Dear all,

Today my scripts of GEE API are not working. The console returns the following error message 'Cannot read property 'undefined' of undefined'.

See below my code which was based on a previous version.

Thanks.

// Script automatically produced by Collect Earth for the plot that has been clicked on Google Earht. See bottom of the script for more info on customization. // This script will show graphs of NDVI, EVI and NDWI mean-values for the pixels contained within the plot.

// The date that is used as the start of the chart ( if the dataset is available ) // You can change the start date manually and hit the button "Run""again to reload the charts using the different time series var startTime = '2000-01-01';

// The last date for which the chart is generated. Should be today's date var endTime = '${todayDate}';

//Set up calculations for % of images with NDVI above a threshold

var visualizationLandsat = {min: 0, max: [0.2,0.2,0.2], gamma: [1, 1, 1]}; var visualizationAster = {bands: ['nir', 'swir1', 'red'], min: 0, max: [30, 50, 200], gamma: [0.8, 0.8, 1]}; var visualizationSentinel = {min: 0, max: [4000, 4000, 4000], gamma: [1, 0.1, 1]}; var visualizationLandsat8 = {min: 0, max: [0.1, 0.1, 0.1], gamma: [1, 1, 1]};

var startYear = "-01-01"; var endYear = "-12-31";

// DO NOT EDIT THIS BLOCK!! ------ // x The polygon that describes the plot. var plot = ee.Geometry.MultiLineString([ <#list placemark.multiShape as shp> ee.Geometry.LineString([ // The placemark variable has an array called shape that contains the locations of the corners of the polygon <#list shp as coord> [${coord.longitude}, ${coord.latitude}], ]), ] );

// UNTIL HERE ---------------

// Load the MODIS Vegetation Index composite. Select the NDVI band. Resolution of the pixels is 250 meters. var modisNoaaNdvi = ee.ImageCollection('MODIS/MOD13Q1').filterDate(startTime, endTime).select('NDVI');

var addFire = function(i){ var image = ee.Image(i); var startModisRange = image.get("system:time_start"); var endModisRange = image.get("system:time_end"); var fireValue = ee.ImageCollection('FIRMS').filterDate(startModisRange, endModisRange).select('T21').mean(); var fireValueImage = ee.Image( fireValue ); var concat = image.addBands( fireValueImage ); return concat; } modisNoaaNdvi = modisNoaaNdvi.map( addFire ); var modisNoaaTimeSeries = Chart.image.series(modisNoaaNdvi, plot, ee.Reducer.mean(), 30); modisNoaaTimeSeries = modisNoaaTimeSeries .setOptions({
title: 'MODIS NDVI 16-Day + FIRMS Fire alerts', hAxis: {title: 'Date',gridlines: {count: 10,}}, vAxis: {title: 'NDVI',viewWindowMode: 'explicit', viewWindow: {max: 10000,min: -2500,},gridlines: {count: 5,}} });

// Show the MODIS NDVI chart on the console print(modisNoaaTimeSeries);

var landsat7MonthlyNdvi = ee.ImageCollection('LANDSAT/LE7_L1T_32DAY_NDVI').filterDate(startTime, endTime).select('NDVI');

var landsat7MonthlyTimeSeries = ui.Chart.image.series(landsat7MonthlyNdvi, plot, ee.Reducer.mean(), 30);

landsat7MonthlyTimeSeries = landsat7MonthlyTimeSeries .setOptions({ title: 'Landsat 7 Monthly NDVI Composite', hAxis: {title: 'Month'}, vAxis: {title: 'NDVI',viewWindowMode: 'explicit', viewWindow: {max: 1,min: -0.25,},gridlines: {count: 5,}} });

print(landsat7MonthlyTimeSeries);

