4xmiKD1b5CF9EhtYLzgEYFL5-R");
ft53 = ft53.remap([101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119],
[1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Hurgada - Egypt 2009
var ft54 = ee.FeatureCollection("ft:1RwW2jFBdUEtxlFWQRIM0R1jneXHlXYRlS_k0dCSu");
ft54 = ft54.remap([101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116],
[1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Sirte - Lybia 2009
var ft55= ee.FeatureCollection("ft:1H8wOhLPCIWYXayXjcwcQu8PDv3m-_tQd-ZN4L6M1");
ft55 = ft55.remap([101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116],
[1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Cercle de Dire - Mali 2009
var ft56= ee.FeatureCollection("ft:1bkRPcvqxJoEQupltGhx1XSH0sKsivXIH_152-EFF");
ft56 = ft56.remap([101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121],
[1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Maputo - Mozambico 2009
var ft57 = ee.FeatureCollection("ft:1U6j_VE9vGNk6C4tg1wrEV2Hh7KNIB4EjBUIjmJti");
ft57 = ft57.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,
121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138],
[1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Harare - Zimbawe 2009
var ft58 = ee.FeatureCollection("ft:1x4nBwW3-Hn-PVexdWk3nPN49aH8Usd8l0ljJRsa0");
ft58 = ft58.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,
123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144],
[1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Johannesburg - South Africa 2009
var ft59 = ee.FeatureCollection("ft:1Ye-K6RsCf4ixpUgwQ4r1OSuPFQ0xjB6CVniZ0NIA");
ft59 = ft59.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,
123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141],
[1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Durban - South Africa 2009
var ft60 = ee.FeatureCollection("ft:1fSLrnYRnBmMkZxdrSnIeQr9_TdbKifI-7HPrDk9u");
ft60 = ft60.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,
123,124,125,126,127,128,129],
[1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Cape Town - South Africa 2009
var ft61 = ee.FeatureCollection("ft:1om0_icjG1Wz90_ACpOUU4E50IHZgU9-57HH_dNAS");
ft61 = ft61.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,
123,124,125,126,127,128,129,130,131,132,133,134],
[1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "Number");
// Tranining set Andres
var ftA4 = ee.FeatureCollection("ft:1YZfa286rC-MiQLdGGanFfvoOFcaACq79D_guqeB2");
ftA4 = ftA4.remap([100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,
121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142],
[1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
"Number");
var ftA6 = ee.FeatureCollection("ft:1E_sQ9l7-uQbuEfGgCcuHlp-fWB6MQJqgFFb0KQqo");
ftA6 = ftA6.remap([100,101,102,103,104,200,201,202,300,301,302,400,401,402],
[1,1,1,1,1,0,0,0,0,0,0,0,0,0],"Number");
// India FT66 Test punti
var ft66 = ee.FeatureCollection("ft:1w65fJ11u4BeJuX0xQDsWCloB5Y1_ZF-h2Cc0qciz");
ft66 = ft66.remap([100,200,300,400,500,600,700,800,900,1000,1100,1200],
[1,0,0,0,0,0,0,0,0,0,0,0], "Number");
// ====================================== //
// General Functions //
// ====================================== //
// autocenter map
function autoCenterMap(polygon, zoom)
{
var centroid = polygon.centroid().getInfo().coordinates;
Map.setCenter(centroid[0],centroid[1],zoom);
}
// create a quad polygon from lat and lon
function getPoly(lng, lat)
{
var poly = ee.Geometry.Polygon([[lng-1, lat-1],
[lng-1, lat+1],
[lng+1, lat+1],
[lng+1, lat-1] ]);
return poly;
}
// Return an image in flag is 0 or the median of a collection if flag is 1
function img_or_collection(input, flag)
{
if(flag===0)
return input;
else if(flag===1)
return input.median();
}
// Return an image in flag is 0 or the median of a collection if flag is 1
function input_selector(year, collection_type, sensor, cloud_cover, polygon)
{
var collection, collection1, collection2, collection3;
var coll;
if(collection_type === "greenest")
{
coll = (sensor==='L5') ? 'LT5_L1T_ANNUAL_GREENEST_TOA/' :
