Soil Water Content Backward Average 

//VERSION=3

const nDays = 20; // The number of days to load data for
const scaleFactor = 1000; // The scale factor for the SWC values
const vmin = 0.0; // The minimum value of the colormap
const vmax = 0.4; // The maximum value of the colormap

function setup() {
  return {
    input: ["SWC", "dataMask"],
    output: { id: "default", bands: 4 },
    mosaicking: "ORBIT",
  };
}

function preProcessScenes(collections) {
  collections.scenes.orbits = collections.scenes.orbits.filter(function (
    orbit
  ) {
    var orbitDateFrom = new Date(orbit.dateFrom);
    // Select all images within the last nDays
    return (
      orbitDateFrom.getTime() >=
      collections.to.getTime() - nDays * 24 * 3600 * 1000
    );
  });
  return collections;
}

function get_mean_swc_value(samples) {
  // Get the sum of all SWC values
  let n_valid_dates = 0;
  let sum = 0;
  for (let i = 0; i < samples.length; i++) {
    if (samples[i].dataMask) {
      sum += samples[i].SWC / scaleFactor;
      n_valid_dates += 1;
    }
  }

  // Calculate the mean SWC value
  let mean_swc_value = NaN;
  if (n_valid_dates > 0) {
    mean_swc_value = sum / n_valid_dates;
  }

  return mean_swc_value;
}

const cmap = [
  [0.0, 0xfff7ea],
  [0.05, 0xfaedda],
  [0.1, 0xede4cb],
  [0.15, 0xdedcbd],
  [0.2, 0xced3af],
  [0.25, 0xbdcba3],
  [0.3, 0xaac398],
  [0.35, 0x96bc90],
  [0.4, 0x80b48a],
  [0.45, 0x68ac86],
  [0.5, 0x4da484],
  [0.55, 0x269c83],
  [0.6, 0x009383],
  [0.65, 0x008a85],
  [0.7, 0x008186],
  [0.75, 0x007788],
  [0.8, 0x006d8a],
  [0.85, 0x00618c],
  [0.9, 0x00558d],
  [0.95, 0x00478f],
  [1.0, 0x003492],
];

// Prepare colormap based on provided min and max values
const visualizer = new ColorRampVisualizer(cmap, vmin, vmax);

function evaluatePixel(samples) {
  // When there are no dates, return no data
  if (samples.length == 0) return [NaN, NaN, NaN, 0];

  // Calculate mean SWC value
  const mean_swc_val = get_mean_swc_value(samples);

  // Set opacity to 0 if there is no valid data
  let opacity = 1;
  if (isNaN(mean_swc_val)) {
    opacity = 0;
  }

  // Apply colormap
  imgVals = visualizer.process(mean_swc_val);

  return [...imgVals, opacity];
}
//VERSION=3

const nDays = 20; // The number of days to load data for
const scaleFactor = 1000; // The scale factor for the SWC values

function setup() {
  return {
    input: ["SWC", "dataMask"],
    output: { bands: 1, sampleType: "FLOAT32" },
    mosaicking: "ORBIT",
  };
}

function preProcessScenes(collections) {
  collections.scenes.orbits = collections.scenes.orbits.filter(function (
    orbit
  ) {
    var orbitDateFrom = new Date(orbit.dateFrom);
    // Select all images within the last nDays
    return (
      orbitDateFrom.getTime() >=
      collections.to.getTime() - nDays * 24 * 3600 * 1000
    );
  });
  return collections;
}

function get_mean_swc_value(samples) {
  // Get the sum of all SWC values
  let n_valid_dates = 0;
  let sum = 0;
  for (let i = 0; i < samples.length; i++) {
    if (samples[i].dataMask) {
      sum += samples[i].SWC / scaleFactor;
      n_valid_dates += 1;
    }
  }

  // Calculate the mean SWC value
  let mean_swc_value = NaN;
  if (n_valid_dates > 0) {
    mean_swc_value = sum / n_valid_dates;
  }

  return mean_swc_value;
}

function evaluatePixel(samples) {
  // When there are no dates, return no data
  if (samples.length == 0) return [NaN];

  // Calculate mean SWC value
  const mean_swc_val = get_mean_swc_value(samples);

  return [mean_swc_val];
}

Evaluate and Visualize

General description

The Soil Water Content Backward Average is a method to reduce data gaps and measurement noise in the Soil Water Content (SWC) data. Depending on the requirements, we can choose a lookback period, for example 20 days. The 20-day backward average of SWC for day n is the average of SWC over the 20 days preceding day n. We compute the backward average using all available measurements within this 20-day period, and therefore, we do have a valid value for every day, except in case of prolonged data unavailability, such as during long frost and snow periods.

Why it is useful

Our Soil Water Content provides a great reflection of the immediate soil conditions. However, daily measurements often exhibit short-term fluctuations due to for example rainfall events and evaporation. The Soil Water Content Backward Average is suitable for applications where long-term soil moisture conditions are more relevant than daily fluctuations. The moving average operation reduces day-to-day variations and in the resulting time series, seasonal and longer-term changes can be easily detected. It can be used for monitoring drought risk, yield forecasting and analysis of climate change.