//Array sorting is useful for obtaining custom quality mosaics which involve reducing a subset of image bands according to the values in a different band. The following example sorts by a cloud index, then gets the mean of the least cloudy subset of images in the collection:

var sharpenedLandsat8_false = panSharpen('LANDSAT/LC8_L1T_ANNUAL_GREENEST_TOA' , ['B5', 'B6', 'B4'], ['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8','B10', 'B11'], '2017'+startYear, '2017' + endYear); var collection = ee.ImageCollection( 'ASTER/AST_L1T_003' ).filterBounds(plot).filterDate( '2005'+startYear , '2005' + endYear ).filter(ee.Filter.listContains('ORIGINAL_BANDS_PRESENT', 'B3N')).map(normalize); var sharpenedAster = collection.qualityMosaic('cloudCover'); var sharpenedLandsat7_2008 = panSharpen('LANDSAT/LE7_L1T_ANNUAL_GREENEST_TOA' , ['B4', 'B5', 'B3'], ['B1', 'B2', 'B3', 'B4', 'B5', 'B6_VCID_1' , 'B6_VCID_2' , 'B7', 'B8'], '2005'+startYear, '2005' + endYear); var sentinelVV = ee.ImageCollection('COPERNICUS/S2').filterDate('2017'+startYear , '2017' + endYear ).filterBounds(plot).filter(ee.Filter.lte('CLOUDY_PIXEL_PERCENTAGE', 30) ).map(cloudMask); var sentinelImage = sentinelVV.median().select(['B8','B11','B4']); sentinelImage = sharpenSentinel( sentinelImage);

///New Aster normalize function function normalize(image) { var norm = function(band) { return ee.Image(ee.Number(image.get('GAIN_COEFFICIENT_' + band))).float() .rename(band) } var coef = ee.Image.cat( [norm('B01'), norm('B02'), norm('B04'), norm('B05'), norm('B06'), norm('B07'), norm('B08'), norm('B09'), norm('B10'), norm('B11'), norm('B12'), norm('B13'), norm('B14'), norm('B3N')] )

var cloudCover = ee.Image(ee.Number(image.get('CLOUDCOVER'))) .float().multiply(-1).add(100).rename('cloudCover') image = image.subtract(1).multiply(coef) image = image.select( ['B01', 'B02', 'B3N', 'B04', 'B05', 'B10'], ['green', 'red', 'nir', 'swir1', 'swir2', 'thermal'])

return image .addBands(cloudCover) } ////END

function addPlotToMap(map){ map.addLayer(plot, {}, "Plot"); map.centerObject( plot , 15 ); map.setControlVisibility(false); return map; }

function createL7SliderMap( image, visualization, year, name){ var map = ui.Map(); addL7Slider(map, year); map.addLayer(image, visualization, name); // Add the plot polygon to the map return addPlotToMap(map); }

function createAsterSliderMap( image, visualization, year, name){ var map = ui.Map(); addAsterSlider(map, year); map.addLayer(image, visualization, name); // Add the plot polygon to the map return addPlotToMap(map); }

function createS2SliderMap( image, visualization, year, name){ var map = ui.Map(); addS2Slider(map, year); map.addLayer(image, visualization, name); // Add the plot polygon to the map return addPlotToMap(map); }

function createL8SliderMap( image, visualization, year, name){ var map = ui.Map(); addL8Slider(map, year); map.addLayer(image, visualization, name); // Add the plot polygon to the map return addPlotToMap(map); }

// Create a map for each visualization option. var maps = [];

var showLandsat7ForYearTop = function(year){ showLandsat7ForYear( landsat7Map, year); }

var showAsterForYearBottom = function(year){ showAsterForYear( asterMap, year); }

var showS2ForYearTop = function(year){ showS2ForYear( sentinelMap, year); }

var showLandsat8ForYearBottom = function(year){ showLandsat8ForYear( landsat8Map, year); }

var showAsterForYear = function(map, year){ var Aster = ee.ImageCollection( 'ASTER/AST_L1T_003' ).filterBounds(plot).filterDate( year + startYear, year + endYear ).filter(ee.Filter.listContains('ORIGINAL_BANDS_PRESENT', 'B3N')).map(normalize); Aster = Aster.qualityMosaic('cloudCover').visualize(visualizationAster); map.layers().set( 0, Aster); }

var showLandsat7ForYear = function(map, year){ var landsat = panSharpen('LANDSAT/LE7_L1T_ANNUAL_GREENEST_TOA' , ['B4', 'B5', 'B3'], ['B1', 'B2', 'B3', 'B4', 'B5', 'B6_VCID_1' , 'B6_VCID_2' , 'B7', 'B8'], year + startYear, year + endYear ); landsat = landsat.visualize(visualizationLandsat ); map.layers().set( 0, landsat); }

