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

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.

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.

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

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.

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.

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