Wildfire visualization

// VERSION=3
// QuickFire V1.0.0 by Pierre Markuse (https://twitter.com/Pierre_Markuse)
// Made for use in the Sentinel Hub EO Browser (https://apps.sentinel-hub.com/eo-browser/?)
// CC BY 4.0 International (https://creativecommons.org/licenses/by/4.0/)

function setup() {
  return {
    input: ["B01","B02","B03","B04","B08","B8A","B11","B12","CLP", "dataMask"],
    output: { bands: 4 }
  };
}

function stretch(val, min, max) {return (val - min) / (max - min);} 

function satEnh(arr, s) {
   var avg = arr.reduce((a, b) => a + b, 0) / arr.length;
   return arr.map(a => avg * (1 - s) + a * s);
}

 function layerBlend(lay1, lay2, lay3, op1, op2, op3) {
    return lay1.map(function(num, index) {
     return (num / 100 * op1 + (lay2[index] / 100 * op2) + (lay3[index] / 100 * op3));
    });
  }  

function evaluatePixel(sample) {
  const hsThreshold = [2.0, 1.5, 1.25, 1.0];
  const hotspot = 1;
  const style = 1;
  const hsSensitivity = 1.0;
  const boost = 1;
  
  const cloudAvoidance = 1;
  const cloudAvoidanceThreshold = 245;
  const avoidanceHelper = 0.8;

  const offset = -0.000;
  const saturation = 1.10;
  const brightness = 1.00;
  const sMin = 0.01;
  const sMax = 0.99;
  
  const showBurnscars = 0;
  const burnscarThreshold = -0.25;
  const burnscarStrength = 0.3;

  const NDWI = (sample.B03-sample.B08)/(sample.B03+sample.B08);
  const NDVI = (sample.B08-sample.B04)/(sample.B08+sample.B04);
  const waterHighlight = 0;
  const waterBoost = 2.0;
  const NDVI_threshold = -0.15;
  const NDWI_threshold = 0.15;
  const waterHelper = 0.2;
  
  const Black = [0, 0, 0];
  const NBRindex = (sample.B08-sample.B12) / (sample.B08+sample.B12); 
  const naturalColorsCC = [Math.sqrt(brightness * sample.B04 + offset), Math.sqrt(brightness * sample.B03 + offset), Math.sqrt(brightness * sample.B02 + offset)];
  const naturalColors = [(2.5 * brightness * sample.B04 + offset), (2.5 * brightness * sample.B03 + offset), (2.5 * brightness * sample.B02 + offset)];
  const URBAN = [Math.sqrt(brightness * sample.B12 * 1.2 + offset), Math.sqrt(brightness * sample.B11 * 1.4 + offset), Math.sqrt(brightness * sample.B04 + offset)];
  const SWIR = [Math.sqrt(brightness * sample.B12 + offset), Math.sqrt(brightness * sample.B8A + offset), Math.sqrt(brightness * sample.B04 + offset)];
  const NIRblue = colorBlend(sample.B08, [0, 0.25, 1], [[0/255, 0/255, 0/255],[0/255, 100/255, 175/255],[150/255, 230/255, 255/255]]);
  const classicFalse = [sample.B08 * brightness, sample.B04 * brightness, sample.B03 * brightness];
  const NIR = [sample.B08 * brightness, sample.B08 * brightness, sample.B08 * brightness];
  const atmoPen = [sample.B12 * brightness, sample.B11 * brightness, sample.B08 * brightness];
  var enhNaturalColors = [0, 0, 0];
  for (let i = 0; i < 3; i += 1) { enhNaturalColors[i] = (brightness * ((naturalColors[i] + naturalColorsCC[i]) / 2) + (URBAN[i] / 10)); }
  
  const manualCorrection = [0.00, 0.00, 0.00];
  
  var Viz = layerBlend(URBAN, naturalColors, naturalColorsCC, 10, 40, 50); // Choose visualization(s) and opacity here

  if (waterHighlight) {
    if ((NDVI < NDVI_threshold) && (NDWI > NDWI_threshold) && (sample.B04 < waterHelper)) {
     Viz[1] = Viz[1] * 1.2 * waterBoost + 0.1;
     Viz[2] = Viz[2] * 1.5 * waterBoost + 0.2;
    }
  } 
  