((sensor==='L7') ? 'LE7_L1T_ANNUAL_GREENEST_TOA/' : 'LC8_L1T_ANNUAL_GREENEST_TOA/');
return ee.Image(coll + year).clip(polygon);
}
else if(collection_type === "standard")
{
coll = (sensor==='L5' || sensor==='L45') ? 'LT5_L1T_TOA' : ((sensor==='L7') ? 'LE7_L1T_TOA' : 'LC8_L1T_TOA');
// check for combo L4-L5
if(sensor==='L45')
{
collection1 = ee.ImageCollection("LT5_L1T_TOA").filterDate(new Date(year+"-01-01"), new Date(year+"-12-31"))
.filterMetadata('catalog_cloud_cover', 'less_than', cloud_cover)
.filterBounds(polygon);
collection2 = ee.ImageCollection("LT4_L1T_TOA").filterDate(new Date(year+"-01-01"), new Date(year+"-12-31"))
.filterMetadata('catalog_cloud_cover', 'less_than', cloud_cover)
.filterBounds(polygon);
collection = ee.ImageCollection(collection1.merge(collection2));
return collection.median().clip(polygon);
}
else
{
collection = ee.ImageCollection(coll).filterDate(new Date(year+"-01-01"), new Date(year+"-12-31"))
.filterMetadata('catalog_cloud_cover', 'less_than', cloud_cover)
.filterBounds(polygon);
return collection.median().clip(polygon);
}
}
else if(collection_type === "simplecomposite")
{
coll = (sensor==='L5') ? 'LT5_L1T' : ((sensor==='L7') ? 'LE7_L1T' : 'LC8_L1T');
collection = ee.ImageCollection(coll).filterDate(new Date(year+"-01-01"), new Date(year+"-12-31"))
//.filterMetadata('catalog_cloud_cover', 'less_than', cloud_cover)
.filterBounds(polygon);
var simpleComp = ee.Algorithms.Landsat.simpleComposite(collection, 50, 10);
return simpleComp.clip(polygon);
}
}
// ====================================== //
// Morphology Functions //
// ====================================== //
// launch matematical morphology
function morphology(image, operator, radius, kernelType, units, iterations)
{
var morph;
if(image.getInfo().bands[0].data_type.precision == 'int')
{
morph = ee.call(operator, image, radius, kernelType, units, iterations);
}
else if(image.getInfo().bands[0].data_type.precision == 'float' || image.getInfo().bands[0].data_type.precision == 'double')
{
morph = ee.call(operator, image.multiply(255).toInt(), radius, kernelType, units, iterations);
}
return morph;
}
// opening function
function opening(image, radius, kernelType, units)
{
var erode = morphology(image, 'Window.min', radius, kernelType, units, 1);
var open = morphology(erode, 'Window.max', radius, kernelType, units, 1);
return open;
}
// closing function
function closing(image, radius, kernelType, units)
{
var dilate = morphology(image, 'Window.max', radius, kernelType, units, 1);
var closure = morphology(dilate, 'Window.min', radius, kernelType, units, 1);
return closure;
}
// Morphology adjustment
function morph_adjustment(img1, radius1, radius2, kernelType)
{
// Opening
var morph = closing(img1, radius1, kernelType, "meters");
morph = opening(morph, radius1, kernelType, "meters");
//Map.addLayer(ee.Image(0).mask(morph), {palette: '000000, 77ff00'}, 'Classified + clos-op', false);
// And
var result = img1.and(morph);
result = closing(result, radius2, kernelType, "meters");
return result;
}
// ====================================== //
// NDVI Functions //
// ====================================== //
// NDVI computing
function NDVI(image)
{
return image.expression('((b("B4") - b("B3")) / (b("B4") + b("B3")))');
}
// ====================================== //
// NDSV Functions //
// ====================================== //
// NDSV computing
function NDSV(image, b1, b2)
{
//print('((b(\"' + b2 + '\") - b(\"' + b1 + '\")) / (b(\"' + b2 + '\") + b(\"'+ b1 + '\"))) ');
return image.expression(
'((b(\"' + b2 + '\") - b(\"' + b1 + '\")) / (b(\"' + b2 + '\") + b(\"'+ b1 + '\"))) ');
}
// Compute all the 15 bands of NDSV
function create_ndsv_img_15(image)
{
image = image.float();
//print("NDSV for L5 or L7");
var band_1_2_image = NDSV(image,'B1','B2');
var band_1_3_image = NDSV(image,'B1','B3');
var band_1_4_image = NDSV(image,'B1','B4');
var band_1_5_image = NDSV(image,'B1','B5');
var band_1_7_image = NDSV(image,'B1','B7');
