Spectral signature of classified image in GEE using Random Forest - histogram

Question

I am using this script to draw average spectral signature of all classes together and each class separately of a classified image by RF algorithm in GEE.
var bands = ['B1', 'B2', 'B3', 'B4','B5','B6','B7', 'B8', 'B8A', 'B9' ,'B11', 'B12','NDVI', 'EVI', 'GNDVI', 'NBR', 'NDII'];
var Training_Points = Water.merge(Residential).merge(Agricultural).merge(Arbusti).merge(BoschiMisti).merge(Latifoglie).merge(Conifere).merge(BareSoil);
var classes = ee.Image().byte().paint(Training_Points, "land_class").rename("land_class")
var stratified_points = classes.stratifiedSample({
numPoints: 50,
classBand: 'land_class',
scale: 10,
region: Training_Points,
geometries: false,
tileScale: 6
})
print(stratified_points, 'stratified_points')
//Create training data
var training_Stratified = RF_classified.select(bands).sampleRegions({
collection: stratified_points,
properties: ['land_class'],
scale:10,
tileScale:2
});
var bands = RF_classified.bandNames()
var numBands = bands.length()
var bandsWithClass = bands.add('land_class')
var classIndex = bandsWithClass.indexOf('land_class')
// Use .combine() to get a reducer capable of computing multiple stats on the input
var combinedReducer = ee.Reducer.mean().combine({
reducer2: ee.Reducer.stdDev(),
sharedInputs: true})
// Use .repeat() to get a reducer for each band and then use .group() to get stats by class
var repeatedReducer = combinedReducer.repeat(numBands).group(classIndex)
var stratified_points_Stats = training_Stratified.reduceColumns({
selectors: bands.add('land_class'),
reducer: repeatedReducer,
})
// Result is a dictionary, we do some post-processing to extract the results
var groups = ee.List(stratified_points_Stats.get('groups'))
var classNames = ee.List(['Water','Residential', 'Agricultural', 'Arbusti', 'BoschiMisti', 'Latifoglie','Conifere', 'BareSoil'])
var fc = ee.FeatureCollection(groups.map(function(item) {
// Extract the means
var values = ee.Dictionary(item).get('mean')
var groupNumber = ee.Dictionary(item).get('group')
var properties = ee.Dictionary.fromLists(bands, values)
var withClass = properties.set('class', classNames.get(groupNumber))
return ee.Feature(null, withClass)
}))
// Chart spectral signatures of training data
var options = {
title: 'Average Spectral Signatures',
hAxis: {title: 'Bands'},
vAxis: {title: 'Reflectance',
viewWindowMode:'explicit',
viewWindow: {
max:6000,
min:0
}},
lineWidth: 1,
pointSize: 4,
series: {
0: {color: '105af0'},
1: {color: 'dc350a'},
2: {color: 'caa712'},
3: {color: 'b9ffa4'},
4: {color: '369b47'},
5: {color: '21ff2d'},
6: {color: '275b25'},
7: {color: 'f7e084'},
}};
// Default band names don't sort propertly Instead, we can give a dictionary with labels for each band in the X-Axis
var bandDescriptions = {
'B2': 'B2/Blue',
'B3': 'B3/Green',
'B4': 'B4/Red',
'B5': 'B5/Red Edge 1',
'B6': 'B5/Red Edge 2',
'B7': 'B7/Red Edge 3',
'B8': 'B8/NIR',
'B8A': 'B8A/Red Edge 4',
'B11': 'B11/SWIR-1',
'B12': 'B12/SWIR-2'
}
// Create the chart and set options.
var chart = ui.Chart.feature.byProperty({
features: fc,
xProperties: bandDescriptions,
seriesProperty: 'class'
})
.setChartType('ScatterChart')
.setOptions(options);
print(chart)
var classChart = function(land_class, label, color) {
var options = {
title: 'Spectral Signatures for ' + label + ' Class',
hAxis: {title: 'Bands'},
vAxis: {title: 'Reflectance',
viewWindowMode:'explicit',
viewWindow: {
max:6000,
min:0
}},
lineWidth: 1,
pointSize: 4,
};
var fc = training_Stratified.filter(ee.Filter.eq('land_class', land_class))
var chart = ui.Chart.feature.byProperty({
features: fc,
xProperties: bandDescriptions,
})
.setChartType('ScatterChart')
.setOptions(options);
print(chart)
}
classChart(0, 'Water')
classChart(1, 'Residential')
classChart(2, 'Agricultural')
classChart(3, 'Arbusti')
classChart(4, 'BoschiMisti')
classChart(5, 'Latifoglie')
classChart(6, 'Conifere')
classChart(7, 'BareSoil')
I receive the error:
Error generating chart: Image.select: Pattern 'B1' did not match any
bands.
I do not understand where is the problem since I used the same script before to draw histogram of training data and it worked well.