Greetings to all! I hope everyone is doing well.
I am currently utilizing the Processing API within my VSCode environment to retrieve images. I’ve also incorporated a function into the script to determine the minimum and maximum values. Please note that I’m not using the Sentinel Hub editor; the code has been integrated directly into my VSCode setup.
const CLIENT_ID = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxx";
const CLIENT_SECRET = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx";
const fromDate = "2020-07-01T00:00:00.000Z";
const toDate = "2020-09-01T00:00:00.000Z";
const dataset = "S2L1C";
// NDVI image
let minVal = 1;
let maxVal = -1;
// Function to update min and max values
function updateMinMaxValues(val) {
if (val < minVal) minVal = val;
if (val > maxVal) maxVal = val;
}
const evalscript = `
//VERSION=3
//This script was converted from v1 to v3 using the converter API
//NDVI EVALSCRIPT
if (dataMask == 0) return [0,0,0,0];
//ndvi
var val = (B08-B04)/(B08+B04);
// ========= Here i call Function to update min and max values
updateMinMaxValues(val);
if (val<-1.1) return [0,0,0,1];
else if (val<-0.2) return [0.75,0.75,0.75,1];
else if (val<-0.1) return [0.86,0.86,0.86,1];
else if (val<0) return [1,1,0.88,1];
else if (val<0.025) return [1,0.98,0.8,1];
else if (val<0.05) return [0.93,0.91,0.71,1];
else if (val<0.075) return [0.87,0.85,0.61,1];
else if (val<0.1) return [0.8,0.78,0.51,1];
else if (val<0.125) return [0.74,0.72,0.42,1];
else if (val<0.15) return [0.69,0.76,0.38,1];
else if (val<0.175) return [0.64,0.8,0.35,1];
else if (val<0.2) return [0.57,0.75,0.32,1];
else if (val<0.25) return [0.5,0.7,0.28,1];
else if (val<0.3) return [0.44,0.64,0.25,1];
else if (val<0.35) return [0.38,0.59,0.21,1];
else if (val<0.4) return [0.31,0.54,0.18,1];
else if (val<0.45) return [0.25,0.49,0.14,1];
else if (val<0.5) return [0.19,0.43,0.11,1];
else if (val<0.55) return [0.13,0.38,0.07,1];
else if (val<0.6) return [0.06,0.33,0.04,1];
else return [0,0.27,0,1];
`;
// Promise which will fetch Sentinel Hub authentication token:
const authTokenPromise = fetch(
"https://services.sentinel-hub.com/oauth/token",
{
method: "post",
headers: { "Content-Type": "application/x-www-form-urlencoded" },
body: `grant_type=client_credentials&client_id=${encodeURIComponent(
CLIENT_ID
)}&client_secret=${encodeURIComponent(CLIENT_SECRET)}`,
}
)
.then((response) => response.json())
.then((auth) => auth["access_token"]);
// We need to extend Leaflet's GridLayer to add support for loading images through
// Sentinel Hub Process API:
L.GridLayer.SHProcessLayer = L.GridLayer.extend({
createTile: function (coords, done) {
const tile = L.DomUtil.create("img", "leaflet-tile");
const tileSize = this.options.tileSize;
tile.width = tileSize;
tile.height = tileSize;
const nwPoint = coords.multiplyBy(tileSize);
const sePoint = nwPoint.add([tileSize, tileSize]);
const nw = L.CRS.EPSG4326.project(this._map.unproject(nwPoint, coords.z));
const se = L.CRS.EPSG4326.project(this._map.unproject(sePoint, coords.z));
authTokenPromise.then((authToken) => {
// Construct Process API request payload:
// https://docs.sentinel-hub.com/api/latest/reference/#tag/process
const payload = {
input: {
bounds: {
bbox: [nw.x, nw.y, se.x, se.y], // a tile's bounding box
geometry: {
// remove to disable clipping
type: "Polygon",
coordinates: [
[
[37.033538818359375, 39.246745041633794],
[37.03388214111328, 39.23777105285819],
[37.04864501953125, 39.23836935449403],
[37.04804420471191, 39.24754267396328],
[37.033538818359375, 39.246745041633794],
],
],
},
properties: {
crs: "http://www.opengis.net/def/crs/EPSG/0/4326",
},
},
data: [
{
dataFilter: {
timeRange: {
from: fromDate,
to: toDate,
},
maxCloudCoverage: 10,
mosaickingOrder: "mostRecent",
},
processing: {},
type: dataset,
},
],
},
output: {
width: 512,
height: 512,
responses: [
{
identifier: "default",
format: {
type: "image/png",
},
},
],
},
evalscript: this.options.evalscript, // CHANGED: using the evalscript that was passed
};
// Fetch the image:
fetch("https://services.sentinel-hub.com/api/v1/process", {
method: "post",
headers: {
Authorization: "Bearer " + authToken,
"Content-Type": "application/json",
Accept: "*/*",
},
body: JSON.stringify(payload),
})
.then((response) => response.blob())
.then((blob) => {
const objectURL = URL.createObjectURL(blob);
tile.onload = () => {
URL.revokeObjectURL(objectURL);
done(null, tile);
};
tile.src = objectURL;
})
.catch((err) => done(err, null));
});
return tile;
},
});
L.gridLayer.shProcessLayer = function (opts) {
return new L.GridLayer.SHProcessLayer(opts);
};
// CHANGED: passed the object with the correct evalscript to the L.gridLayer.shProcessLayer
const sentinelHubNDVI = L.gridLayer.shProcessLayer({ evalscript: evalscript });
const sentinelHubTrueColor = L.gridLayer.shProcessLayer({
evalscript: evalscript,
});
// OpenStreetMap layer:
let osm = L.tileLayer("http://{s}.tile.osm.org/{z}/{x}/{y}.png", {
attribution:
'© <a href="http://osm.org/copyright">OpenStreetMap</a> contributors',
});
// configure Leaflet:
let baseMaps = {
OpenStreetMap: osm,
};
let overlayMaps = {
NDVI: sentinelHubNDVI,
True: sentinelHubTrueColor,
};
let map = L.map("map", {
center: [39.243276, 37.042575], // lat/lng in EPSG:4326
zoom: 15,
layers: [osm, sentinelHubNDVI],
});
L.control.layers(baseMaps, overlayMaps).addTo(map);