// Example GEE Code - Abulug catchment

// v2.0	February 2025 
// richard.boothroyd@glasgow.ac.uk 
// richard.boothroyd@liverpool.ac.uk

// Note: The code has been migrated to Landsat Collection 2. 

// 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 up user-defined parameters:

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

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

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 

// Params for visualisations:
var params_true = {crs: 'EPSG:4326', region: roi, min: 0.0, max: 0.3, bands: ["Red", "Green", "Blue"], dimensions: 1000};
var params_false = {crs: 'EPSG:4326', region: roi, min: 0.0, max: 0.3, bands: ["Swir1", "Red", "Green"], dimensions: 1000};

// Standardise band names, merge Landsat data*/
var bn9 = ['SR_B1', 'SR_B2', 'SR_B3', 'SR_B4', 'SR_B6', 'QA_PIXEL', 'SR_B5', 'SR_B7'];
var bn8 = ['SR_B1', 'SR_B2', 'SR_B3', 'SR_B4', 'SR_B6', 'QA_PIXEL', 'SR_B5', 'SR_B7'];
var bn7 = ['SR_B1', 'SR_B1', 'SR_B2', 'SR_B3', 'SR_B5', 'QA_PIXEL', 'SR_B4', 'SR_B7'];
var bn5 = ['SR_B1', 'SR_B1', 'SR_B2', 'SR_B3', 'SR_B5', 'QA_PIXEL', 'SR_B4', 'SR_B7'];
var bns = ['uBlue', 'Blue', 'Green', 'Red', 'Swir1', 'QA_PIXEL', 'Nir', 'Swir2'];

var ls5 = ee.ImageCollection("LANDSAT/LT05/C02/T1_L2")
var ls7 = (ee.ImageCollection("LANDSAT/LE07/C02/T1_L2")
  .filterDate('1999-04-15', '2003-05-30')) // exclude LE7 images that affected by failure of Scan Line Corrector (SLC) 
var ls8 = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2")
var ls9 = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2")


var applyScaleFactors = function(image) {
  var opticalBands = image.select('SR_B.').multiply(0.0000275).add(-0.2);
  return image.addBands(opticalBands, null, true);
}

var ls5_scaled = ls5.map(applyScaleFactors).select(bn5, bns);
var ls7_scaled = ls7.map(applyScaleFactors).select(bn7, bns);
var ls8_scaled = ls8.map(applyScaleFactors).select(bn8, bns);
var ls9_scaled = ls9.map(applyScaleFactors).select(bn9, bns);
var merged_scaled = ls5_scaled.merge(ls7_scaled).merge(ls8_scaled).merge(ls9_scaled);


// 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_scaled.filterDate(sDate_T1, eDate_T1) 
                 .filterBounds(roi) 
                 .map(function(image) { 
                 var qaMask = image.select('QA_PIXEL').bitwiseAnd(parseInt('11111', 2)).eq(0)                 
                    return image.updateMask(qaMask).resample('bicubic').set('system:time_start',sDate_T1); 
                   }); 

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

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').clip(roi);

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

//var size = Active_Channel.getInfo()
//print(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.image.toDrive({
    image: active_map,
    description: (river + '_' + date),
    fileNamePrefix: (river + '_' + date),
    region: roi,
    scale: 10,
    fileFormat: 'GeoTIFF',  
    folder: folder,
    maxPixels: 1e12,  
  })
}