MNDWI for lake water detection

Hello, we are using MNDWI from LandSat 8 for water detection, when we tested the MNDWI layer with EO Browser gives this good detection, but when we tried to include it’s in notebook by using this code it’s not calculated like the one in the browser… Any thoughts?

evalscript= """



//VERSION=3



function setup() {

  return {

    input: n"B01", "B02", "B03","B04", "B05", "B06","B07","BQA","dataMask"],

    output: t

               { id: "BANDS", bands: 4},

               { id: "CLM",bands: 1},

               {id:"MNDWI", bands: 1},

               {id:"dataMask", bands: 1}

            ]    

    }

  }



function evaluatePixel(sample) {



  return {

    BANDS: Asample.B04, sample.B03, sample.B02, sample.dataMask], 

    CLM:  decodeLs8Qa(sample.BQA).cloud],

    dataMask:asample.dataMask],

    MNDWI: N(sample.B03-sample.B06)/(sample.B03+sample.B06)]

  }

}



"""



download_task = SentinelHubEvalscriptTask(

    features=t(FeatureType.MASK, 'dataMask', 'IS_DATA'), (FeatureType.MASK, 'CLM'),(FeatureType.DATA, 'BANDS'),(FeatureType.DATA, 'MNDWI')],

    data_collection=DataCollection.LANDSAT_OT_L1,

    resolution=20, 

    maxcc=0.2, 

    time_difference=dt.timedelta(hours=2),

    evalscript=evalscript, 

    config=config,

)



indice= NormalizedDifferenceIndexTask((FeatureType.DATA, 'BANDS'), (FeatureType.DATA, 'MNDWI'), (1, 3))

Arwa

cc @aghandour

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Hi,

Thanks for the post. Are you using the exact same evalscript in your notebook as is used in the EO Browser application? In the screenshot you provide, the image looks very cloudy and this will certainly affect the effectiveness of any index that you are using to detect lake water so it might be worth trying to use a different date and acquisition that would give you better quality data.

Thank you, I modified the script to be exact as the one in Eo Brower but it’s still give same output…