var showLandsat8ForYear = function(map, year){ var landsat = panSharpen('LANDSAT/LC8_L1T_ANNUAL_GREENEST_TOA' , ['B5', 'B6', 'B4'], ['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8','B10', 'B11'], year + startYear, year + endYear ); landsat = landsat.visualize(visualizationLandsat8 ); map.layers().set( 0, landsat); }

var showS2ForYear = function(map, year){ var sentinelVV = ee.ImageCollection('COPERNICUS/S2').filterDate(year + startYear, year + endYear).filterBounds(plot).filter(ee.Filter.lte('CLOUDY_PIXEL_PERCENTAGE', 30) ).map(cloudMask); var sentinelImage = sentinelVV.median().select(['B8','B11','B4']); sentinelImage = sharpenSentinel( sentinelImage); sentinelImage = sentinelImage.visualize(visualizationSentinel); map.layers().set( 0, sentinelImage); }

var addL7Slider = function(mapWithSlider , selectedYear ){ // Create a label and slider. var label = ui.Label('Landsat 7 False Color'); var onChangeFunction = showLandsat7ForYearTop; var slider = ui.Slider({ min: 2000, max: 2017, step: 1, onChange: onChangeFunction, style: {stretch: 'horizontal'} });

// Create a panel that contains both the slider and the label. var panelSlider = ui.Panel({ widgets: [label, slider], layout: ui.Panel.Layout.flow('vertical'), style: { position: 'top-center', padding: '7px' } });

mapWithSlider.add(panelSlider); slider.setValue(selectedYear,false); }

var addAsterSlider = function(mapWithSlider , selectedYear ){ // Create a label and slider. var label = ui.Label('Aster False Color'); var onChangeFunction = showAsterForYearBottom; var slider = ui.Slider({ min: 2000, max: 2012, step: 1, onChange: onChangeFunction, style: {stretch: 'horizontal'} });

// Create a panel that contains both the slider and the label. var panelSlider = ui.Panel({ widgets: [label, slider], layout: ui.Panel.Layout.flow('vertical'), style: { position: 'top-center', padding: '7px' } });

mapWithSlider.add(panelSlider); slider.setValue(selectedYear,false); }

var addL8Slider = function(mapWithSlider , selectedYear ){ // Create a label and slider. var label = ui.Label('Landsat 8 False Color'); var onChangeFunction = showLandsat8ForYearBottom; var slider = ui.Slider({ min: 2013, max: 2017, step: 1, onChange: onChangeFunction, style: {stretch: 'horizontal'} });

// Create a panel that contains both the slider and the label. var panelSlider = ui.Panel({ widgets: [label, slider], layout: ui.Panel.Layout.flow('vertical'), style: { position: 'top-center', padding: '7px' } });

mapWithSlider.add(panelSlider); slider.setValue(selectedYear,false); }

var addS2Slider = function(mapWithSlider , selectedYear ){ // Create a label and slider. var label = ui.Label('Sentinel False Color'); var onChangeFunction = showS2ForYearTop; var slider = ui.Slider({ min: 2015, max: 2017, step: 1, onChange: onChangeFunction, style: {stretch: 'horizontal'} });

// Create a panel that contains both the slider and the label. var panelSlider = ui.Panel({ widgets: [label, slider], layout: ui.Panel.Layout.flow('vertical'), style: { position: 'top-center', padding: '7px' } });

mapWithSlider.add(panelSlider); slider.setValue(selectedYear,false); }

var sentinelMap = createS2SliderMap( sentinelImage, visualizationSentinel , 2017, "S2 False Color"); var landsat8Map = createL8SliderMap(sharpenedLandsat8_false, visualizationLandsat8, 2017, "L7 False color"); var landsat7Map = createL7SliderMap(sharpenedLandsat7_2008, visualizationLandsat, 2008, "L7 False color"); var asterMap = createAsterSliderMap(sharpenedAster, visualizationAster, 2005, "Aster False color");

maps.push(sentinelMap); maps.push(landsat8Map); maps.push(landsat7Map); maps.push(asterMap);

var linker = ui.Map.Linker(maps); // Create a grid of maps.

var panelLeft = ui.Panel([sentinelMap, landsat8Map], null, {stretch: 'both'}); var panelRight = ui.Panel([landsat7Map, asterMap], null, {stretch: 'both'});

var mapGrid = ui.Panel([ panelLeft,panelRight], ui.Panel.Layout.Flow('horizontal'), {stretch: 'both'} );

