// Example GEE Code - Abulug catchment

// v1.0 November 2021
// richard.boothroyd@glasgow.ac.uk 

// Note: Landsat Collection 1 is now deprecated in Google Earth Engine.  Please use the "GEE_Code_Abulug_Migrated.txt".  

// Goal: Export binary images of the active river channel over 2-year time periods (to calculate locational probabilities).  No binary image cleaning is applied within GEE. 
// Note: This code can take a while to run (approx 30 mins), to reduce the run-time comment out some of the yearRanges. 




// Sets user-defined parameters:

var folder = ('Locational_Probability_Example');
var river = ('Abulug');

var scale = 30;
var mndwi_param = -0.4;
var ndvi_param = 0.20;

var buffer_1 = ee.FeatureCollection('users/rjboothroyd1/WP1_20_Largest_Trunk_Only_Buffered_Simplified/Abulug_3000m_Buffered_500m_Simplified');
var buffer_1 = buffer_1.geometry().transform('EPSG:4326', 10); 
var roi = buffer_1;
Map.addLayer(roi, {color: 'FFFF00'}, 'ROI');
Map.centerObject(roi,12)

var sites = [
  [roi]
]

var yearRanges = [
[1988, 1990],
[1990, 1992],
[1992, 1994],
[1994, 1996],
[1996, 1998],
[1998, 2000],
[2000, 2002],
[2002, 2004],
[2004, 2006],
[2006, 2008],
[2008, 2010],
[2010, 2012],
[2012, 2014],
[2014, 2016],
[2016, 2018],
[2018, 2020]
]


// Prepares Landsat dataset and multispectral functions 

// Standardise band names, merge Landsat data*/

var bn8 = ['B1', 'B2', 'B3', 'B4', 'B6', 'pixel_qa', 'B5', 'B7'];
var bn7 = ['B1', 'B1', 'B2', 'B3', 'B5', 'pixel_qa', 'B4', 'B7'];
var bn5 = ['B1', 'B1', 'B2', 'B3', 'B5', 'pixel_qa', 'B4', 'B7'];
var bns = ['uBlue', 'Blue', 'Green', 'Red', 'Swir1', 'BQA', 'Nir', 'Swir2'];

var ls5 = ee.ImageCollection("LANDSAT/LT05/C01/T1_SR").select(bn5, bns);
var ls7 = (ee.ImageCollection("LANDSAT/LE07/C01/T1_SR")
  .filterDate('1999-04-15', '2003-05-30') // exclude LE7 images that affected by failure of Scan Line Corrector (SLC) 
  .select(bn7, bns));
var ls8 = ee.ImageCollection("LANDSAT/LC08/C01/T1_SR").select(bn8, bns);
var merged = ls5.merge(ls7).merge(ls8);


// Functions for active river belt classification
var Ndvi = function(image) {
  // calculate normalized difference vegetation index
  var ndvi = image.normalizedDifference(['Nir', 'Red']).rename('ndvi');
  return(ndvi);
};

var Mndwi = function(image) {
  // calculate modified normalized difference water index
  var mndwi = image.normalizedDifference(['Green', 'Swir1']).rename('mndwi');
  return(mndwi);
};


// Loop over years

sites.forEach(function (site) {
  yearRanges.forEach(function (yearRange) {
    exportTimeseries(site, yearRange)
  })
})

function exportTimeseries(site, yearRange) {
  var sDate_T1 = ee.Date.fromYMD(yearRange[0], 1, 1);
  var eDate_T1 = ee.Date.fromYMD(yearRange[1], 1, 1);


// Filter date range, roi and apply simple cloud processing

var imgCol = merged.filterDate(sDate_T1, eDate_T1) 
                 .filterBounds(roi) 
                 .map(function(image) { 
                    var cloudShadowBitMask = 1 << 3; 
                    var cloudsBitMask = 1 << 5; 
                    var qa = image.select('BQA'); 
                    var mask = qa.bitwiseAnd(cloudShadowBitMask).eq(0) 
                                 .and(qa.bitwiseAnd(cloudsBitMask).eq(0)); 
                    return image.updateMask(mask).resample('bicubic').multiply(0.0001).clip(roi).set('system:time_start',sDate_T1); 
                   }); 

// print(imgCol.limit(1)); 
// print(imgCol.size(),'T1: Number of tiles used'); 
// print(imgCol);


// Apply approach to classify active channel:

var mndwi_scaled = (imgCol.map(Mndwi).map(function(i) { return i.unitScale(-0.4, 1).clamp(0, 1) }).reduce(ee.Reducer.percentile([10])))
var mndwi_out = (mndwi_scaled.gt(0));
var ndvi_scaled = (imgCol.map(Ndvi).map(function(i) { return i.unitScale(-1, 0.2).clamp(0, 1) }).reduce(ee.Reducer.percentile([10])))
var ndvi_out = (ndvi_scaled.lt(1));
var active_map = (mndwi_out).and(ndvi_out).rename('active');

var size = imgCol.size().getInfo()
var list = imgCol.toList(size)

for (var n=0; n<size; n++) {
  var image = ee.Image(list.get(n))
  var date = ee.Date(image.get('system:time_start')).format('YYYY');
  date = date.getInfo();
}


// Export binary images to Google Drive [scale set to 10 m to match DEM resolution]

  Export.image.toDrive({
    image: active_map,
    description: (river + '_' + date),
    fileNamePrefix: (river + '_' + date),
    region: roi,
    scale: 10,
    fileFormat: 'GeoTIFF',  
    folder: folder,
    maxPixels: 1e12,  
  })
}