A ready-to-use curated list of Spectral Indices for Remote Sensing applications.

Global shoreline mapping tool from satellite imagery

Algorithms for computing global land surface temperature and emissivity from NASA's Landsat satellite images with Python.

deck.gl layers and WebGL modules for client-side satellite imagery analysis

Q. Zhang, Q. Yuan, J. Li, Z. Li, H. Shen, and L. Zhang, "Thick Cloud and Cloud Shadow Removal in Multitemporal Images using Progressively Spatio-Temporal Patch Group Learning", ISPRS Journal, 2020.

A sensor invariant Atmospheric Correction (SIAC)

To process a Sentinel-2 time series with MAJA cloud detection and atmospheric correction processor

A simple python script that, given a location and a date, uses the Nasa Earth API to show a photo taken by the Landsat 8 satellite. The script must be executed on the command-line.

Package designed to detect and quantify water quality and cyanobacterial harmful algal bloom (CHABs) from remotely sensed imagery

2D/3D WebGL Landsat 8 satellite image analysis

Sentinel 2 and Landsat 8 Atmospheric correction

It contains Google Earth Engine codes (JavaScript API) to process Sentinel-1 and Landsat 8 images to compute SAR and optical vegetation indices.

Using Vision Transformers for enhanced wildfire detection in satellite images

Remote sensing data processing

Reproducible remote sensing analysis using Google Earth Engine (GEE) to identify vegetation change in Columbia.

Auto-updating global Landsat 8 mosaic of Cloud-Optimized GeoTIFFs from SNS notifications

Compare Spectrograms of Hyperspectral and Multispectral Satellite Missions

High-Resolution Cloud Detection Network

The Optical Reef and Coastal Area Assessment (ORCAA) tool in Google Earth Engine allows users to monitor, track, and evaluate water parameters in the Belize and Honduras Barrier Reefs from January 2013 to present using Landsat 8, Sentinel-2, and Aqua/Terra MODIS imagery.

Pytorch code for estimating the presence of the West Nile Disease employing Graph Neural network