How To Apply Change Detection Using Google Earth Engine

Change detection for GIS(geographical information systems) is a process that measures how the attributes of a particular area have changed between two or more time periods. Change detection often involves comparing aerial photographs or satellite imagery of the area taken at different times. Change detection has been widely used to assess shifting cultivation, urban growth, impact of natural disasters like tsunamis, earthquakes, and use/land cover changes.

I will instruct you how to appky change detection using google earth engine

// Import LAndsat Images
var sr = ee.ImageCollection("LANDSAT/LC08/C01/T1_SR");
// These are the input features:
var bands = ['B2', 'B3', 'B4', 'B5', 'B6', 'B7'];
// Function to composite Landsat 8 SR imagery and atmospheric correction.
var compositeFunctionSR = function(image) {
// Bits 3 and 5 are cloud shadow and cloud, respectively.
var cloudShadowBitMask = ee.Number(2).pow(3).int();
var cloudsBitMask = ee.Number(2).pow(5).int();
var qa = image.select('pixel_qa');
// Both flags should be set to zero, indicating clear conditions. 
var mask = qa.bitwiseAnd(cloudShadowBitMask).eq(0).and(
            qa.bitwiseAnd(cloudsBitMask).eq(0));
return image
// Scale the data to reflectance and temperature.
      .select(['B[1-7]']).multiply(0.0001)
      .addBands(image.select(['B10', 'B11']).multiply(0.1))
      .updateMask(mask);
};
var compositeBefore = sr.filterDate('2016-02-01', '2016-08-01')
                          .map(compositeFunctionSR)
                          .median();
var compositeLater = sr.filterDate('2017-02-01', '2017-08-01')
                          .map(compositeFunctionSR)
                          .median();
var rgbVis = {bands: ['B4', 'B3', 'B2'], min: 0, max: 0.3};
Map.addLayer(compositeBefore, rgbVis, 'compositeBefore');
Map.addLayer(compositeLater, rgbVis, 'compositeLater');
// NBR:
var nbrFunction = function(image) {
  return image.addBands(image.expression(
    '(nir - 0.0001 * swir * thermal) / ' +
    '(nir + 0.0001 * swir * thermal)', {
      nir: image.select('B5'),
      swir: image.select('B7'),
      thermal: image.select('B11')
    }).rename('NBR').clamp(-1, 1));
};
var nbrBefore = nbrFunction(compositeBefore).select('NBR');
Map.addLayer(nbrBefore, {min: -0.2, max: 1}, 'nbrBefore');
var nbrLater = nbrFunction(compositeLater).select('NBR');
Map.addLayer(nbrLater, {min: -0.2, max: 1}, 'nbrLater');
var dNBRt = nbrLater.subtract(nbrBefore);
Map.addLayer(dNBRt, {min: -0.3, max: 0}, 'dNBRt');
var burned = dNBRt.lt(-0.02).rename('burned');
Map.addLayer(burned.updateMask(burned), {palette: ['red']}, 'burned');

On the layer tab, you should see the before and after burnt area, nbr and composite before and after.