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harmonizationTutorial.js
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harmonizationTutorial.js
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/*
This tutorial is made to demonstrate the workflow of harmonizing Landsat 4-7 and Sentinel 2 to Landsat 8
time series of datasets.
It will display the charts of the harmonized satellite albedo (All Observations) and original albedo
(All Observations Original).
The linear trendline will be plotted on a separate chart.
ref:
This script is adapted from the excellent tutorial made by Justin Braaten.
https://github.com/jdbcode
https://developers.google.com/earth-engine/tutorials/community/landsat-etm-to-oli-harmonization
Shunan Feng
*/
/**
* Intial parameters
*/
var date_start = ee.Date.fromYMD(1984, 1, 1);
var date_end = ee.Date(Date.now());
// var aoi = ee.Geometry.Point([-49.3476433532785, 67.0775206116519]);
var aoi = ee.Geometry.Point([-48.8355, 67.0670]); // change your coordinate here
// Display AOI on the map.
Map.centerObject(aoi, 4);
Map.addLayer(aoi, {color: 'f8766d'}, 'AOI');
Map.setOptions('HYBRID');
/*
prepare harmonized satellite data
*/
// Function to get and rename bands of interest from OLI.
function renameOli(img) {
return img.select(
['SR_B2', 'SR_B3', 'SR_B4', 'SR_B5', 'SR_B6', 'SR_B7', 'QA_PIXEL', 'QA_RADSAT'], // 'QA_PIXEL', 'QA_RADSAT'
['Blue', 'Green', 'Red', 'NIR', 'SWIR1', 'SWIR2', 'QA_PIXEL', 'QA_RADSAT']);//'QA_PIXEL', 'QA_RADSAT';
}
// Function to get and rename bands of interest from ETM+, TM.
function renameEtm(img) {
return img.select(
['SR_B1', 'SR_B2', 'SR_B3', 'SR_B4', 'SR_B5', 'SR_B7', 'QA_PIXEL', 'QA_RADSAT'], //#, 'QA_PIXEL', 'QA_RADSAT'
['Blue', 'Green', 'Red', 'NIR', 'SWIR1', 'SWIR2', 'QA_PIXEL', 'QA_RADSAT']); // #, 'QA_PIXEL', 'QA_RADSAT'
}
// Function to get and rename bands of interest from Sentinel 2.
function renameS2(img) {
return img.select(
['B2', 'B3', 'B4', 'B8', 'B11', 'B12', 'QA60', 'SCL', QA_BAND],
['Blue', 'Green', 'Red', 'NIR', 'SWIR1', 'SWIR2', 'QA60', 'SCL', QA_BAND]
);
}
/* RMA transformation */
var rmaCoefficients = {
itcpsL7: ee.Image.constant([-0.0084, -0.0065, 0.0022, -0.0768, -0.0314, -0.0022]),
slopesL7: ee.Image.constant([1.1017, 1.0840, 1.0610, 1.2100, 1.2039, 1.2402]),
itcpsS2: ee.Image.constant([0.0210, 0.0167, 0.0155, -0.0693, -0.0039, -0.0112]),
slopesS2: ee.Image.constant([1.0849, 1.0590, 1.0759, 1.1583, 1.0479, 1.0148])
}; // #rma
function oli2oli(img) {
return img.select(['Blue', 'Green', 'Red', 'NIR', 'SWIR1', 'SWIR2'])
.toFloat();
}
function etm2oli(img) {
return img.select(['Blue', 'Green', 'Red', 'NIR', 'SWIR1', 'SWIR2'])
.multiply(rmaCoefficients.slopesL7)
.add(rmaCoefficients.itcpsL7)
.toFloat();
}
function s22oli(img) {
return img.select(['Blue', 'Green', 'Red', 'NIR', 'SWIR1', 'SWIR2'])
.multiply(rmaCoefficients.slopesS2)
.add(rmaCoefficients.itcpsS2)
.toFloat();
}
function imRangeFilter(image) {
var maskMax = image.lte(1);
var maskMin = image.gt(0);
return image.updateMask(maskMax).updateMask(maskMin);
}
/*
Cloud mask for Landsat data based on fmask (QA_PIXEL) and saturation mask
based on QA_RADSAT.