var band_2_3_image = NDSV(image,'B2','B3');
var band_2_4_image = NDSV(image,'B2','B4');
var band_2_5_image = NDSV(image,'B2','B5');
var band_2_7_image = NDSV(image,'B2','B7');
var band_3_4_image = NDSV(image,'B3','B4');
var band_3_5_image = NDSV(image,'B3','B5');
var band_3_7_image = NDSV(image,'B3','B7');
var band_4_5_image = NDSV(image,'B4','B5');
var band_4_7_image = NDSV(image,'B4','B7');
var band_5_7_image = NDSV(image,'B5','B7');
band_1_2_image = band_1_2_image.addBands(band_1_3_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_1_4_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_1_5_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_1_7_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_2_3_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_2_4_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_2_5_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_2_7_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_3_4_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_3_5_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_3_7_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_4_5_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_4_7_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_5_7_image,null,false);
var bandnames = ["ndsv_1_2", "ndsv_1_3", "ndsv_1_4", "ndsv_1_5", "ndsv_1_7", "ndsv_2_3", "ndsv_2_4", "ndsv_2_5", "ndsv_2_7", "ndsv_3_4", "ndsv_3_5", "ndsv_3_7", "ndsv_4_5", "ndsv_4_7", "ndsv_5_7"];
var ndsv = band_1_2_image.select(['.*'], bandnames);
return ndsv;
}
// Compute all the 15 bands of NDSV for Landsat8
function create_ndsv_img_15_L8(image)
{
image = image.float();
//print("NDSV for L8");
var band_1_2_image = NDSV(image,'B2','B3');
var band_1_3_image = NDSV(image,'B2','B4');
var band_1_4_image = NDSV(image,'B2','B5');
var band_1_5_image = NDSV(image,'B2','B6');
var band_1_7_image = NDSV(image,'B2','B7');
var band_2_3_image = NDSV(image,'B3','B4');
var band_2_4_image = NDSV(image,'B3','B5');
var band_2_5_image = NDSV(image,'B3','B6');
var band_2_7_image = NDSV(image,'B3','B7');
var band_3_4_image = NDSV(image,'B4','B5');
var band_3_5_image = NDSV(image,'B4','B6');
var band_3_7_image = NDSV(image,'B4','B7');
var band_4_5_image = NDSV(image,'B5','B6');
var band_4_7_image = NDSV(image,'B5','B7');
var band_5_7_image = NDSV(image,'B6','B7');
band_1_2_image = band_1_2_image.addBands(band_1_3_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_1_4_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_1_5_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_1_7_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_2_3_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_2_4_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_2_5_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_2_7_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_3_4_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_3_5_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_3_7_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_4_5_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_4_7_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_5_7_image,null,false);
var bandnames = ["ndsv_1_2", "ndsv_1_3", "ndsv_1_4", "ndsv_1_5", "ndsv_1_7", "ndsv_2_3", "ndsv_2_4", "ndsv_2_5", "ndsv_2_7", "ndsv_3_4", "ndsv_3_5", "ndsv_3_7", "ndsv_4_5", "ndsv_4_7", "ndsv_5_7"];
var ndsv = band_1_2_image.select(['.*'], bandnames);
return ndsv;
}
// Compute all the 6 bands of NDSV
function create_ndsv_img_6(image)
{
image = image.float();
var band_1_2_image = 0;
var band_1_3_image = 0;
var band_1_4_image = 0;
var band_2_3_image = 0;
var band_2_4_image = 0;
var band_3_4_image = 0;
if(image.getInfo().bands[0].id == 1)
{
band_1_2_image = NDSV(image,'1','2');
band_1_3_image = NDSV(image,'1','3');
band_1_4_image = NDSV(image,'1','4');
band_2_3_image = NDSV(image,'2','3');
band_2_4_image = NDSV(image,'2','4');
band_3_4_image = NDSV(image,'3','4');
}
else if(image.getInfo().bands[0].id == 4){
band_1_2_image = NDSV(image,'4','5');
