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LAI (Leaf Area Index)

//VERSION=3 (auto-converted from 2)
var degToRad = Math.PI / 180;

function evaluatePixelOrig(samples) {
  var sample = samples[0];
  var b03_norm = normalize(sample.B03, 0, 0.253061520471542);
  var b04_norm = normalize(sample.B04, 0, 0.290393577911328);
  var b05_norm = normalize(sample.B05, 0, 0.305398915248555);
  var b06_norm = normalize(sample.B06, 0.006637972542253, 0.608900395797889);
  var b07_norm = normalize(sample.B07, 0.013972727018939, 0.753827384322927);
  var b8a_norm = normalize(sample.B8A, 0.026690138082061, 0.782011770669178);
  var b11_norm = normalize(sample.B11, 0.016388074192258, 0.493761397883092);
  var b12_norm = normalize(sample.B12, 0, 0.493025984460231);
  var viewZen_norm = normalize(Math.cos(sample.viewZenithMean * degToRad), 0.918595400582046, 1);
  var sunZen_norm  = normalize(Math.cos(sample.sunZenithAngles * degToRad), 0.342022871159208, 0.936206429175402);
  var relAzim_norm = Math.cos((sample.sunAzimuthAngles - sample.viewAzimuthMean) * degToRad)

  var n1 = neuron1(b03_norm,b04_norm,b05_norm,b06_norm,b07_norm,b8a_norm,b11_norm,b12_norm, viewZen_norm,sunZen_norm,relAzim_norm);
  var n2 = neuron2(b03_norm,b04_norm,b05_norm,b06_norm,b07_norm,b8a_norm,b11_norm,b12_norm, viewZen_norm,sunZen_norm,relAzim_norm);
  var n3 = neuron3(b03_norm,b04_norm,b05_norm,b06_norm,b07_norm,b8a_norm,b11_norm,b12_norm, viewZen_norm,sunZen_norm,relAzim_norm);
  var n4 = neuron4(b03_norm,b04_norm,b05_norm,b06_norm,b07_norm,b8a_norm,b11_norm,b12_norm, viewZen_norm,sunZen_norm,relAzim_norm);
  var n5 = neuron5(b03_norm,b04_norm,b05_norm,b06_norm,b07_norm,b8a_norm,b11_norm,b12_norm, viewZen_norm,sunZen_norm,relAzim_norm);

  var l2 = layer2(n1, n2, n3, n4, n5);

  var lai = denormalize(l2, 0.000319182538301, 14.4675094548151);
  return {
    default: [lai / 3]
  }
}

function neuron1(b03_norm,b04_norm,b05_norm,b06_norm,b07_norm,b8a_norm,b11_norm,b12_norm, viewZen_norm,sunZen_norm,relAzim_norm) {
  var sum =
	+ 4.96238030555279
	- 0.023406878966470 * b03_norm
	+ 0.921655164636366 * b04_norm
	+ 0.135576544080099 * b05_norm
	- 1.938331472397950 * b06_norm
	- 3.342495816122680 * b07_norm
	+ 0.902277648009576 * b8a_norm
	+ 0.205363538258614 * b11_norm
	- 0.040607844721716 * b12_norm
	- 0.083196409727092 * viewZen_norm
	+ 0.260029270773809 * sunZen_norm
	+ 0.284761567218845 * relAzim_norm;

  return tansig(sum);
}

function neuron2(b03_norm,b04_norm,b05_norm,b06_norm,b07_norm,b8a_norm,b11_norm,b12_norm, viewZen_norm,sunZen_norm,relAzim_norm) {
  var sum =
	+ 1.416008443981500
	- 0.132555480856684 * b03_norm
	- 0.139574837333540 * b04_norm
	- 1.014606016898920 * b05_norm
	- 1.330890038649270 * b06_norm
	+ 0.031730624503341 * b07_norm
	- 1.433583541317050 * b8a_norm
	- 0.959637898574699 * b11_norm
	+ 1.133115706551000 * b12_norm
	+ 0.216603876541632 * viewZen_norm
	+ 0.410652303762839 * sunZen_norm
	+ 0.064760155543506 * relAzim_norm;