Cloud mask and saturation mask by sen2cor.
Codes provided by GEE official.
*/
// This example demonstrates the use of the Landsat 8 Collection 2, Level 2
// QA_PIXEL band (CFMask) to mask unwanted pixels.
function maskL8sr(image) {
// Bit 0 - Fill
// Bit 1 - Dilated Cloud
// Bit 2 - Cirrus
// Bit 3 - Cloud
// Bit 4 - Cloud Shadow
var qaMask = image.select('QA_PIXEL').bitwiseAnd(parseInt('11111', 2)).eq(0);
var saturationMask = image.select('QA_RADSAT').eq(0);
// Apply the scaling factors to the appropriate bands.
// var opticalBands = image.select(['Blue', 'Green', 'Red', 'NIR']).multiply(0.0000275).add(-0.2);
// var thermalBands = image.select('ST_B.*').multiply(0.00341802).add(149.0);
// Replace the original bands with the scaled ones and apply the masks.
return image.select(['Blue', 'Green', 'Red', 'NIR', 'SWIR1','SWIR2']).multiply(0.0000275).add(-0.2)
// .addBands(thermalBands, null, true)
.updateMask(qaMask)
.updateMask(saturationMask);
}
// This example demonstrates the use of the Landsat 4, 5, 7 Collection 2,
// Level 2 QA_PIXEL band (CFMask) to mask unwanted pixels.
function maskL457sr(image) {
// Bit 0 - Fill
// Bit 1 - Dilated Cloud
// Bit 2 - Unused
// Bit 3 - Cloud
// Bit 4 - Cloud Shadow
var qaMask = image.select('QA_PIXEL').bitwiseAnd(parseInt('11111', 2)).eq(0);
var saturationMask = image.select('QA_RADSAT').eq(0);
// Apply the scaling factors to the appropriate bands.
// var opticalBands = image.select('SR_B.').multiply(0.0000275).add(-0.2);
// var thermalBand = image.select('ST_B6').multiply(0.00341802).add(149.0);
// Replace the original bands with the scaled ones and apply the masks.
return image.select(['Blue', 'Green', 'Red', 'NIR', 'SWIR1','SWIR2']).multiply(0.0000275).add(-0.2)
// .addBands(thermalBand, null, true)
.updateMask(qaMask)
.updateMask(saturationMask);
}
/**
* Function to mask clouds using the Sentinel-2 QA band
* @param {ee.Image} image Sentinel-2 image
* @return {ee.Image} cloud masked Sentinel-2 image
* archived after updating to Cloud Score+
*/
// function maskS2sr(image) {
// var qa = image.select('QA60');
// // Bits 10 and 11 are clouds and cirrus, respectively.
// var cloudBitMask = 1 << 10;
// var cirrusBitMask = 1 << 11;
// // 1 is saturated or defective pixel
// var not_saturated = image.select('SCL').neq(1);
// // Both flags should be set to zero, indicating clear conditions.
// var mask = qa.bitwiseAnd(cloudBitMask).eq(0)
// .and(qa.bitwiseAnd(cirrusBitMask).eq(0));
// // return image.updateMask(mask).updateMask(not_saturated);
// return image.updateMask(mask).updateMask(not_saturated).divide(10000);
// }
/**
* Function to mask clouds using the Cloud Score+
*/
// Cloud Score+ image collection. Note Cloud Score+ is produced from Sentinel-2
// Level 1C data and can be applied to either L1C or L2A collections.
var csPlus = ee.ImageCollection('GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED');
// Use 'cs' or 'cs_cdf', depending on your use case; see docs for guidance.
var QA_BAND = 'cs'; // I find'cs' is better than 'cs_cdf' because it is more robust but may mask out more clear pixels though
// The threshold for masking; values between 0.50 and 0.65 generally work well.
