Custom protocol to load Cloud Optimized GeoTIFFs (COG) in Maplibre GL JS
https://labs.geomatico.es/maplibre-cog-protocol
For better quality, use always tileSize: 256
to match the size of tiles delivered by the custom protocol.
<!DOCTYPE html>
<html lang="en">
<head>
<link rel="stylesheet" href="https://unpkg.com/maplibre-gl/dist/maplibre-gl.css">
<script src="https://unpkg.com/maplibre-gl/dist/maplibre-gl.js"></script>
<script src="https://unpkg.com/@geomatico/maplibre-cog-protocol/dist/index.js"></script>
</head>
<body>
<div id="map" style="width: 600px; height: 400px"></div>
<script>
let map = new maplibregl.Map({
container: 'map',
style: 'https://geoserveis.icgc.cat/contextmaps/icgc_mapa_base_gris_simplificat.json',
center: [1.83369, 41.5937],
zoom: 14
});
maplibregl.addProtocol('cog', MaplibreCOGProtocol.cogProtocol);
map.on('load', () => {
map.addSource('imageSource', {
type: 'raster',
url: 'cog://https://labs.geomatico.es/maplibre-cog-protocol/data/image.tif',
tileSize: 256
});
map.addLayer({
id: 'imageLayer',
source: 'imageSource',
type: 'raster'
});
});
</script>
</body>
</html>
npm install @geomatico/maplibre-cog-protocol
import maplibregl from 'maplibre-gl';
import {cogProtocol} from '@geomatico/maplibre-cog-protocol';
import Map from 'react-map-gl/maplibre';
maplibregl.addProtocol('cog', cogProtocol);
const App = () =>
<Map
style={{width: 600, height: 400}}
mapStyle="https://geoserveis.icgc.cat/contextmaps/icgc_mapa_base_gris_simplificat.json"
initialViewState={{longitude: 1.83369, latitude: 41.5937, zoom: 14}}
>
<Source id="imageSource" type="raster" url="cog://https://labs.geomatico.es/maplibre-cog-protocol/data/image.tif" tileSize={256}>
<Layer id="imageLayer" type="raster"/>
</Source>
</Map>;
COGs with three or four 8-bit bands can be displayed as RGB or RGBA images.
- Use a
raster
source with the url prepended withcog://
- Use a
raster
layer.
map.addSource('sourceId', {
type: 'raster',
url: 'cog://https://labs.geomatico.es/maplibre-cog-protocol/data/image.tif',
});
map.addLayer({
id: 'imageId',
source: 'sourceId',
type: 'raster'
});
COGs with a single band can be interpreted DEMs.
- Use a
raster-dem
source with the url prepended withcog://
and appended with#dem
- Use a
hillshade
layer.
map.addSource('sourceId', {
type: 'raster-dem',
url: 'cog://https://cdn.geomatico.es/pirineo_dem_cog_256.tif#dem',
});
map.addLayer({
id: 'hillshadeId',
source: 'sourceId',
type: 'hillshade'
});
- Use a
raster-dem
source with the url prepended withcog://
and appended with#dem
, same as above. - Set it as the terrain.
map.addSource('sourceId', {
type: 'raster-dem',
url: 'cog://https://cdn.geomatico.es/pirineo_dem_cog_256.tif#dem',
});
map.setTerrain({
source: 'sourceId'
});
COGs with a single band can be also converted to images applying a color ramp.
- Use a
raster
source with the url prepended withcog://
and appended with#color:
and the color ramp specification. - Use a
raster
layer.
map.addSource('sourceId', {
type: 'raster',
url: 'cog://https://labs.geomatico.es/maplibre-cog-protocol/data/kriging.tif#color:BrewerSpectral9,1.7,1.8,c',
});
map.addLayer({
id: 'imageId',
source: 'sourceId',
type: 'raster'
});
In case you want to apply any other coloring logic, you can provide a function that converts pixel values to RGBA color values, and assign it to the COG URL where it needs to be applied.
