new sentinel-5p NO2 monthly mean custom script

Author: azlinszkysinergise

sentinel-5p/no2_monthly_mean/README.md

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+---
+title: NO2 Monthly mean
+parent: Sentinel-5p
+grandparent: Sentinel
+layout: script
+permalink: /sentinel-5p/no2_monthly_mean/
+nav_exclude: true
+examples:
+- zoom: '8'
+  lat: '46.60228'
+  lng: '15.17212'
+  datasetId: S5_NO2
+  fromTime: '2024-12-28T00:00:00.000Z'
+  toTime: '2025-01-28T23:59:59.999Z'
+  platform:
+  - CDSE
+  - EOB
+  evalscripturl: https://custom-scripts.sentinel-hub.com/custom-scripts/sentinel/sentinel-5p/no2_monthly_mean/script.js
+---
+
+The layout `script` automatically adds the title defined in the front matter and adds buttons to visualize the script. For the buttons to work the evalscript has to be named `script.js` and must be in the same directory as the `README.md` file.
+
+## General description of the script
+
+This script calculates the mean values of NO<sub>2</sub> over the time period you select. It is useful for visualizing large-scale patterns of air pollution. 
+In order to comply with the SI unit definitions, the TROPOMI NO2 data product gives trace gas concentrations in mol/m<sup>2</sup>.
+
+Cloud-affected pixels are masked from Sentinel-5P air pollution imagery, you will see them as empty pixels on the map. Due to the relatively low resolution of Sentinel-5P TROPOMI, these datasets work best at regional to continental scale, however, at such scales it is extremely rare to encounter an image that is not influenced by clouds. Therefore, similar to [Sentinel-2 quarterly mosaics](https://dataspace.copernicus.eu/news/2024-2-27-exploring-new-frontier-sentinel-cloudless-mosaics-copernicus-data-space-ecosystem), creating longer-term mean mosaics of Sentinel-5P data enables exploring pollution patterns across regions.
+
+The script is written to work for NO2, but can be used for other Sentinel-5P data layers as well by manually changing the variable "NO2" in the setup function and in the sum(array) function.
+
+## References
+
+- Sentinel-5P TROPOMI NO2 data products Algorithm Theoretical Basis Document: https://sentiwiki.copernicus.eu/__attachments/1673595/S5P-KNMI-L2-0005-RP%20-%20Sentinel-5P%20TROPOMI%20ATBD%20NO2%20data%20products%202022%20-%202.4.0.pdf?inst-v=9aab56a9-2b0f-4066-9dbe-4985b055a039

sentinel-5p/no2_monthly_mean/script.js

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+//VERSION=3 
+// By Jonas Viehweger, Sinergise
+
+var minVal = 0.0;
+var maxVal = 0.0001;
+const map = [
+  [0, 0x00007f], 
+  [1, 0x0000ff],
+  [2, 0x00ffff],
+  [3, 0xffff00],
+  [4, 0xff0000],
+  [5, 0x7f0000]
+]; 
+const visualizer = new ColorRampVisualizer(map, minVal, maxVal)
+function setup() {
+   return {
+    input: ["NO2","dataMask"],
+  output: [
+      { id: "default", bands: 4 },
+      { id: "index", bands: 1, sampleType: "FLOAT32" },
+      { id: "eobrowserStats", bands: 1, sampleType: "FLOAT32"},
+      { id: "dataMask", bands: 1 },
+    ],
+    mosaicking: "ORBIT"
+  };
+}
+function isClear(sample) {
+    return sample.dataMask == 1;
+}
+function sum(array) {
+    let sum = 0;
+    for (let i = 0; i < array.length; i++) {
+        sum += array[i].NO2;
+    }
+    return sum;
+}
+function evaluatePixel(samples) {
+      const clearTs = samples.filter(isClear)
+    const mean = sum(clearTs) / clearTs.length
+   const [r, g, b] = visualizer.process(mean);
+   const dataMask = clearTs.length > 0;
+   return {
+        default: [r, g, b, dataMask],
+        index: [mean],
+        eobrowserStats: [mean],
+        dataMask: [dataMask],
+      };
+}