// Higher values will remove thin clouds, haze & cirrus shadows.
var CLEAR_THRESHOLD = 0.65;
function maskS2sr(image) {
// 1 is saturated or defective pixel
var not_saturated = image.select('SCL').neq(1);
return image.updateMask(image.select(QA_BAND).gte(CLEAR_THRESHOLD))
.updateMask(not_saturated)
.divide(10000);
}
// // narrow to broadband conversion
function addVisnirAlbedo(image) {
var albedo = image.expression(
'0.7963 * Blue + 2.2724 * Green - 3.8252 * Red + 1.4143 * NIR + 0.2053',
{
'Blue': image.select('Blue'),
'Green': image.select('Green'),
'Red': image.select('Red'),
'NIR': image.select('NIR')
}
).rename('visnirAlbedo');
return image.addBands(albedo).copyProperties(image, ['system:time_start']);
}
// function addNDSI(image) {
// // var indice = image.normalizedDifference(['Green', 'SWIR1']).rename('NDSI');
// return image.normalizedDifference(['Green', 'SWIR1']).rename('NDSI');
// }
/* get harmonized image collection */
// Define function to prepare OLI2 images.
function prepOli2(img) {
var orig = img;
img = renameOli(img);
img = maskL8sr(img);
img = oli2oli(img);
img = imRangeFilter(img);
img = addVisnirAlbedo(img);
return ee.Image(img.copyProperties(orig, orig.propertyNames()).set('SATELLITE', 'LANDSAT_9'));
}
// Define function to prepare OLI images.
function prepOli(img) {
var orig = img;
img = renameOli(img);
img = maskL8sr(img);
img = oli2oli(img);
img = imRangeFilter(img);
img = addVisnirAlbedo(img);
return ee.Image(img.copyProperties(orig, orig.propertyNames()).set('SATELLITE', 'LANDSAT_8'));
}
// Define function to prepare ETM+ images.
function prepEtm(img) {
var orig = img;
img = renameEtm(img);
img = maskL457sr(img);
img = etm2oli(img);
img = imRangeFilter(img);
img = addVisnirAlbedo(img);
return ee.Image(img.copyProperties(orig, orig.propertyNames()).set('SATELLITE', 'LANDSAT_7'));
}
// Define function to prepare TM images.
function prepTm(img) {
var orig = img;
img = renameEtm(img);
img = maskL457sr(img);
img = etm2oli(img);
img = imRangeFilter(img);
img = addVisnirAlbedo(img);
return ee.Image(img.copyProperties(orig, orig.propertyNames()).set('SATELLITE', 'LANDSAT_4/5'));
}
// Define function to prepare S2 images.
function prepS2(img) {
var orig = img;
img = renameS2(img);
img = maskS2sr(img);
img = s22oli(img);
img = imRangeFilter(img);
img = addVisnirAlbedo(img);
return ee.Image(img.copyProperties(orig, orig.propertyNames()).set('SATELLITE', 'SENTINEL_2'));
}
var colFilter = ee.Filter.and(
ee.Filter.bounds(aoi),
ee.Filter.date(date_start, date_end)
// ee.Filter.calendarRange(6, 8, 'month')
);
var s2colFilter = ee.Filter.and(
ee.Filter.bounds(aoi),
ee.Filter.date(date_start, date_end),
// ee.Filter.calendarRange(6, 8, 'month'),
ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE', 50)
);
var oli2Col = ee.ImageCollection('LANDSAT/LC09/C02/T1_L2')
.filter(colFilter)
.map(prepOli2)
.select(['visnirAlbedo']); //# .select(['totalAlbedo']) or .select(['visnirAlbedo'])
var oliCol = ee.ImageCollection('LANDSAT/LC08/C02/T1_L2')
.filter(colFilter)
.map(prepOli)
.select(['visnirAlbedo']); //# .select(['totalAlbedo']) or .select(['visnirAlbedo'])
var etmCol = ee.ImageCollection('LANDSAT/LE07/C02/T1_L2')
.filter(colFilter)
.filter(ee.Filter.calendarRange(1999, 2020, 'year')) // filter out L7 imagaes acquired after 2020 due to orbit drift
.map(prepEtm)
.select(['visnirAlbedo']); // # .select(['totalAlbedo']) or .select(['visnirAlbedo'])
var tmCol = ee.ImageCollection('LANDSAT/LT05/C02/T1_L2')
.filter(colFilter)
.map(prepTm)
.select(['visnirAlbedo']); //# .select(['totalAlbedo']) or .select(['visnirAlbedo'])
var tm4Col = ee.ImageCollection('LANDSAT/LT04/C02/T1_L2')
.filter(colFilter)
.map(prepTm)
.select(['visnirAlbedo']); //# .select(['totalAlbedo']) or .select(['visnirAlbedo'])
var s2Col = ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')
.linkCollection(csPlus, [QA_BAND])
.filter(s2colFilter)
.map(prepS2)
.select(['visnirAlbedo']); //# .select(['totalAlbedo']) or .select(['visnirAlbedo'])
var landsatCol = oliCol.merge(etmCol).merge(tmCol).merge(tm4Col).merge(oli2Col);
var multiSat = landsatCol.merge(s2Col).sort('system:time_start', true); // Sort chronologically in descending order.