// Enable zooming on the top-left map. sentinelMap.setControlVisibility({zoomControl: true});

// Show the scale (e.g. '500m') on the bottom-right map. landsat7Map.setControlVisibility({scaleControl: true});

// Add the maps and title to the ui.root. ui.root.widgets().reset([mapGrid]); ui.root.setLayout(ui.Panel.Layout.Flow('vertical'));

function sharpenSentinel(image){ // sharpen see e.g. http://www.cse.psu.edu/~rtc12/CSE486/lecture11_6pp.pdf var log = image .convolve(ee.Kernel.gaussian(10, 7, 'meters')) // G .convolve(ee.Kernel.laplacian8(0.5)) // L of G

var sharpened = image.subtract(log);
return sharpened;

}

function panSharpen(landsatCollectionName, bandsToSharpen, bandsCloudScore, startPeriod, endPeriod ){

var bandNames = ee.List(bandsCloudScore);

// Load a Landsat collection.
var image= ee.ImageCollection( landsatCollectionName )
// Select the bands of interest to avoid taking up memory.
.select(bandsCloudScore)
// Filter to get only six months of data.
.filterDate( startPeriod , endPeriod ).first();

image = ee.Image(image );

// Convert the RGB bands to the HSV color space.
var hsv = image.select( bandsToSharpen ).rgbToHsv();

// Swap in the panchromatic band and convert back to RGB.
var sharpened = ee.Image.cat([
    hsv.select('hue'), hsv.select('saturation'), image.select('B8')
]).hsvToRgb();

return sharpened;

}

function cloudMask(im) { // Opaque and cirrus cloud masks cause bits 10 and 11 in QA60 to be set, // so values less than 1024 are cloud-free var mask = ee.Image(0).where(im.select('QA60').gte(1024), 1).not(); return im.updateMask(mask); } // cloudMask

// Center the map on the plot location (actually the top-left corner of the plot ) and set Zoom level to 15 Map.setCenter(${placemark.shape[0].longitude}, ${placemark.shape[0].latitude}, 15)

// This is an automatically generated script. // If you want to Collect Earth to run a different script for your project when a user clicks on a plot on Google Earth follow these steps : // 1. Copy the contents of this file : https://raw.githubusercontent.com/openforis/collect-earth/master/collect-earth/collect-earth-app/resources/eePlaygroundScript.fmt // 2. Modify the script as you please but keep the lines where the plot variable has been defined using Freemarker tamplate variables // 3. Save the script as "eePlaygroundScript.fmt" inside the root folder of your CEP project file

asked 06 Apr, 20:34

abespejo's gravatar image

abespejo
153
accept rate: 0%


Hello,

The problem seems to happen because the script uses an old version of the MODIS vegetation index collection.

If you replace the reference to the old version(MODIS/MOD13Q1) to the version 6 newest product ( MODIS/006/MOD13Q1 ) then the script works fine...

Check line 40 : https://code.earthengine.google.com/f1d3d6bffde960d6a27bb5633abdafd4

Also, We have other scripts that you might use where the scripts reference other scripts in a library that we control, this way if something like this happens we fix it from Open Foris and the issue is solved for all users. Of course this takes away versatility from your side but if you want you could replicate the same idea for your users.

Check this script (which actually is the one that is run by default on the newer version of Collect Earth) :

LINK TO CODE EDITOR SCRIPT

Let me know if you need more help setting the new script structure, we need to document this better!

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answered 08 Apr, 12:03

collectearth's gravatar image

collectearth ♦
62515
accept rate: 16%

Dear,

Thank you very much for the prompt response!

Finally, I went ahead, copied your code and made some modifications. I have a different script for Aster that might work better that the script that you have (which gives the median of the collection, so it has a lot of cloud contamination). I also added a L8 slider.

In case someone is interested https://code.earthengine.google.com/?accept_repo=users/andresbernabeespejo/CollectEarth

Best regards.

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answered 09 Apr, 02:10

abespejo's gravatar image

abespejo
153
accept rate: 0%

Thank you for sharing! I will add these improvements to our libraries too

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answered 10 Apr, 10:30

collectearth's gravatar image

collectearth ♦
62515
accept rate: 16%

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question asked: 06 Apr, 20:34

question was seen: 198 times

last updated: 10 Apr, 10:30