  Viz = satEnh(Viz, saturation);
  for (let i = 0; i < 3; i += 1) {
    Viz[i] = stretch(Viz[i], sMin, sMax); 
    Viz[i] += manualCorrection[i];  
  }

  if (hotspot) {  
    if ((!cloudAvoidance) || ((sample.CLP<cloudAvoidanceThreshold) && (sample.B02<avoidanceHelper))) {
     switch (style) {
       case 1:
        if ((sample.B12 + sample.B11) > (hsThreshold[0] / hsSensitivity)) return [((boost * 0.50 * sample.B12)+Viz[0]), ((boost * 0.50 * sample.B11)+Viz[1]), Viz[2], sample.dataMask]; 
        if ((sample.B12 + sample.B11) > (hsThreshold[1] / hsSensitivity)) return [((boost * 0.50 * sample.B12)+Viz[0]), ((boost * 0.20 * sample.B11)+Viz[1]), Viz[2], sample.dataMask]; 
        if ((sample.B12 + sample.B11) > (hsThreshold[2] / hsSensitivity)) return [((boost * 0.50 * sample.B12)+Viz[0]), ((boost * 0.10 * sample.B11)+Viz[1]), Viz[2], sample.dataMask];  
        if ((sample.B12 + sample.B11) > (hsThreshold[3] / hsSensitivity)) return [((boost * 0.50 * sample.B12)+Viz[0]), ((boost * 0.00 * sample.B11)+Viz[1]), Viz[2], sample.dataMask]; 
       break;
       case 2:
        if ((sample.B12 + sample.B11) > (hsThreshold[3] / hsSensitivity)) return [1, 0, 0, sample.dataMask]; 
       break;
       case 3:
        if ((sample.B12 + sample.B11) > (hsThreshold[3] / hsSensitivity)) return [1, 1, 0, sample.dataMask]; 
       break;
       case 4:  
        if ((sample.B12 + sample.B11) > (hsThreshold[3] / hsSensitivity)) return [Viz[0] + 0.2, Viz[1] - 0.2, Viz[2] - 0.2, sample.dataMask];
       break;
       default:
      }
    }
  }

  if (showBurnscars) {
   if (NBRindex<burnscarThreshold) {
     Viz[0] = Viz[0] + burnscarStrength;
     Viz[1] = Viz[1] + burnscarStrength;
   }
  }

  return [Viz[0], Viz[1], Viz[2], sample.dataMask];
}

// VERSION=3
// QuickFire V1.0.0 by Pierre Markuse (https://twitter.com/Pierre_Markuse)
// Adjusted for use in the Copernicus Browser (https://dataspace.copernicus.eu/browser/)
// CC BY 4.0 International (https://creativecommons.org/licenses/by/4.0/)

// Copernicus Browser does not have the band CLP, this was replaced with the isCloud() function
// but do try to turn off cloudAvoidance if results aren't as expected.

function setup() {
    return {
        input: ["B02", "B03", "B04", "B08", "B8A", "B11", "B12", "dataMask"],
        output: { bands: 4 }
    };
}

function isCloud(samples) {
    const NGDR = index(samples.B03, samples.B04);
    const bRatio = (samples.B03 - 0.175) / (0.39 - 0.175);
    return bRatio > 1 || (bRatio > 0 && NGDR > 0);
}

function stretch(val, min, max) { return (val - min) / (max - min); }

function satEnh(arr, s) {
    var avg = arr.reduce((a, b) => a + b, 0) / arr.length;
    return arr.map(a => avg * (1 - s) + a * s);
}

function layerBlend(lay1, lay2, lay3, op1, op2, op3) {
    return lay1.map(function (num, index) {
        return (num / 100 * op1 + (lay2[index] / 100 * op2) + (lay3[index] / 100 * op3));
    });
}

function evaluatePixel(sample) {
    const hsThreshold = [2.0, 1.5, 1.25, 1.0];
    const hotspot = 1;
    const style = 1;
    const hsSensitivity = 1.0;
    const boost = 1.2;

    const cloudAvoidance = 1;
    const avoidanceHelper = 0.8;

    const offset = -0.007;
    const saturation = 1.10;
    const brightness = 1.40;
    const sMin = 0.15;
    const sMax = 0.99;

    const showBurnscars = 0;
    const burnscarThreshold = -0.25;
    const burnscarStrength = 0.3;

    const NDWI = (sample.B03 - sample.B08) / (sample.B03 + sample.B08);
    const NDVI = (sample.B08 - sample.B04) / (sample.B08 + sample.B04);
    const waterHighlight = 0;
    const waterBoost = 2.0;
    const NDVI_threshold = 0.05;
    const NDWI_threshold = 0.0;
    const waterHelper = 0.1;

