A deep learning approach for mapping and dating burned areas using temporal sequences of satellite images

Access data from the MODIS web service and perform quality filtering in Python

Georeferenced Rasters and Statistics of Nightlights from NASA Black Marble

Webinar: NASA ORNL DAAC MODIS and VIIRS Data Tools and Services at your Fingertips

Python scripts and Jupyter Notebooks to download and preprocess VIIRS DNB Nighttime Lights data.

Georeferenced Rasters and Statistics of Nighttime Lights from NASA Black Marble

Package to analyse VIIRS nighttime lights

This repository contains code examples which demonstrate how users can access the CMRSET actual evapotranspiration data product and related data services.

Resources on the ORNL DAAC's Terrestrial Ecology Subsetting & Visualization Services (TESViS) tools

This project contains the python scripting which wraps the various ADL VIIRS EDR executables, for use in the CSPP VIIRS EDR package.

Submit a batch of MODIS Global Subset Tool orders via the MODIS Web Service

A collection of C code for reading NOAA VIIRS SDR (level-1b in NASA parlance) files in HDF5 format.

Fast and Accurate collocation of Fast and Accurate Collocation of the Visible Infrared Imaging Radiometer Suite (VIIRS) Measurements with Cross-Track Infrared Sounder (CrIS)

Dash Plotly Application to view current drought and fire conditions. Uses US Drought Monitor current county csv report and FIRMS current fire report from MODIS and VIIRS data.

This is the code used in my masters thesis research.

Use locally calibrated satellite products to improve the satellite estimation of the partial pressure of carbon dioxide in coastal waters