This repository showcases our work on using computer vision to detect wildfires. Explore the code, model, and results of our research on wildfire prevention.

Evaluate Wildfire Environmental Impact and Assess Burn Severity Consequences using Cloud Based Geoprocessing via Earth Engine Streamlit App.

A collection of modules to programmatically search for/download imagery from live cam feeds across the state of California.

Machine Learning for Wildfire Detection - MLOps

This project develops an automated forest fire surveillance system using UAV drones, combining Artificial Intelligence (AI) with the YOLOv11 model optimized by TensorRT to run on NVIDIA Jetson Nano.

This repository showcases our work on using computer vision to detect wildfires. Explore the code, model, and results of our research on wildfire prevention.

Automated framework for retrieving and processing Sentinel-2 satellite imagery using the Sentinel Hub API. Focused on analyzing geospatial data, particularly SWIR composites, to visualize wildfire-affected areas and support environmental monitoring.

🔥 Detect forest fires and smoke in real-time using a drone equipped with YOLOv11 and Jetson Nano for effective monitoring and response.

Build and version wildfire datasets for training object detectors

Geospatial event intelligence platform — converts natural language event descriptions into satellite-derived flood, wildfire, and storm analysis products. Intent resolution, multi-sensor fusion, distributed processing (Pi to Spark), and automated report generation.

Large-scale fire detection analysis using NASA FIRMS data

Large-scale fire detection analysis using NASA FIRMS data feat: Add dynamic region support for North America case study in v1.4.3 - Enabled flexible geospatial parameterization for wildfire analysis - Updated preprocessing pipeline to support North America-specific satellite data formats.

Large-scale fire detection analysis using NASA FIRMS data feat: Add dynamic region support for Africa case study in v1.4.4 - Enabled flexible geospatial parameterization for wildfire analysis - Updated preprocessing pipeline to support Africa-specific satellite data formats.

AutoML pipeline for wildfire detection using continuous training and deployment.

Large-scale fire detection analysis using NASA FIRMS data feat: Add dynamic region support for EU case study in v1.4.2 - Enabled flexible geospatial parameterization for wildfire analysis - Updated preprocessing pipeline to support EU-specific satellite data formats.

AI-powered wildfire damage detection using IBM/NASA Prithivi-EO-2.0 foundation models and hybrid spectral analysis for high-precision burn mapping.

python based tool for reconciling fire activity data sources into a single stream based on the smartfire 2 system

Wildfire detection system using adhoc Raspberry Pi and sensors

Large-scale fire detection analysis using NASA FIRMS data. feat: Add dynamic region support for South America case study in v1-4_area - Enabled flexible geospatial parameterization for wildfire analysis - Updated preprocessing pipeline to accommodate South American satellite data formats.