Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/aazuspan/geesharp

Pan-sharpening in the Earth Engine code editor
https://github.com/aazuspan/geesharp

earth-engine ergas gram-schmidt image-processing image-quality landsat pan-sharpening panchromatic pansharpening pca remote-sensing

Last synced: 2 months ago
JSON representation

Pan-sharpening in the Earth Engine code editor

Awesome Lists containing this project

README 

        
# geeSharp



[![Earth Engine Javascript](https://img.shields.io/badge/Earth%20Engine%20API-Javascript-red)](https://developers.google.com/earth-engine/tutorials/tutorial_api_01)

[![Open in Code Editor](https://img.shields.io/badge/Open%20in-Code%20Editor-9cf)](https://code.earthengine.google.com/f08d3e4265bf0e502dacca76668d1914)



Pan-sharpen multispectral imagery in the [Google Earth Engine](https://earthengine.google.com/) Code Editor with one line of code:



```javascript

var sharp = geeSharp.sharpen(img.select(["B4", "B3", "B2"]), img.select("B8");

```






## Usage

### Pan-sharpening



To pan-sharpen an image, separate the lower resolution multispectral bands and the higher resolution panchromatic band into two images and pass them to the `geeSharp.sharpen` function. For example:



```javascript

// Import the geeSharp module

var geeSharp = require("users/aazuspan/geeSharp:geeSharp");



// Load an example Landsat 8 TOA image to sharpen

var img = ee.Image("LANDSAT/LC08/C01/T1_TOA/LC08_047027_20160819");



// Select the 30 m spectral bands to sharpen

var ms = img.select(["B4", "B3", "B2"]);

// Select the 15 m panchromatic band

var pan = img.select(["B8"]);



// Pan-sharpen!

var sharpened = geeSharp.sharpen(ms, pan);

```



By default, pansharpening in `geeSharp` uses the Smoothing Filter-based Intensity Modulation (SFIM) algorithm because it is fast and produces consistent, high-quality results. However, you may want to experiment with other methods. You can do that by passing an algorithm name to the `sharpen` function.



```javascript

var method = "brovey";

var sharpened = geeSharp.sharpen(ms, pan, method);

```



Most sharpening functions just require the unsharpened multispectral bands and the high-resolution panchromatic band as inputs, but some algorithms (like Gram-Schmidt) may accept other parameters. You can add those parameters after the method name when calling `sharpen`.



```javascript

// The Gram-Schmidt algorithm may require additional parameters depending on the size of your image.

var method = "GS";

var geom = ee.Geometry.Point([-122.41676185101713, 47.26851080476613]).buffer(1000);

var scale = 30;

var maxPixels = 1e13;



var sharpened = geeSharp.sharpen(ms, pan, method, geom, scale, maxPixels);

```



Print `geeSharp.methods` for a full list of supported algorithms, and see the [documentation](https://github.com/aazuspan/geeSharp.js/wiki/Sharpening-Functions) for descriptions.



### Image quality assessment



Image quality metrics measure the distortion between a reference image and an image that has been modified, such as a pan-sharpened image. 



```javascript

// Choose a metric

var metric = "RMSE";

// Reproject the unsharpened image to the sharpened resolution

var reproj = unsharpened.resample("bicubic").reproject(sharpened.projection());

// Calculate the metric

var quality = geeSharp.quality(reproj, sharpened, metric);

```



> **Warning**  

> Metrics are affected by spatial resolution, so when comparing unsharpened and pan-sharpened images, **always resample and reproject** the unsharpened image to high resolution first to ensure an accurate comparison!



Most quality metrics just require an unmodified and a modified image and return a dictionary mapping band names to metric values, but some metrics require other parameters (e.g. `ERGAS` requires the high and low spectral resolution) and some return a single image-wise value (e.g. `RASE` and `ERGAS`). Print `geeSharp.metrics` for a full list of supported metrics and see the [documentation](https://github.com/aazuspan/geeSharp.js/wiki/Image-Quality-Metrics) for descriptions.