GEE_classification

var rgbVis = {
  min: 0.0,
  max: 3000,
  bands: ['b4', 'b3', 'b2'],
};

Map.addLayer(image, rgbVis, 'Istanbul');

var ct=deniz.merge(gol).merge(bina)
.merge(orman).merge(arazi).merge(yol);

// Eğitim ve test örnekleri
var sample= ct.randomColumn();
var trainingsample= sample.filter('random<=0.70')
var validationsample= sample.filter('random>0.70')

  
// Overlay the point on the image to get training data.
var overlay = image.sampleRegions({
  collection: ct, 
  properties: ['sinif'], 
  scale: 20
});

// Train a classifier.
var classifier = ee.Classifier.smileRandomForest(100).train({
  features: overlay,  
  classProperty: 'sinif', 
  inputProperties: image.bandNames()
});

// // Classify the image.
var classified = image.classify(classifier);
Map.addLayer(classified, {min: 1, max: 6, palette: ['blue', 'green', 'red', 'green', 'yellow', 'gray']}, 'istanbul_class'); 

print (classified);


// Istanbul
var test = classified.sampleRegions({
  collection: validationsample,
  properties: ['sinif'],
  tileScale: 16,
  scale: 10,
});

var testConfusionMatrix = test.errorMatrix('sinif', 'classification')

// Kappa katsayısını hesapla
var kappa = testConfusionMatrix.kappa();

print('Kappa Katsayısı 2022:', kappa);





// Printing of confusion matrix may time out. Alternatively, you can export it as CSV
print('Confusion Matrix 2022', testConfusionMatrix);
print('Test Accuracy 2022', testConfusionMatrix.accuracy());

// Exporting Results
//************************************************************************** 

// Create a Feature with null geometry and the value we want to export.
// Use .array() to convert Confusion Matrix to an Array so it can be
// exported in a CSV file
var fc2022 = ee.FeatureCollection([
  ee.Feature(null, {
    'accuracy': testConfusionMatrix.accuracy(),
    'matrix': testConfusionMatrix.array()
  })
]);

print(fc2022);

Export.table.toDrive({
  collection: fc2022,
  description: 'Accuracy_2022',
  folder: 'earthengine',
  fileNamePrefix: 'accuracy_2022',
  fileFormat: 'CSV'
});


// Sınıf renkleri ve etiketleri
var classColors = ['blue', 'turquoise', 'red', 'green', 'brown', 'orange'];
var classLabels = ['Deniz', 'Göl', 'Bina', 'Orman', 'Arazi', 'Yol'];

// Lejant simgelerini oluştur
var legend = ui.Panel({
  style: {
    position: 'bottom-right',
    padding: '8px 15px'
  }
});

// Lejant etiketlerini ve renkleri ekle
var legendTitle = ui.Label({
  value: 'Sınıflar',
  style: {
    fontWeight: 'bold',
    fontSize: '16px',
    margin: '0 0 4px 0',
    padding: '0'
  }
});
legend.add(legendTitle);

var makeRow = function(color, label) {
  var colorBox = ui.Label({
    style: {
      backgroundColor: color,
      padding: '8px',
      margin: '0 0 4px 0'
    }
  });

  var description = ui.Label({
    value: label,
    style: { margin: '0 0 4px 6px' }
  });

  return ui.Panel({
    widgets: [colorBox, description],
    layout: ui.Panel.Layout.Flow('horizontal')
  });
};

for (var i = 0; i < classColors.length; i++) {
  legend.add(makeRow(classColors[i], classLabels[i]));
}

// Haritaya lejantı ekle
Map.add(legend);

// Lejantı içeren haritayı indir
var mapWithLegend = ui.Map();
mapWithLegend.addLayer(classified, {min: 1, max: 6, palette: classColors}, 'istanbul_class');
mapWithLegend.add(legend);
print(mapWithLegend);

Export.image.toDrive({
  image: mapWithLegend.toByte(),
  description: 'istanbul_class_with_legend',
  folder: 'earthengine',
  region: image.geometry(),
  scale: 10,
  maxPixels: 1e9
});