Global shoreline mapping tool from satellite imagery
A ready-to-use curated list of Spectral Indices for Remote Sensing applications.
Algorithms for computing global land surface temperature and emissivity from NASA's Landsat satellite images with Python.
A sensor invariant Atmospheric Correction (SIAC)
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.
To process a Sentinel-2 time series with MAJA cloud detection and atmospheric correction processor
Sentinel 2 and Landsat 8 Atmospheric correction
Package designed to detect and quantify water quality and cyanobacterial harmful algal bloom (CHABs) from remotely sensed imagery
deck.gl layers and WebGL modules for client-side satellite imagery analysis
Using Vision Transformers for enhanced wildfire detection in satellite images
Reproducible remote sensing analysis using Google Earth Engine (GEE) to identify vegetation change in Columbia.
The Supervised Land Cover Classification (SLaCC) tool is a Google Earth Engine script created by the Summer 2019 Southern Maine Health and Air Quality Team. It uses NASA Earth observations, the National Land Cover Database, land cover classification training data, and a shapefile of Cumberland County, Maine, USA. The goal of the project was to e…
A module to process LandSat8 Remote Sense Images. Features: NDBI NDVI NDWI calculation; LandSat8 BandMerge(GIS info reserved); Building Area Extraction; Water Area Extraction;
Remote sensing data processing
Compare Spectrograms of Hyperspectral and Multispectral Satellite Missions
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.
2D/3D WebGL Landsat 8 satellite image analysis
It contains Google Earth Engine codes (JavaScript API) to process Sentinel-1 and Landsat 8 images to compute SAR and optical vegetation indices.
Flask extension for Brazil Data Cube to collect satellite imagery from multiple providers.
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