Use the setColorFunction
method, which needs two arguments:
cogUrl
: the COG to which the custom color function will be applied. Don't prepend thecog://
protocol here.colorFunction
: A function that maps pixel values to color values, whose arguments are:pixel
: An array of numeric values, one for each band. If defined in COG metadata,offset
andscale
are already applied to each value.color
: An Uint8ClampedArray of exactly 4 elements. Set the pixel color by setting the first, second, third and fourth element tored
,green
,blue
andalpha
values respectively.metadata
: (CogMetadata)[src/types.ts#L27] structure with information about the COG, such as thenoData
value.
The following example paints values below a given threshold as red, and green otherwise:
const cogUrl = 'https://labs.geomatico.es/maplibre-cog-protocol/data/kriging.tif';
const threshold = 1.75;
// Function is called for every pixel, keep it fast!
MaplibreCOGProtocol.setColorFunction(cogUrl, (pixel, color, metadata) => {
if (pixel[0] === metadata.noData) {
color.set([0, 0, 0, 0]); // Transparent
} else if (pixel[0] < threshold) {
color.set([255, 0, 0, 255]); // Red
} else {
color.set([0, 255, 0, 255]); // Green
}
});
map.addSource('sourceId', {
type: 'raster',
url: `cog://${cogUrl}`, // Use the same URL as in setColorFunction, preppended with "cog://".
});
map.addLayer({
id: 'imageId',
source: 'sourceId',
type: 'raster'
});
Some other interesting usages:
- Apply other color scales not listed in the builtin standard ColorBrewer or CartoColors catalog.
- Use custom breakpoints or interpolations.
- Display other bands.
- Combine bands of a multispectral image to calculate indicators on the fly.
The locationValues(url, location, zoom?)
method reads raw pixel values for a given location. It returns an array of numbers, one for each band in the COG. NaNs are returned when querying outside of the image. If zoom is indicated, it will query the nearest overview corresponding to that zoom level.
Example usage in conjunction with maplibre API to get COG values on mouse hover:
import {locationValues} from '@geomatico/maplibre-cog-protocol';
map.on('mousemove', ({lngLat}) => {
locationValues(
'./data/kriging.tif',
{latitude: lngLat.lat, longitude: lnglat.lon},
map.getZoom()
).then(console.log);
});
locationValues
doesn't depend on Maplibre API or the CogProtocol, so it can be used to query raster values in applications without a map:
import {locationValues} from '@geomatico/maplibre-cog-protocol';
const url = 'https://labs.geomatico.es/maplibre-cog-protocol/data/kriging.tif';
locationValues(url, {latitude: 41.656278, longitude: 0.501394}).then(console.log);
COG should be in EPSG:3857 (Google Mercator) projection, as this library doesn't reproject and won't understand any other projection.
For better performance, use the Google Maps tiling scheme with 256x256 blocksize.
For RGB images, JPEG yCbCr (lossy) compression is recommended. For lossless compression, deflate gives good decoding performance on the browser.
Sample GDAL commands (using docker for convenience, but not needed):
docker run --rm -v .:/srv ghcr.io/osgeo/gdal:alpine-small-3.9.1 gdalwarp /srv/<source>.tif /srv/<target>.tif -of COG -co BLOCKSIZE=256 -co TILING_SCHEME=GoogleMapsCompatible -co COMPRESS=JPEG -co OVERVIEWS=IGNORE_EXISTING -co ADD_ALPHA=NO -co ALIGNED_LEVELS=10 -dstnodata NaN
docker run --rm -v .:/srv ghcr.io/osgeo/gdal:alpine-small-3.9.1 gdalwarp /srv/<source>.tif /srv/<target>.tiff -of COG -co BLOCKSIZE=256 -co TILING_SCHEME=GoogleMapsCompatible -co COMPRESS=DEFLATE -co RESAMPLING=BILINEAR -co OVERVIEW_RESAMPLING=NEAREST -co OVERVIEWS=IGNORE_EXISTING -co ADD_ALPHA=NO -co ALIGNED_LEVELS=10 -dstnodata NaN
npm version [patch | minor | major]
npm run build
npm publish --access public
git push origin tag vX.X.X
npm run gh-publish # publish examples to labs.geomatico.es
- Apply transparency mask if present (now taking 0 as the default noData value)
- Integrate maplibre-contour