Calculating LST and NDVI in Single Graph for comparison

Question

I am trying to calculate the LST and NDVI mean values in a Single graph for comparison but somehow my code is giving an error:

Error in map(ID=1_0): Image. select: Pattern 'NDVI' did not match any bands.

    var geometry = ee.Geometry.Polygon(
        [[[-106.30418639794439, 30.500836767799143],
          [-106.30418639794439, 30.202199728834206],
          [-105.87846618310064, 30.202199728834206],
          [-105.87846618310064, 30.500836767799143]]]);

Map.centerObject(geometry);

//cloud mask
function maskL8sr(col) {
  // Bits 3 and 5 are cloud shadow and cloud, respectively.
  var cloudShadowBitMask = (1 << 3);
  var cloudsBitMask = (1 << 5);
  // Get the pixel QA band.
  var qa = col.select('pixel_qa');
  // Both flags should be set to zero, indicating clear conditions.
  var mask = qa.bitwiseAnd(cloudShadowBitMask).eq(0)
                 .and(qa.bitwiseAnd(cloudsBitMask).eq(0));
  return col.updateMask(mask);
}

//vis params
var vizParams = {
  bands: ['B5', 'B6', 'B4'],
  min: 642,
  max: 3307,
  gamma: [1, 0.9, 1.1]
};

var vizParams2 = {
  bands: ['B4', 'B3', 'B2'],
  min: 0,
  max: 3000,
  gamma: 1.4,
};

//load the collection:
var col = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR')
    .map(maskL8sr)
    .filterDate('2020-05-01','2020-08-1')
    .filterBounds(geometry)
    .map(function(image){return image.clip(geometry)});

print('collection', col);

var ndvi_func = function (image) {
  var ndvi_cal = image.normalizedDifference(['B5', 'B4']).rename('NDVI');
  return image.addBands(ndvi_cal);
};

var ndvi = col.map(ndvi_func);
var ndvi_chart=ndvi.select('NDVI')
print(ndvi)
var reduced = ndvi.map(function(image){
  return image.reduceRegions({
    collection:geometry , 
    reducer:ee.Reducer.mean(), 
    scale: 30,
  });
})
//imagen reduction

var image = col.median();
//print('image', image);

Map.addLayer(image, vizParams2);

//median
var ndvi1 = image.normalizedDifference(['B5', 'B4']).rename('NDVI');
var ndviParams = {min: 0.10554729676864096, max: 0.41295681063122924, palette: ['blue', 'white', 'green']};

//print('ndvi1', ndvi1);

//individual LST images

var col_list = col.toList(col.size());

var LST_col = col_list.map(function (ele) {
  
  var date = ee.Image(ele).get('system:time_start');

  var ndvi = ee.Image(ele).normalizedDifference(['B5', 'B4']).rename('NDVI');
  
  // find the min and max of NDVI
  var min = ee.Number(ndvi.reduceRegion({
    reducer: ee.Reducer.min(),
    geometry: geometry,
    scale: 30,
    maxPixels:19562870,
    bestEffort: true
  }).values().get(0));
  
  var max = ee.Number(ndvi.reduceRegion({
    reducer: ee.Reducer.max(),
    geometry: geometry,
    scale: 30,
    maxPixels:19562870,
   bestEffort: true
  }).values().get(0));
  
  var fv = (ndvi.subtract(min).divide(max.subtract(min))).pow(ee.Number(2)).rename('FV');
  
  var a= ee.Number(0.004);
  var b= ee.Number(0.986);
  
  var EM = fv.multiply(a).add(b).rename('EMM');

  var image = ee.Image(ele);

  var LST = image.expression(
    '(Tb/(1 + (0.00115* (Tb / 1.438))*log(Ep)))-273.15', {
      'Tb': image.select('B10').multiply(0.1),
      'Ep': fv.multiply(a).add(b)
  });

  return LST.set('system:time_start', date).float().rename('LST');
  
});

LST_col = ee.ImageCollection(LST_col);

print("LST_col", LST_col);

/////////////////

Map.addLayer(ndvi1, ndviParams, 'ndvi');

//select thermal band 10(with brightness tempereature), no calculation 
var thermal= image.select('B10').multiply(0.1);

var b10Params = {min: 306.4, max: 322.8, palette: ['blue', 'white', 'green']};

Map.addLayer(thermal, b10Params, 'thermal');

// find the min and max of NDVI
var min = ee.Number(ndvi1.reduceRegion({
  reducer: ee.Reducer.min(),
  geometry: geometry,
  scale: 30,
  maxPixels:19562870,
  bestEffort: true
}).values().get(0));

//print('min', min );

var max = ee.Number(ndvi1.reduceRegion({
  reducer: ee.Reducer.max(),
  geometry: geometry,
  scale: 30,
  maxPixels:19562870,
  bestEffort: true
}).values().get(0));

//print('max', max);

//fractional vegetation
var fv = (ndvi1.subtract(min).divide(max.subtract(min))).pow(ee.Number(2)).rename('FV'); 

//print('fv', fv);

//Map.addLayer(fv);

//Emissivity
var a= ee.Number(0.004);
var b= ee.Number(0.986);
var EM = fv.multiply(a).add(b).rename('EMM');

var imageVisParam3 = {min: 0.9865619146722164, max:0.989699971371314};

//Map.addLayer(EM, imageVisParam3,'EMM');

//LST in Celsius Degree bring -273.15
//NB: In Kelvin don't bring -273.15
var LST = col.map(function (image){

  var date = image.get('system:time_start');
  
  var LST = image.expression(
    '(Tb/(1 + (0.00115* (Tb / 1.438))*log(Ep)))-273.15', {
    'Tb': thermal.select('B10'),
    'Ep':EM.select('EMM')
  }).float().rename('LST');
  
  return LST.set('system:time_start', date);
  
});

print(LST);

Map.addLayer(LST, {min: 34.22748947143555, max: 50.7606086730957, palette: [
'040274', '040281', '0502a3', '0502b8', '0502ce', '0502e6',
'0602ff', '235cb1', '307ef3', '269db1', '30c8e2', '32d3ef',
'3be285', '3ff38f', '86e26f', '3ae237', 'b5e22e', 'd6e21f',
'fff705', 'ffd611', 'ffb613', 'ff8b13', 'ff6e08', 'ff500d',
'ff0000', 'de0101', 'c21301', 'a71001', '911003'
]},'LST');

// merge the collections
var merged = LST_col.merge(ndvi_chart).select(['NDVI', 'LST'])
// plot the collection
var chart = ui.Chart.image.series({
  imageCollection: merged,
  region: geometry,
  reducer: ee.Reducer.mean(),
  scale: 500
})
print(chart)

Answer 1

Deleting 'select' part in following line:

var merged = LST_col.merge(ndvi_chart).select(['NDVI', 'LST'])

to get this:

var merged = LST_col.merge(ndvi_chart)

the code runs without any problem. However, as NDVI values are very small as compared to LST temperature values, your result will look as follows:

Variations in NDVI values are not observable.