Mosaicing images across orbits in one AOI

Apps / Services Python SDK
1

I am using Sentinel Hub’s Python SDK to download large-scale Sentinel 2/1 imagery. This works great but we still have some issues at the edges of Sentinel orbits, as we are downloading imagery for specific dates as ~5-6 km tiles.

The Python request looks something like this:

image_request = WcsRequest(
            layer='L2A10_ORBIT',
            bbox=box, time=dates,
            image_format = MimeType.TIFF,
            maxcc=1., resx='10m', resy='10m',
            config=api_key,
            custom_url_params = {constants.CustomUrlParam.DOWNSAMPLING: 'BICUBIC',
                                constants.CustomUrlParam.UPSAMPLING: 'BICUBIC'},
            time_difference=datetime.timedelta(hours=48),
    )

Setting time_difference to 48 hours typically allows sentinel-hub to collect images from both orbits, rather than returning one orbit, and no data outside of the orbit bounds.

Here is my setup function in the evalscript, where I have set mosaicking to orbit:

function setup() {
  return {
    input: [{
      bands: [
        "B02",
        "B03",
        "B04",
        "B08",
        "dataMask",
             ]
    }],
    output: {
      bands: 4,
      sampleType:"UINT16",
      mosaicking: "ORBIT"
    }
  }
}

This works insofar as all pixels have data but it appears that the images are superimposed, leaving artifacts. Is it possible to average them? (Or perhaps is there a better way to combine them?) I have tried per the example here but with no success: https://docs.sentinel-hub.com/api/latest/user-guides/metadata/ … e.g. this evaluatePixel only returns 0.


function evaluatePixel(samples, scenes, inputMetadata, customData, outputMetadata) {
  //Average value of band B02 based on the requested scenes
  var sumOfValidSamplesB02 = 0
  var sumOfValidSamplesB03 = 0
  var sumOfValidSamplesB04 = 0
  var sumOfValidSamplesB08 = 0
  var numberOfValidSamples = 0
  var factor = 65535
  for (i = 0; i < samples.length; i++) {
    var sample = samples[i]
    if (sample.dataMask == 1){
     sumOfValidSamplesB02 += sample.B02
     sumOfValidSamplesB03 += sample.B03
     sumOfValidSamplesB04 += sample.B04
     sumOfValidSamplesB08 += sample.B08
     numberOfValidSamples += 1
    }
    
  }
  return [(sumOfValidSamplesB02 / numberOfValidSamples) * factor,
          (sumOfValidSamplesB03 / numberOfValidSamples) * factor,
         (sumOfValidSamplesB04 / numberOfValidSamples) * factor,
         (sumOfValidSamplesB08 / numberOfValidSamples) * factor]
}

function updateOutputMetadata(scenes, inputMetadata, outputMetadata) {
  outputMetadata.userData = {
    "inputMetadata": inputMetadata
  }
  outputMetadata.userData["orbits"] = scenes.orbits
}
2

Solved this! By taking the minimum of each sample rather than the mean.

3

Great! Happy that you solved it John! Thanks for sharing hoe you solved it with the community! :+1: :clap: