Wrapper around Georeferenced Rasters like GeoTIFF, NetCDF, JPG, and PNG that provides a standard interface
npm install @mluds/georasterjavascript
const parseGeoraster = require("georaster");
fetch(url)
.then(response => response.arrayBuffer() )
.then(parseGeoraster)
.then(georaster => {
console.log("georaster:", georaster);
});
`load from file on back-end
javascript
const parseGeoraster = require("georaster");
fs.readFile("data/GeogToWGS84GeoKey5.tif", (error, data) => {
parseGeoraster(data).then(georaster => {
console.log("georaster:", georaster);
})
});
`load from simple object on front-end
javascript
const parseGeoraster = require("georaster");
const values = [ [ [0, 1, 2], [0, 0, 0], [2, 1, 1] ] ];
const noDataValue = 3;
const projection = 4326;
const xmin = -40;
const ymax = 14;
const pixelWidth = 0.00001;
const pixelHeight = 0.00001;
const metadata = { noDataValue, projection, xmin, ymax, pixelWidth, pixelHeight };
const georaster = parseGeoraster(values, metadata);
`load cloud optimized geotiff
This option allows you to basically load the pixels only when you need them versus the other options
that require you to load the whole image into memory. It will also attempt to automatically discover any available overview files.where to clip
is how many pixels from the top of the image to skip over before we start clippingbottom is how many pixels from the bottom of the image to skip over before we start clippingleft is how many pixels in from the left side of the image to skip over before we start clippingright is how many pixels in from the right side of the image to skip over before we start clipping
clipping resolution
width is how many pixels wide should be the returned image. This helps to configure the resolution.height is how many pixels tall should be the returned image. This helps to configure the resolution.resampling
resampleMethod is how to resample the pixels for the returned image. This value is passed on to geotiff.js' readRasters function and defaults to 'bilinear'. The alternative is 'nearest', which is faster and better for categorical data like landcover and continous classes with smooth variation like temperature.`javascript
const raster_url = "https://landsat-pds.s3.amazonaws.com/c1/L8/024/030/LC08_L1TP_024030_20180723_20180731_01_T1/LC08_L1TP_024030_20180723_20180731_01_T1_B1.TIF";
parseGeoraster(raster_url).then(georaster => {
console.log(georaster.height);
const options = { left: 0, top: 0, right: 4000, bottom: 4000, width: 10, height: 10 };
georaster.getValues(options).then(values => {
console.log("clipped values are", values);
});
});
`required properties
| name | description |
| ---- | ----------- |
| maxs | array with max value for each band |
| mins | array with min value for each band |
| ranges | array with difference between max and min value for each band |
| noDataValue | no data value |
| pixelWidth | width of pixel in dimension of coordinate reference system |
| pixelHeight | height of pixel in dimension of coordinate reference system |
| projection | equal to EPSG code, like 4326 |
| values | two dimensional array of pixel values (for Cloud Optimized GeoTIFF's, use instead) |
| width | number of pixels wide raster is |
| xmax | xmax in crs, which is often in longitude |
| xmin | xmin in crs, which is often in longitude |
| ymin | ymin in crs, which is often in latitude |
| ymax | ymax in crs, which is often in latitude |optional properties
| name | description |
| ---- | ----------- |
| palette | Array that maps raster values to RGBA colors |functions
| name | description |
| ---- | ----------- |
| getValues | described above |
| toCanvas | experimental! returns a canvas picture of the data. You can pass in options object with height or width specified |loading georaster package through a script tag
`html
``