How can i get multiple images files with Process API

Apps / Services
1

Hello everyone, I’m trying to make a request that returns me seven images from the past seven days, below is my fetch function:

await fetch(
      'https://services.sentinel-hub.com/api/v1/process',
      {
        method: 'POST',
        headers: {
          'Content-Type': 'application/json',
          Authorization: `Bearer ${token}`,
          Accept: 'application/tar'
        },
        body: JSON.stringify({
          input: {
            bounds: {
              bbox,
              geometry
            },
            data: [
              {
                type: 'sentinel-2-l2a',
                dataFilter: {
                  timeRange: {
                    from: new Date(
                      today.getFullYear(),
                      today.getMonth(),
                      today.getDate() - 7
                    ).toISOString(),
                    to: today.toISOString()
                  }
                }
              }
            ]
          },
          output: {
            width: 512,
            height: 512,
            responses: [
              {
                identifier: 'default',
                format: {
                  type: 'image/png'
                }
              },
              {
                identifier: 'default',
                format: {
                  type: 'image/png'
                }
              },
              {
                identifier: 'default',
                format: {
                  type: 'image/png'
                }
              },
              {
                identifier: 'default',
                format: {
                  type: 'image/png'
                }
              },
              {
                identifier: 'default',
                format: {
                  type: 'image/png'
                }
              },
              {
                identifier: 'default',
                format: {
                  type: 'image/png'
                }
              },
              {
                identifier: 'default',
                format: {
                  type: 'image/png'
                }
              }
            ]
          },
          evalscript: ndviEvalscript
        })
      }
    )

and this is my evalscript:

//VERSION=3

  function setup() {
    return {
      input: ["B04", "B08", "SCL","dataMask"],
      output: [
     			{ id: "default", bands: 4 },
     			{ id: "index", bands: 1, sampleType: "FLOAT32" },
          { id: "eobrowserStats", bands: 2, sampleType: 'FLOAT32' },
          { id: "dataMask", bands: 1 }
  		]
    };
  }

  function evaluatePixel(samples) {
    let val = index(samples.B08, samples.B04);
    let imgVals = null;
    // The library for tiffs works well only if there is only one channel returned.
    // So we encode the "no data" as NaN here and ignore NaNs on frontend.
    const indexVal = samples.dataMask === 1 ? val : NaN;

    if (val<-0.5) imgVals = [0.05,0.05,0.05,samples.dataMask];
    else if (val<-0.2) imgVals = [0.75,0.75,0.75,samples.dataMask];
    else if (val<-0.1) imgVals = [0.86,0.86,0.86,samples.dataMask];
    else if (val<0) imgVals = [0.92,0.92,0.92,samples.dataMask];
    else if (val<0.025) imgVals = [1,0.98,0.8,samples.dataMask];
    else if (val<0.05) imgVals = [0.93,0.91,0.71,samples.dataMask];
    else if (val<0.075) imgVals = [0.87,0.85,0.61,samples.dataMask];
    else if (val<0.1) imgVals = [0.8,0.78,0.51,samples.dataMask];
    else if (val<0.125) imgVals = [0.74,0.72,0.42,samples.dataMask];
    else if (val<0.15) imgVals = [0.69,0.76,0.38,samples.dataMask];
    else if (val<0.175) imgVals = [0.64,0.8,0.35,samples.dataMask];
    else if (val<0.2) imgVals = [0.57,0.75,0.32,samples.dataMask];
    else if (val<0.25) imgVals = [0.5,0.7,0.28,samples.dataMask];
    else if (val<0.3) imgVals = [0.44,0.64,0.25,samples.dataMask];
    else if (val<0.35) imgVals = [0.38,0.59,0.21,samples.dataMask];
    else if (val<0.4) imgVals = [0.31,0.54,0.18,samples.dataMask];
    else if (val<0.45) imgVals = [0.25,0.49,0.14,samples.dataMask];
    else if (val<0.5) imgVals = [0.19,0.43,0.11,samples.dataMask];
    else if (val<0.55) imgVals = [0.13,0.38,0.07,samples.dataMask];
    else if (val<0.6) imgVals = [0.06,0.33,0.04,samples.dataMask];
    else imgVals = [0,0.27,0,samples.dataMask];

    return {
      default: imgVals,
      index: [indexVal],
      eobrowserStats:[val,isCloud(samples.SCL)?1:0],
      dataMask: [samples.dataMask]
    };
  }

  function isCloud (scl) {
    if (scl == 3) { // SC_CLOUD_SHADOW
      return false;
    } else if (scl == 9) { // SC_CLOUD_HIGH_PROBA
      return true;
    } else if (scl == 8) { // SC_CLOUD_MEDIUM_PROBA
      return true;
    } else if (scl == 7) { // SC_CLOUD_LOW_PROBA
      return false;
    } else if (scl == 10) { // SC_THIN_CIRRUS
      return true;
    } else if (scl == 11) { // SC_SNOW_ICE
      return false;
    } else if (scl == 1) { // SC_SATURATED_DEFECTIVE
      return false;
    } else if (scl == 2) { // SC_DARK_FEATURE_SHADOW
        return false;
    }
    return false;
  }

if any other info is needed please let me know and thank you for the attention!

2

Hi,

If you require several image output files from your request, you need to define these separately in the evalscript. Currently, in your request you have seven outputs named default but only a single output named default in your evalscript.

In addition, if you want separate images for separate days, I would recommend that each of these is separate requests with the time range set as each of the time periods. This example shows how you can do this using the Python SDK.

However, please remember that Sentinel-2 has a return period of 5 days so you will not get an image every day from this sensor so this approach doesn’t really make sense.

3

hello, thank you for answering, what i wanted to do is something that I did some time ago with the sentinel JS lib and it was this:

      const layer = new S2L2ALayer({
        instanceId: this.instanceId,
        layerId: 'NDVI'
      })

      const images: Array<{
        url: string
        imageDate: string
        id: string
      }> = []

      const flyOvers = layer.findFlyovers(bbox, fromTime, toTime)

      ;(await flyOvers).forEach(async f => {
        const getMsentinelarams = {
          bbox: bbox,
          fromTime: new Date(f.fromTime.toISOString()),
          toTime: new Date(f.toTime.toISOString()),
          width: 512,
          height: 512,
          format: MimeTypes.PNG,
          geometry: polygon([data.fieldPoints]).geometry
        }

i wanted to get images from the day before because in my application when creating a field it shows the ndvi from 5 or 7 days before then i will just be adding more to the db as the time goes