Hi,

this is possible. If you calculate in your custom script a “mask” for NDVI larger than 0.8,
like

let NDVI_ABOVE_08 = (NDVI > 0.80) ? 1 : 0;

and add it to the output bands, then StatAPI will aggregate values of this band over all pixels. mean value of NDVI_ABOVE_08 in this case will represent the fraction of pixels within the request geometry with NDVI value above 0.8.

Best

thank you for the fast respond! if I want to get precentage between two values, how will that be written?

Two options:

• add output for larger than and lower than

let NDVI_UNDER_04 = (NDVI < 0.40) ? 1 : 0;

let NDVI_UNDER_08 = (NDVI < 0.80) ? 1 : 0;

• or join the conditions in a single output

let NDVI_IN_BETWEEN = (NDVI > 0.40 && NDVI < 0.8) ? 1 : 0;

In the first case you would then subtract fractions of pixels under 0.8 and 0.4.

I have tried to add this to my evalscript but get errors:

ndvi_evalscript= """

//VERSION=3



function setup() {

  return {

    input: [

      {

        bands: [

          "B04",

          "B08",

          "dataMask"

        ]

      }

    ],

    output: [

      {

        id: "ndvi",

        bands: 1

      },

      {

        id: "dataMask",

        bands: 1

      }

    ]

  }

}



function evaluatePixel(samples) {

    return {

      let NDVI=index(samples.B08, samples.B04)

      let NDVI_UNDER_04 = (NDVI < 0.40) ? 1 : 0;

      ndvi: [NDVI,NDVI_UNDER_04],

      dataMask: [samples.dataMask]

    };

}

"""





#run statistics like in the documentation

yearly_time_interval = '2020-01-01', '2020-12-31'





aggregation = SentinelHubStatistical.aggregation(

    evalscript=ndvi_evalscript,

    time_interval=yearly_time_interval,

    aggregation_interval='P1D',

    resolution=(10, 10)

)



input_data = SentinelHubStatistical.input_data(

    DataCollection.SENTINEL2_L2A

)



histogram_calculations = {

    "ndvi": {

        "histograms": {

            "default": {

                "nBins": 20,

                "lowEdge": -1.0,

                "highEdge": 1.0

            }

        }

    }

}



ndvi_requests = []



for geo_shape in polygons_gdf.geometry.values:

    request = SentinelHubStatistical(

        aggregation=aggregation,

        input_data=[input_data],

        geometry=Geometry(geo_shape, crs=CRS(polygons_gdf.crs)),

        calculations=histogram_calculations,

        config=config

    )

    ndvi_requests.append(request)



%%time



download_requests = [ndvi_request.download_list[0] for ndvi_request in ndvi_requests]



client = SentinelHubStatisticalDownloadClient(config=config)



ndvi_stats = client.download(download_requests)



len(ndvi_stats)

That part runs but when I print the ndvi_stats can see error of bad request/execution error:

[{'data': [{'interval': {'from': '2020-01-04T00:00:00Z',

     'to': '2020-01-05T00:00:00Z'},

    'error': {'type': 'EXECUTION_ERROR'}},

   {'interval': {'from': '2020-01-09T00:00:00Z', 'to': '2020-01-10T00:00:00Z'},

    'error': {'type': 'EXECUTION_ERROR'}},

   {'interval': {'from': '2020-01-14T00:00:00Z', 'to': '2020-01-15T00:00:00Z'},

    'error': {'type': 'EXECUTION_ERROR'}},

   {'interval': {'from': '2020-01-19T00:00:00Z', 'to': '2020-01-20T00:00:00Z'},

    'error': {'type': 'EXECUTION_ERROR'}},

   {'interval': {'from': '2020-01-24T00:00:00Z', 'to': '2020-01-25T00:00:00Z'},

    'error': {'type': 'BAD_REQUEST'}},

.....

When I run this withou the NDVI_UNDER etc. it works just like in the tutorial.

Do you see my mistake?

thanks a lot

The mistake is in the setup part: you defined “ndvi” output to contain single band, but your evalscript is returning 2.

Additionally, the let parts of the evaluatePixel should be outside the return statement.

Thank you, that worked but it seems like the query returns 1 or 0 but not the percentage itself

How large is your area? If there is only a single Sentinel-2 pixel, that would be expected.

it is more than one pixel for sure

maybe is something about the data type?

One thing to check is the geometry and it’s CRS. If you are making requests for geometries in WGS84, then the resolution you specify in aggregation is in degrees! Your geometries are probably smaller than 10deg x 10deg, meaning the result is for 1 pixel.

Thank you, that was the issue