老年人手抖是什么原因

Question

I'm calculating the ndti for a water body over a time period and have successfully made the ndti calculation and can view the results for each time period. In the layer settings I have to set results to greyscale and then set the color palette. I would like to do this programmatically, but am new to GEE and having difficulties. When I set the color palette in Map.addLayer I get an error "ndti: Layer error: Image.visualize: Cannot provide a palette when visualizing more than one band." I understand the error. It seems like I need to convert the multiband to single band first and have tried various additions of

var grayscale = image.expression(
  '(0.299 * R) + (0.587 * G) + (0.114 * B)', {
    'R': image.select('B4'),
    'G': image.select('B3'),
    'B': image.select('B2')
  }
);

to the code but run into other errors with applying to image collection. Not sure how to resolve. Any suggestions would be appreciated.

// Add Sentinel 2 Images and filter
var sentinelImage = ee.ImageCollection("COPERNICUS/S2_SR_HARMONIZED")
   .select(['B3','B4','B8'])
  .filterDate('2025-08-06','2025-08-06')
  .filterBounds(AOI)
  .filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE',45))
  
.map(function(img){
  var bands = img.select('B3','B4','B8').multiply(0.0001)
  //Create watermask
  var ndwi = bands.normalizedDifference(['B3','B8']).rename('ndwi')
  var watermask = ndwi.gt(0.1)
  //Calculate ndti
  var ndti = bands.normalizedDifference(['B4','B3']).rename('ndti')
  //Mask non-water areas
  return ndti.updateMask(watermask)
  .copyProperties(img,['system:time_start','system:time_end'])
  })

var palette = ['blue', 'green', 'yellow', 'red'];
var vis = {
     min: -1,
     max: 1,
     palette: palette
   };

Map.addLayer(sentinelImage.toBands().clip(AOI), vis, 'ndti', false);
print(sentinelImage);

Answer 1

toBands() is converting your ImageColection with N images to a single Image with N bands which is probably not what you want for display. You can display a mosaiced version of the image collection or reduce it to a single image, see Map.addLayer and various reducers such as ImageCollection.mean

// Add Sentinel 2 Images and filter
var sentinelImage = ee.ImageCollection("COPERNICUS/S2_SR_HARMONIZED")
   .select(['B3','B4','B8'])
  .filterDate('2025-08-06','2025-08-06')
  .filterBounds(AOI)
  .filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE',45))
  .map(function(img){
    var bands = img
      .select('B3','B4','B8')
      .clip(AOI)
      .multiply(0.0001)
    //Create watermask
    var ndwi = bands.normalizedDifference(['B3','B8']).rename('ndwi');
    var watermask = ndwi.gt(0.1);
    //Calculate ndti
    var ndti = bands.normalizedDifference(['B4','B3']).rename('ndti');
    //Mask non-water areas
    return ndti
      .updateMask(watermask)
      .copyProperties(img,['system:time_start','system:time_end']);
  })

var palette = ['blue', 'green', 'yellow', 'red'];
var vis = {
     min: -1,
     max: 1,
     palette: palette
   };

// Images within ImageCollections are automatically mosaicked according to mask
// status and image order. The last image in the collection takes priority,
// invalid pixels are filled by valid pixels in preceding images.
Map.addLayer(sentinelImage, vis, 'ndti mosaiced', false);

// Reduce the collection to a single image using a variety of methods.
var mean = sentinelImage.median();
Map.addLayer(sentinelImage, vis, 'ndti median', false);

var mean = sentinelImage.mean();
Map.addLayer(sentinelImage, vis, 'ndti mean', false);

var min = sentinelImage.min();
Map.addLayer(min, vis, 'ndti min');

var max = sentinelImage.max();
Map.addLayer(max, vis, 'ndti max');

// Or add them all individually
var image_count = sentinelImage.size().getInfo();
var image_list = sentinelImage.toList(image_count); 
print(image_count);
for(var i = 0; i < image_count; i++){  //Warning client side loop, will be slow!
  var image = ee.Image(image_list.get(i));
  var date = image.date().format('YYYY-MM-dd').getInfo();
  Map.addLayer(image, vis, date, false);
  
}