将 NDVI+NDWI 计算为绿色和蓝色值。
本示例中的 GeoTIFF 图层从两个云优化的 Sentinel 2 GeoTIFF 计算归一化植被指数 (NDVI) 和归一化水体指数 (NDWI):一个具有 10 米分辨率、红波段和近红外波段,另一个具有 60 米分辨率和短波红外通道。NDVI 显示为绿色,NDWI 显示为蓝色。第 4 个波段是 alpha 波段,当数据源配置了 nodata 值时会添加该波段。
import Map from 'ol/Map.js';
import TileLayer from 'ol/layer/WebGLTile.js';
import GeoTIFF from 'ol/source/GeoTIFF.js';
const source = new GeoTIFF({
sources: [
{
url: 'https://s2downloads.eox.at/demo/Sentinel-2/3857/R10m.tif',
bands: [3, 4],
min: 0,
nodata: 0,
max: 65535,
},
{
url: 'https://s2downloads.eox.at/demo/Sentinel-2/3857/R60m.tif',
bands: [9],
min: 0,
nodata: 0,
max: 65535,
},
],
});
source.setAttributions(
"<a href='https://s2maps.eu'>Sentinel-2 cloudless</a> by <a href='https://eox.at/'>EOX IT Services GmbH</a> (Contains modified Copernicus Sentinel data 2019)",
);
const ndvi = [
'/',
['-', ['band', 2], ['band', 1]],
['+', ['band', 2], ['band', 1]],
];
const ndwi = [
'/',
['-', ['band', 3], ['band', 1]],
['+', ['band', 3], ['band', 1]],
];
const map = new Map({
target: 'map',
layers: [
new TileLayer({
style: {
color: [
'color',
// red: | NDVI - NDWI |
['*', 255, ['abs', ['-', ndvi, ndwi]]],
// green: NDVI
['*', 255, ndvi],
// blue: NDWI
['*', 255, ndwi],
// alpha
['band', 4],
],
},
source,
}),
],
view: source.getView(),
});
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>NDVI+NDWI from two 16-bit COGs</title>
<link rel="stylesheet" href="node_modules/ol/ol.css">
<style>
.map {
width: 100%;
height: 400px;
}
</style>
</head>
<body>
<div id="map" class="map"></div>
<script type="module" src="main.js"></script>
</body>
</html>
{
"name": "cog-math-multisource",
"dependencies": {
"ol": "10.9.0"
},
"devDependencies": {
"vite": "^3.2.3"
},
"scripts": {
"start": "vite",
"build": "vite build"
}
}