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 = samplespi]

    if (sample.dataMask == 1){

     sumOfValidSamplesB02 += sample.B02

     sumOfValidSamplesB03 += sample.B03

     sumOfValidSamplesB04 += sample.B04

     sumOfValidSamplesB08 += sample.B08

     numberOfValidSamples += 1

    }

    

  }

  return u(sumOfValidSamplesB02 / numberOfValidSamples) * factor,

          (sumOfValidSamplesB03 / numberOfValidSamples) * factor,

         (sumOfValidSamplesB04 / numberOfValidSamples) * factor,

         (sumOfValidSamplesB08 / numberOfValidSamples) * factor]

}



function updateOutputMetadata(scenes, inputMetadata, outputMetadata) {

  outputMetadata.userData = {

    "inputMetadata": inputMetadata

  }

  outputMetadata.userDataD"orbits"] = scenes.orbits

}