// prepare the chart of harmonized satellite albedo
var allObs = multiSat.map(function(img) {
var obs = img.reduceRegion(
{geometry: aoi,
reducer: ee.Reducer.median(),
scale: 30});
return img.set('visnirAlbedo', obs.get('visnirAlbedo'));
});
var allObsValid = allObs.filter(ee.Filter.lt('visnirAlbedo', 1));
var chartAllObs =
ui.Chart.feature.groups(allObsValid, 'system:time_start', 'visnirAlbedo', 'SATELLITE')
.setChartType('ScatterChart')
// .setSeriesNames(['TM', 'ETM+', 'OLI', 'S2'])
.setOptions({
title: 'All Harmonized Observations',
colors: ['f8766d', '00ba38', '619cff', '8934eb', 'cf513e'],
hAxis: {title: 'Date'},
vAxis: {title: 'visnirAlbedo', viewWindow: {min: 0, max: 1}},
pointSize: 6,
dataOpacity: 0.5
});
print(chartAllObs);
var chartAllObsTrend = ui.Chart.image.series({
imageCollection: multiSat,
region: aoi,
reducer: ee.Reducer.median(),
scale:30,
xProperty:'system:time_start'
}).setChartType('ScatterChart')
.setOptions({
title: 'All Harmonized Observations with Trendline',
hAxis: {title: 'Date'},
vAxis: {title: 'visnirAlbedo', viewWindow: {min: 0, max: 1}},
pointSize: 6,
dataOpacity: 0.5,
trendlines: {0:{color:'black'}}
});
print(chartAllObsTrend);
/*
Make a new chart for the original dataset.
*/
// Define function to prepare OLI images.
function prepOli2Ori(img) {
var orig = img;
img = renameOli(img);
img = maskL8sr(img);
img = imRangeFilter(img);
img = addVisnirAlbedo(img);
return ee.Image(img.copyProperties(orig, orig.propertyNames()).set('SATELLITE', 'LANDSAT_9'));
}
// Define function to prepare OLI images.
function prepOliOri(img) {
var orig = img;
img = renameOli(img);
img = maskL8sr(img);
img = imRangeFilter(img);
img = addVisnirAlbedo(img);
return ee.Image(img.copyProperties(orig, orig.propertyNames()).set('SATELLITE', 'LANDSAT_8'));
}
// Define function to prepare ETM+ images.
function prepEtmOri(img) {
var orig = img;
img = renameEtm(img);
img = maskL457sr(img);
img = imRangeFilter(img);
img = addVisnirAlbedo(img);
return ee.Image(img.copyProperties(orig, orig.propertyNames()).set('SATELLITE', 'LANDSAT_7'));
}
// Define function to prepare TM images.
function prepTmOri(img) {
var orig = img;
img = renameEtm(img);
img = maskL457sr(img);
img = imRangeFilter(img);
img = addVisnirAlbedo(img);
return ee.Image(img.copyProperties(orig, orig.propertyNames()).set('SATELLITE', 'LANDSAT_4/5'));
}
// Define function to prepare S2 images.
function prepS2Ori(img) {
var orig = img;
img = renameS2(img);
img = maskS2sr(img);
img = imRangeFilter(img);
img = addVisnirAlbedo(img);
return ee.Image(img.copyProperties(orig, orig.propertyNames()).set('SATELLITE', 'SENTINEL_2'));
}
var oli2ColOri = ee.ImageCollection('LANDSAT/LC09/C02/T1_L2')
.filter(colFilter)
.map(prepOli2Ori)
.select(['visnirAlbedo']); //# .select(['totalAlbedo']) or .select(['visnirAlbedo'])
var oliColOri = ee.ImageCollection('LANDSAT/LC08/C02/T1_L2')
.filter(colFilter)
.map(prepOliOri)
.select(['visnirAlbedo']); //# .select(['totalAlbedo']) or .select(['visnirAlbedo'])
var etmColOri = ee.ImageCollection('LANDSAT/LE07/C02/T1_L2')
.filter(colFilter)
.filter(ee.Filter.calendarRange(1999, 2020, 'year')) // filter out L7 imagaes acquired after 2020 due to orbit drift
.map(prepEtmOri)
.select(['visnirAlbedo']); // # .select(['totalAlbedo']) or .select(['visnirAlbedo'])
var tmColOri = ee.ImageCollection('LANDSAT/LT05/C02/T1_L2')
.filter(colFilter)
.map(prepTmOri)
.select(['visnirAlbedo']); //# .select(['totalAlbedo']) or .select(['visnirAlbedo'])
var tm4ColOri = ee.ImageCollection('LANDSAT/LT04/C02/T1_L2')
.filter(colFilter)
.map(prepTmOri)
.select(['visnirAlbedo']); //# .select(['totalAlbedo']) or .select(['visnirAlbedo'])
var s2ColOri = ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')
.linkCollection(csPlus, [QA_BAND])
.filter(s2colFilter)
.map(prepS2Ori)
.select(['visnirAlbedo']); //# .select(['totalAlbedo']) or .select(['visnirAlbedo'])
var landsatColOri = oliColOri.merge(etmColOri).merge(tmColOri).merge(tm4ColOri).merge(oli2ColOri);
var multiSatOri = landsatColOri.merge(s2ColOri).sort('system:time_start', true); // Sort chronologically in descending order.
var allObsOri = multiSatOri.map(function(img) {
var obs = img.reduceRegion(
{geometry: aoi,
reducer: ee.Reducer.median(),
scale: 30});
return img.set('visnirAlbedo', obs.get('visnirAlbedo'));
});
var allObsOriValid = allObsOri.filter(ee.Filter.lt('visnirAlbedo', 1));
var chartAllObsOri =
ui.Chart.feature.groups(allObsOriValid, 'system:time_start', 'visnirAlbedo', 'SATELLITE')
.setChartType('ScatterChart')
// .setSeriesNames(['TM', 'ETM+', 'OLI', 'S2'])
.setOptions({
title: 'All Observations Original',
colors: ['f8766d', '00ba38', '619cff', '8934eb', 'cf513e'],
hAxis: {title: 'Date'},
vAxis: {title: 'visnirAlbedo', viewWindow: {min: 0, max: 1}},
pointSize: 6,
dataOpacity: 0.5
});
print(chartAllObsOri);
var chartAllObsOriTrend = ui.Chart.image.series({
imageCollection: multiSatOri,
region: aoi,
reducer: ee.Reducer.median(),
scale:30,
xProperty:'system:time_start'
}).setChartType('ScatterChart')
// .setSeriesNames('visnirAlbedo')
.setOptions({
title: 'All Observations Original with Trendline',
hAxis: {title: 'Date'},
vAxis: {title: 'visnirAlbedo', viewWindow: {min: 0, max: 1}},
pointSize: 6,
dataOpacity: 0.5,
trendlines: {0:{color:'black'}}
});
print(chartAllObsOriTrend);