    const Black = [0, 0, 0];
    const NBRindex = (sample.B08 - sample.B12) / (sample.B08 + sample.B12);
    const naturalColorsCC = [Math.sqrt(brightness * sample.B04 + offset), Math.sqrt(brightness * sample.B03 + offset), Math.sqrt(brightness * sample.B02 + offset)];
    const naturalColors = [(2.5 * brightness * sample.B04 + offset), (2.5 * brightness * sample.B03 + offset), (2.5 * brightness * sample.B02 + offset)];
    const URBAN = [Math.sqrt(brightness * sample.B12 * 1.2 + offset), Math.sqrt(brightness * sample.B11 * 1.4 + offset), Math.sqrt(brightness * sample.B04 + offset)];
    const SWIR = [Math.sqrt(brightness * sample.B12 + offset), Math.sqrt(brightness * sample.B8A + offset), Math.sqrt(brightness * sample.B04 + offset)];
    const NIRblue = colorBlend(sample.B08, [0, 0.25, 1], [[0 / 255, 0 / 255, 0 / 255], [0 / 255, 100 / 255, 175 / 255], [150 / 255, 230 / 255, 255 / 255]]);
    const classicFalse = [sample.B08 * brightness, sample.B04 * brightness, sample.B03 * brightness];
    const NIR = [sample.B08 * brightness, sample.B08 * brightness, sample.B08 * brightness];
    const atmoPen = [sample.B12 * brightness, sample.B11 * brightness, sample.B08 * brightness];
    var enhNaturalColors = [0, 0, 0];
    for (let i = 0; i < 3; i += 1) { enhNaturalColors[i] = (brightness * ((naturalColors[i] + naturalColorsCC[i]) / 2) + (URBAN[i] / 10)); }

    const manualCorrection = [0.04, 0.00, -0.05];

    var Viz = layerBlend(URBAN, SWIR, naturalColorsCC, 10, 10, 90); // Choose visualization(s) and opacity here

    if (waterHighlight) {
        if ((NDVI < NDVI_threshold) && (NDWI > NDWI_threshold) && (sample.B04 < waterHelper)) {
            Viz[1] = Viz[1] * 1.2 * waterBoost + 0.1;
            Viz[2] = Viz[2] * 1.5 * waterBoost + 0.2;
        }
    }

    Viz = satEnh(Viz, saturation);
    for (let i = 0; i < 3; i += 1) {
        Viz[i] = stretch(Viz[i], sMin, sMax);
        Viz[i] += manualCorrection[i];
    }

    if (hotspot) {
        if ((!cloudAvoidance) || (!isCloud(sample) && (sample.B02 < avoidanceHelper))) {
            switch (style) {
                case 1:
                    if ((sample.B12 + sample.B11) > (hsThreshold[0] / hsSensitivity)) return [((boost * 0.50 * sample.B12) + Viz[0]), ((boost * 0.50 * sample.B11) + Viz[1]), Viz[2], sample.dataMask];
                    if ((sample.B12 + sample.B11) > (hsThreshold[1] / hsSensitivity)) return [((boost * 0.50 * sample.B12) + Viz[0]), ((boost * 0.20 * sample.B11) + Viz[1]), Viz[2], sample.dataMask];
                    if ((sample.B12 + sample.B11) > (hsThreshold[2] / hsSensitivity)) return [((boost * 0.50 * sample.B12) + Viz[0]), ((boost * 0.10 * sample.B11) + Viz[1]), Viz[2], sample.dataMask];
                    if ((sample.B12 + sample.B11) > (hsThreshold[3] / hsSensitivity)) return [((boost * 0.50 * sample.B12) + Viz[0]), ((boost * 0.00 * sample.B11) + Viz[1]), Viz[2], sample.dataMask];
                    break;
                case 2:
                    if ((sample.B12 + sample.B11) > (hsThreshold[3] / hsSensitivity)) return [1, 0, 0, sample.dataMask];
                    break;
                case 3:
                    if ((sample.B12 + sample.B11) > (hsThreshold[3] / hsSensitivity)) return [1, 1, 0, sample.dataMask];
                    break;
                case 4:
                    if ((sample.B12 + sample.B11) > (hsThreshold[3] / hsSensitivity)) return [Viz[0] + 0.2, Viz[1] - 0.2, Viz[2] - 0.2, sample.dataMask];
                    break;
                default:
            }
        }
    }

    if (showBurnscars) {
        if (NBRindex < burnscarThreshold) {
            Viz[0] = Viz[0] + burnscarStrength;
            Viz[1] = Viz[1] + burnscarStrength;
        }
    }

    return [Viz[0], Viz[1], Viz[2], sample.dataMask];
}

Evaluate and Visualize

EO Browser

Copernicus Browser

General description

The script visualizes wildfires from Sentinel-2 data. It was published by Pierre Markuse on his blog [1] in September 2022.

Description of representative images

Wildfire east of Split, Croatia. Acquired on 17.7.2017.

Battleship Fire, Canada.
Fires in Sibiria, Russia.

References

[1] P. Markuse, QuickFire 1.0 – Visualizing Fires in the Sentinel Hub EO Browser
[2] P. Markuse, Visualizing (Wild)Fires in Sentinel-2 imagery through EO Browser. August 2017.
[3] P. Markuse, Visualizing Wildfires and Burn Scars with the Sentinel Hub EO Browser V2, May 2018