0

I am not able to solve the issue with my code chunk here in Google Earth Engine. The error I encounter are: Unknown element type provided: object. Expected: ee.Image, ee.ImageCollection, ee.FeatureCollection, ee.Element or ee.ComputedObject. LST: Layer error: Parameter 'right' is required.

Editing the code would be most helpful.

Here is my code

`var imageVisParam = {min: 303, max: 323, palette: ['yellow', 'red', 'purple', 'blue']};
var imageVisParam2 = {min: 0.96, max: 1, palette: ['white', 'orange', 'brown']};

//cloud mask
function maskL8sr(image) {
  // 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 = image.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 image.updateMask(mask);
}

//vis params
var vizParams = {
  bands: ['B5', 'B6', 'B4'],
  min: 0,
  max: 4000,
  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('2018-01-01','2018-12-31')
.filterBounds(geometry);
}
print(col, 'coleccion');

//median
{
var image = col.median();
print(image, 'image');
Map.addLayer(image, vizParams2);
}

// NDVI:
{
var ndvi = image.normalizedDifference(['B5', 'B4']).rename('NDVI');
var ndviParams = {min: -1, max: 1, palette: ['blue', 'white', 'green']};
print(ndvi,'ndvi');
Map.addLayer(ndvi, ndviParams, 'ndvi');
}

//

//select thermal band 10(with brightness tempereature), no BT calculation 
 var thermal= image.select('B10').multiply(1000);
 Map.addLayer(thermal, imageVisParam, 'thermal');
 
 
// find the min and max of NDVI
{
var min = ee.Number(ndvi.reduceRegion({
   reducer: ee.Reducer.min(),
   geometry: geometry,
   scale: 30,
   maxPixels: 1e9
   }).values().get(0));
print(min, 'min');
var max = ee.Number(ndvi.reduceRegion({
    reducer: ee.Reducer.max(),
   geometry: geometry,
   scale: 30,
   maxPixels: 1e9
   }).values().get(0));
print(max, 'max')
}

//fractional vegetation
{
var fv = ndvi.subtract(min).divide(max.subtract(min)).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');
  Map.addLayer(EM, imageVisParam2,'EMM');


  //LST c,d,f, p1, p2, p3 are assigned variables to write equaton easily
  var c= ee.Number(1);
  var d= ee.Number(0.00115);
  var f= ee.Number(1.4388);


var p1= ee.Number(thermal.multiply(d).divide(f));
var p2= ee.Number(Math.log(EM));
var p3= ee.Number((p1.multiply(p2)).add(c));


  var LST= (thermal.divide(p3)).rename('LST');
  
  var LSTimage = ee.Image(LST)
  
  Map.addLayer(LSTimage, {min: 0, max: 350, palette: ['FF0000', 
  '00FF00']},'LST');

// Define the export region
var exportRegion = geometry;

// Export the LST image to Google Drive
Export.image.toDrive({
  image: LSTimage,
  description: 'LST_image1',
  region: exportRegion,
  scale: 30,
  crs: 'EPSG:4326'
}, 'LST_image1');

0 Answers0