script.js

//VERSION=3
//Author: Maxim Lamare

function setup() {
  return {
    input: [
      {datasource: "S1GRD", bands:["VV", "VH"]},
      {datasource: "S2L2A", bands:["B02", "B03", "B08", "B04", "SCL"]}],
    output: [
      {id: "default", bands: 3, sampleType: SampleType.AUTO}
    ]
  }
}

function toDb(linear) {
  // Convert the linear backscatter to DB (Filgueiras et al. (2019), eq. 3)
  return 10 * Math.LN10 * linear
}

function calc_s1_ndvi(sigmaVV, sigmaVH){
    // Convert sigma0 to Decibels
    let vh_Db = toDb(sigmaVH)
    let vv_Db = toDb(sigmaVV)

    // Calculate NRPB (Filgueiras et al. (2019), eq. 4)
    let NRPB = (vh_Db - vv_Db) / (vh_Db + vv_Db)

    // Calculate NDVI_nc with approach A3 (Filgueiras et al. (2019), eq. 14)
    let NDVInc = 2.572 - 0.05047 * vh_Db + 0.176 * vv_Db + 3.422 * NRPB

    return NDVInc
}

function evaluatePixel(samples) {
  var s1 = samples.S1GRD[0]
  var s2 = samples.S2L2A[0]

  // Create an NDVI visualiser
  var viz=new ColorMapVisualizer([[0.0,0xa50026],
                                  [0.0,0xd73027], [0.2,0xf46d43],
                                  [0.3,0xfdae61], [0.4,0xfee08b],
                                  [0.5,0xffffbf], [0.6,0xd9ef8b],
                                  [0.7,0xa6d96a], [0.8,0x66bd63],
                                  [0.9,0x1a9850], [1.0,0x006837]]);
  // Calculate S2 NDVI
  let ndvi = index(s2.B08, s2.B04)
  // Calculate S1 NDVI
  let s1_ndvi = calc_s1_ndvi(s1.VV, s1.VH)

  // Use the S2-L2A classification to identify clouds
  if ([7, 8, 9, 10].includes(s2.SCL)) {
    // If clouds are present use S1 NDVI
    return {
      default: viz.process(s1_ndvi)
    }
  } else {
    // Otherwise use s2 NDVI
    return {
      default: viz.process(ndvi)
    }
  }
}