  return tansig(sum);
}

function neuron3(b03_norm,b04_norm,b05_norm,b06_norm,b07_norm,b8a_norm,b11_norm,b12_norm, viewZen_norm,sunZen_norm,relAzim_norm) {
  var sum =
	+ 1.075897047213310
	+ 0.086015977724868 * b03_norm
	+ 0.616648776881434 * b04_norm
	+ 0.678003876446556 * b05_norm
	+ 0.141102398644968 * b06_norm
	- 0.096682206883546 * b07_norm
	- 1.128832638862200 * b8a_norm
	+ 0.302189102741375 * b11_norm
	+ 0.434494937299725 * b12_norm
	- 0.021903699490589 * viewZen_norm
	- 0.228492476802263 * sunZen_norm
	- 0.039460537589826 * relAzim_norm;

  return tansig(sum);
}

function neuron4(b03_norm,b04_norm,b05_norm,b06_norm,b07_norm,b8a_norm,b11_norm,b12_norm, viewZen_norm,sunZen_norm,relAzim_norm) {
  var sum =
	+ 1.533988264655420
	- 0.109366593670404 * b03_norm
	- 0.071046262972729 * b04_norm
	+ 0.064582411478320 * b05_norm
	+ 2.906325236823160 * b06_norm
	- 0.673873108979163 * b07_norm
	- 3.838051868280840 * b8a_norm
	+ 1.695979344531530 * b11_norm
	+ 0.046950296081713 * b12_norm
	- 0.049709652688365 * viewZen_norm
	+ 0.021829545430994 * sunZen_norm
	+ 0.057483827104091 * relAzim_norm;

  return tansig(sum);
}

function neuron5(b03_norm,b04_norm,b05_norm,b06_norm,b07_norm,b8a_norm,b11_norm,b12_norm, viewZen_norm,sunZen_norm,relAzim_norm) {
  var sum =
	+ 3.024115930757230
	- 0.089939416159969 * b03_norm
	+ 0.175395483106147 * b04_norm
	- 0.081847329172620 * b05_norm
	+ 2.219895367487790 * b06_norm
	+ 1.713873975136850 * b07_norm
	+ 0.713069186099534 * b8a_norm
	+ 0.138970813499201 * b11_norm
	- 0.060771761518025 * b12_norm
	+ 0.124263341255473 * viewZen_norm
	+ 0.210086140404351 * sunZen_norm
	- 0.183878138700341 * relAzim_norm;

  return tansig(sum);
}

function layer2(neuron1, neuron2, neuron3, neuron4, neuron5) {
  var sum =
	+ 1.096963107077220
	- 1.500135489728730 * neuron1
	- 0.096283269121503 * neuron2
	- 0.194935930577094 * neuron3
	- 0.352305895755591 * neuron4
	+ 0.075107415847473 * neuron5;

  return sum;
}

function normalize(unnormalized, min, max) {
  return 2 * (unnormalized - min) / (max - min) - 1;
}
function denormalize(normalized, min, max) {
  return 0.5 * (normalized + 1) * (max - min) + min;
}
function tansig(input) {
  return 2 / (1 + Math.exp(-2 * input)) - 1; 
}

function setup() {
  return {
    input: [{
      bands: [
          "B03",
          "B04",
          "B05",
          "B06",
          "B07",
          "B8A",
          "B11",
          "B12",
          "viewZenithMean",
          "viewAzimuthMean",
          "sunZenithAngles",
          "sunAzimuthAngles"
      ]
    }],
    output: [
        {
          id: "default",
          sampleType: "AUTO",
          bands: 1
        }
    ]
  }
}

function evaluatePixel(sample, scene, metadata, customData, outputMetadata) {
  const result = evaluatePixelOrig([sample], [scene], metadata, customData, outputMetadata);
  return result[Object.keys(result)[0]];
}

Evaluate and Visualize

General description of the script

LAI is a dimensionless index measuring the one-sided green leaf area over a unit of land (m^2 / m^2).

Note that the LAI script is as implemented in SNAP but without input and output validation! Input/output values which are suspect are not reported or changed. Most values, however, do not fall under this category. Visualized as an interval from 0-3. This can be adjusted in the evaluatePixel method.

Description of representative images

Leaf area index, Rome. Acquired on 08.10.2017.

snow classifier