Satellite Vu submission for the AWS Disaster Response hackathon

Phoenix Eye—A NASA Space App Hackathon project that forecasts wildfires, alerts remote communities, and provides a comprehensive UI for researchers.

Leveraged Deep Learning (Transformers) to Predict Wildfire

This is a project where we try to understand fire patterns in tandem with the weather data to see if we can arrive at insights into patterns.

Algerian fire prediction with Linear Regression

Fire Prediction using LFMC maps

ML pipeline for predicting wildfire spread at 500m resolution using VIIRS, ERA5, and Canadian FBP fire weather indices. Case study: 2016 Fort McMurray fire.

Fire forest potential prediction in West Kalimantan Province, Indonesia.

Collecting the geometry of settlements, calculating the distances between fires and settlements, displaying geometries on the map.

Determine the probability that a heat source occurs under certain conditions.

UWP application for fire prediction using logistic regression.

Repositório front-end do Hub Niterói Contra Queimadas. Feito em parceria com a SMDCG.

This project aims to predict the occurrence of forest fires using machine learning. The project includes a Flask-based application that serves both backend (for model training and prediction) and frontend Created using Threejs (for user interaction).

calculate 3D polylines that run up the slope following the direction of maximum gradient and their intesections with forest polygons

AI-powered geospatial decision support system for wildfire analysis, spread forecasting, and evacuation planning using historical data replay and scenario simulation.

India's first weekly forest fire prediction system. 1km resolution, 8 satellite data sources, 756 experiments. Built for Karnataka, extensible to all states.