Project Inferno is a data processing and visualization pipeline that uses NASA’s publicly available satellite remote sensing datasets to analyze wildfire severity 🔥

Data science applied in the war

Fire Information for Resource Management System - Tool

Türkiye'deki yangın verilerini NASA FIRMS API'si üzerinden düzenli olarak çekmekte ve kaydetmektedir.

end-to-end pipeline to predict next-day wildfire risk from NASA FIRMS (active fires) and Meteostat weather, train LightGBM, and visualize alerts in Streamlit.

This is a world wide fire events data visualization project based on Streamlit by Python, data provided by NASA FIRMS.

Burn Watch is an experimental web app for real-time fire hotspot mapping using NASA’s FIRMS API. Built with React, Leaflet, and Turf.js, it filters and displays MODIS and VIIRS detections within a GeoJSON-defined area. Deployed on Netlify.

A tool that facilitates access to information about hotspots in the Amazon. It generates reports and maps of hotspots in real time and for the past 7 days. The plugin does this by accessing data from NASA and INPE.

Automated retrieval of farm fire locations to facilitate stakeholders with corrective on-ground actions.

Quick data visualisation of thermal data for airborne campaign planning

Bristol Scientific Computing (BriSC) demonstration of using Python tools in a scientific context. This demo shows how we can use code to examine and plot global fire data.

Wildfire detection and risk assessment integrating NASA FIRMS satellite thermal anomalies (VIIRS/MODIS), NOAA fire weather indices, EPA AirNow air quality data, and PurpleAir real-time PM2.5 sensors