band_1_3_image = NDSV(image,'4','6');
band_1_4_image = NDSV(image,'4','7');
band_2_3_image = NDSV(image,'5','6');
band_2_4_image = NDSV(image,'5','7');
band_3_4_image = NDSV(image,'6','7');
}
band_1_2_image = band_1_2_image.addBands(band_1_3_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_1_4_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_2_3_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_2_4_image,null,false);
band_1_2_image = band_1_2_image.addBands(band_3_4_image,null,false);
var bandnames = ["ndsv_1_2", "ndsv_1_3", "ndsv_1_4", "ndsv_2_3", "ndsv_2_4", "ndsv_3_4"];
var ndsv = band_1_2_image.select(['.*'], bandnames);
return ndsv;
}
// Compute all the bands of NDSV depending on the image
function create_ndsv_img(image)
{
if(sensor==='L8')
return create_ndsv_img_15_L8(image);
else if(sensor==='L7' || sensor==='L5' || sensor === 'L45')
return create_ndsv_img_15(image);
else
return create_ndsv_img_6(image);
}
// ====================================== //
// Classifier //
// ====================================== //
// generate training set of random points (Universe of cities)
function ts_generator(poly, numPoints, selectedCities,seed)
{
seed = (seed === undefined) ? 0 : seed;
var random_points = ee.FeatureCollection.randomPoints(poly, numPoints, seed);
var geom = ee.Feature(selectedCities.geometry());
var training_set = random_points.map(function (feature) {
return feature.set("Number",
ee.Algorithms.If(feature.containedIn(geom), 1, 0));
});
var numPoints_NotUrban = training_set.filter(ee.Filter.eq("Number", 0)).getInfo().features.length;
//print("not urban: " + numPoints_NotUrban);
var numPoints_Urban = training_set.filter(ee.Filter.eq("Number", 1)).getInfo().features.length;
//print("urban: " + numPoints_Urban);
var numPoits_toAdd = (numPoints_NotUrban-numPoints_Urban)/2;
random_points = ee.FeatureCollection.randomPoints(selectedCities, numPoits_toAdd);
var urban_points = random_points.map(function (feature) {
return feature.set("Number",1);
});
training_set = training_set.merge(urban_points);
return training_set;
}
// return random point inside a polygon
function getPoints(polygon, num)
{
var random_points = ee.FeatureCollection.randomPoints(polygon, num);
var input_train_img = ee.Image('ESA/GLOBCOVER_L4_200901_200912_V2_3').select("1");
var blank = ee.Image(0);
var output = blank.where(input_train_img, 1);
var mask_img = output.where(input_train_img.lt(190).or(input_train_img.gt(190)),0);
var x = mask_img.clip(polygon);
var x_erode = morphology(x, 'Window.min', radius1, kernelType1, 'meters', 1);
var x_dilate = morphology(x, 'Window.max', radius1, kernelType1, 'meters', 1);
var morph = x_erode.add(x_dilate);
//Map.addLayer(morph, null, 'Input data morph');
var trainingImage_ = ee.Image.cat(ee.Image(0), morph);
var trainingPoints = ee.apply("ReduceToVectors",{
image: trainingImage_,
reducer: ee.Reducer.mean(), // The particular reducer doesn't matter, since it is a point geometry.
geometry: random_points,
scale: 30, // Scale at which the image is sampled.
geometryType: 'centroid' // The output will be a point.
});
trainingPoints = trainingPoints.filter(ee.Filter.neq("mean", 1));
trainingPoints = trainingPoints.remap([0,2],[0,1],"mean");
var renamed_points = trainingPoints.map(function (feature) {
return feature.set("Number", feature.get("mean"));
});
return renamed_points;
}
// select and create the fusion tables
function training_selector(ft_array)
{
var index;
var merge_ft = ft_array[0];
for (index = 1; index < ft_array.length; index++)
{
merge_ft = merge_ft.merge(ft_array[index]);
}
return merge_ft;
}
// classificiation
function classifier(img, ft, c, crs)
{
crs = (crs === undefined) ? "EPSG:4326" : crs;
var training = img.sampleRegions( ft, ["Number"], null,
ee.Projection(crs, [8.9831528411952135e-05, 0, -180, 0, -8.9831528411952135e-05, 90]));
var trained = c.train(training, "Number", img.bandNames());
/* OLD INSTRUCTION
var y = ee.apply("ClassifyImage",{
"image": img,
"classifierImage": training
});
*/