Example_Code.txt

//upload CSV as a fusion table 

//declare it as a variable
var points = ee.FeatureCollection("ft:197TBk5hVl_MrOdL8R_x53otnJnRzrmWNwv-NPIRY");
// Zoom to a location.
Map.centerObject(points, 10);

//Visualize points on map
Map.addLayer(points, {}, 'samples');
print(points);
//Pick a data source - Landsat 8 7 5 
var l8 = ee.ImageCollection('LANDSAT/LC8_L1T_TOA');

//Filter by date 
var l8_2015 = l8.filterDate('2016-01-01', '2016-12-31');

//Filter by boundaries
//First draw a polygon
var l815s = l8_2015.filterBounds(geometry);

// This will sort from least to most cloudy.
var sorted = l815s.sort('CLOUD_COVER');

// Get the first (least cloudy) image.
var scene = ee.Image(sorted.first());

//add true color composite 
var visParams = {bands: ['B4', 'B3', 'B2'], max: 0.3};
Map.addLayer(scene, visParams, 'true-color composite');

//get NDVI
var ndvi = scene.normalizedDifference(['B5', 'B4']).rename('NDVI');

//Adding NDVI to a collection as another band
var addVI = function(image) {
  var ndvi = image.normalizedDifference(['B5', 'B4']).rename('NDVI')
  return image
    .addBands([ndvi])
};

var collection1 = l8_2015.map(addVI);  

//get min NDVI
var median = collection1.reduce(ee.Reducer.median());
//Export NDVI values to a table in drive
print(median);
Map.addLayer(median.select('NDVI_median'), {min: -0.8, max: 0.8, palette: 'black, green'},'NDVI')

var medianV = median.reduceRegions({
  reducer: ee.Reducer.median(),
  collection: points,
  scale: 30,
}); 
  
Export.table.toDrive({
  collection: medianV,
  fileNamePrefix: 'xx',
  folder: 'xx',
  description: 'xx',
  fileFormat: 'CSV'
});

Export.image.toDrive({
  image: median,
  description: 'xx',
  folder: 'xx', 
  fileNamePrefix: 'xx',
  'maxPixels': 1e13,
  scale: 30,
  region: geometry 
});