Merge pull request #349 from azlinszkysinergise/main

updated radar vegetation index code to v3, added code for monthly mosaics

Author: blazpavlica

sentinel-1/radar_vegetation_index_code_dual_polarimetric/README.md

@@ -5,6 +5,9 @@ grand_parent: Sentinel
 layout: script
 permalink: /sentinel-1/radar_vegetation_index_code_dual_polarimetric/
 nav_exclude: true
+scripts:
+  - [Copernicus Browser, script.js]
+  - [Sentinel-1 Monthly Mosaics, sentinel_1_mosaics.js]
 examples:
 - zoom: '11'
   lat: '15.9973'

sentinel-1/radar_vegetation_index_code_dual_polarimetric/script.js

@@ -6,5 +6,22 @@ IIT Bombay
 This code is based on:
 Nasirzadehdizaji, Rouhollah, et al. "Sensitivity Analysis of Multi-Temporal Sentinel-1 SAR Parameters to Crop Height and Canopy Coverage." Applied Sciences 9.4 (2019): 655.
 */
+/// updated to version 3 by András Zlinszky and GitHub Copilot
 
-return [(4*VH)/(VV+VH)];
+function setup() {
+    return {
+        input: ["VV", "VH"],
+        output: { bands: 3 }
+    };
+}
+
+function evaluatePixel(sample) {
+    let VV = sample.VV;
+    let VH = sample.VH;
+
+    // Calculate RVI
+    let rvi = (4 * VH) / (VV + VH);
+
+    // Return RVI as grayscale
+    return [rvi, rvi, rvi];
+}

sentinel-1/radar_vegetation_index_code_dual_polarimetric/sentinel_1_mosaics.js

@@ -0,0 +1,79 @@
+/*
+Radar Vegetation index for Sentinel-1
+Subhadip Dey
+IIT Bombay
+
+This code is based on:
+Nasirzadehdizaji, Rouhollah, et al. "Sensitivity Analysis of Multi-Temporal Sentinel-1 SAR Parameters to Crop Height and Canopy Coverage." Applied Sciences 9.4 (2019): 655.
+*/
+/// adapted by András Zlinszky for Sentinel-1 quarterly mosaics
+
+function setup() {
+    return {
+        input: ["VV", "VH", "dataMask"],
+        output: [
+            { id: "default", bands: 4 },
+            { id: "index", bands: 1, sampleType: "FLOAT32" },
+            { id: "eobrowserStats", bands: 1, sampleType: "FLOAT32" },
+            { id: "dataMask", bands: 1 }
+        ]
+    };
+}
+
+var water_threshold = 10; // Lower means more water
+const rvi_min = -0.1; // Lower limit of the color ramp
+const rvi_max = 1;   // Upper limit of the color ramp
+const num_steps = 9;  // Number of steps in the ramp
+
+// Define the colors for the ramp from light sand brown to deep fir green
+const colors = [
+    [0.93, 0.91, 0.71], // Light sand brown
+    [0.87, 0.85, 0.61], // Sandy beige
+    [0.8, 0.78, 0.51],  // Light tan
+    [0.74, 0.72, 0.42], // Golden brown
+    [0.69, 0.76, 0.38], // Olive green
+    [0.64, 0.8, 0.35],  // Light moss green
+    [0.57, 0.75, 0.32], // Moss green
+    [0.5, 0.7, 0.28],   // Forest green
+    [0.38, 0.59, 0.21]  // Deep fir green
+];
+
+// Generate the ramp dynamically
+const rvi_ramp = [];
+const step_size = (rvi_max - rvi_min) / (num_steps - 1);
+
+for (let i = 0; i < num_steps; i++) {
+    const value = rvi_min + i * step_size;
+    rvi_ramp.push([value, colors[i]]);
+}
+
+visualizer = new ColorRampVisualizer(rvi_ramp, rvi_min, rvi_max);
+
+function evaluatePixel(samples) {
+    let VV = samples.VV;
+    let VH = samples.VH;
+    let dataMask = samples.dataMask;
+
+    // Calculate RVI
+    let rvi = (4 * VH) / (VV + VH);
+    rvi = Math.max(rvi_min, Math.min(rvi_max, rvi)); // Clamp to the range
+
+    // Apply water threshold
+    if (VV / VH >= water_threshold) {
+        return {
+            default: [0.7, 0.8, 0.9, 1.0], // Water color (light greyish blue)
+            index: [rvi],
+            eobrowserStats: [rvi],
+            dataMask: [dataMask]
+        };
+    } else {
+        // Get the color from the ramp
+        let color = visualizer.process(rvi);
+        return {
+            default: color.concat([dataMask]),
+            index: [rvi],
+            eobrowserStats: [rvi],
+            dataMask: [dataMask]
+        };
+    }
+}