Filtering imageCollection to get only images that fully cover a specified geometry

Question

I would like to perform a supervised classification only on the images of the collection that cover the entire geometry Domain. I used ee.Filter.contains but I get an error message in the console:

Number (Error) Filter.contains: Unable to use a collection in an algorithm that requires a feature or image. This may happen when trying to use a collection of collections where a collection of features is expected; use flatten, or map a function to convert inner collections to features. Use clipToCollection (instead of clip) to clip an image to a collection.

Help me. Here is code:

var Domain= 
    /* color: #d63000 */
    /* displayProperties: [
      {
        "type": "rectangle"
      }
    ] */
    ee.FeatureCollection(
        [ee.Feature(
            ee.Geometry.Polygon(
                [[[-0.9131136144573282, 11.80001340655708],
                  [-0.9131136144573282, 11.44960967007124],
                  [-0.4901399816448282, 11.44960967007124],
                  [-0.4901399816448282, 11.80001340655708]]], null, false),
            {
              "system:index": "0"
            })]);


    var filtered= S2
    .filter(ee.Filter.date('2020-01-01', '2021-12-31'))
    .filter(ee.Filter.bounds(Domain))
    .filter(ee.Filter.contains('.geo', Domain))
    .map(maskS2clouds)
    .select('B.*');

Answer 1

If you want to guarantee some help in the future, you should provide a minimal functional code. Fortunately, I can guess that you are using Sentinel 2 products. Sometimes, several images in a determinate area can be truncated or rotated and this is, probably, your problem. For solving this issue with Sentinel 2 products, you can filter by using 'MGRS_TILE' property of images. Following code includes how it can be used this.

var imageVisParam = {"opacity":0.80,"bands":["B4","B3","B2"],"min":2047.736111111111,"max":5400.827586206897,"gamma":1},
    imageVisParam2 = {"opacity":0.38,"bands":["B4","B3","B2"],"min":2139.2986111111113,"max":5428.427586206896,"gamma":1},
    geometry = ee.Geometry.Polygon(
        [[[-113.57089009346218, 39.75553448647049],
          [-113.29073872627468, 39.75553448647049],
          [-113.30172505439968, 39.96636243482577],
          [-113.30172505439968, 40.13035831477493],
          [-113.54891743721218, 40.0883457054044],
          [-113.64779439033718, 39.93267349837581]]]);

var Domain = ee.Geometry.Point(-113.745, 40.16);

function maskS2clouds(image) {
  var qa = image.select('QA60');

  // Bits 10 and 11 are clouds and cirrus, respectively.
  var cloudBitMask = 1 << 10;
  var cirrusBitMask = 1 << 11;

  // Both flags should be set to zero, indicating clear conditions.
  var mask = qa.bitwiseAnd(cloudBitMask).eq(0)
      .and(qa.bitwiseAnd(cirrusBitMask).eq(0));

  return image.updateMask(mask).divide(10000);
}

var S2 = ee.ImageCollection('COPERNICUS/S2_SR');

var filtered1 = S2
    .filter(ee.Filter.date('2020-01-01', '2021-12-31'))
    .filter(ee.Filter.bounds(Domain))
    .filter(ee.Filter.eq('MGRS_TILE', '11TQE'))
    //.filter(ee.Filter.contains('.geo', Domain))
    //.map(maskS2clouds)
    .select('B.*');

print(filtered1);

Map.addLayer(filtered1.mean(), imageVisParam, 'filtered1 mean');
Map.centerObject(filtered1);

var filtered2 = S2
    .filter(ee.Filter.date('2020-01-01', '2021-12-31'))
    .filter(ee.Filter.bounds(Domain))
    .filter(ee.Filter.eq('MGRS_TILE', '12TTK'))
    //.filter(ee.Filter.contains('.geo', Domain))
    //.map(maskS2clouds)
    .select('B.*');

print(filtered2);

Map.addLayer(filtered2.mean(), imageVisParam2, 'filtered2 mean');
Map.addLayer(geometry, {'color':'green'}, 'Domain');

After running above code in GEE editor, it can be observed in following picture, assuming green area is Domain, that this is not intersecting completely filtering1 mean images ('MGRS_TILE' equals '11TQE').

However, this situation changes in following picture filtering for 'MGRS_TILE' equals '12TTK'.

Concluding, complete Image Collection has 292 images in dates range between '2020-01-01' and '2021-12-31'. So, you should filter by 'MGRS_TILE' equals '12TTK' for obtaining 146 images that completely include green area.