Detection of burned areas using deep learning from satellite images

A semi-automatic GEE tool to monitor burned area progression using Sentinel-1 SAR data. Attachment for the article in the IEEE JSTARS by Paluba D. et al. (2024): Tracking burned area progression in an unsupervised manner using Sentinel-1 SAR data in Google Earth Engine https://doi.org/10.1109/JSTARS.2024.3427382

ModL2T: hybrid MODIS and Landsat algorithm in Google Earth Engine for estimating post-monsoon burned area from agricultural fires in northwestern India

This code repository is an attachment for the IGARSS 2023 proceeding paper: Paluba D. et al. (2023): "Unsupervised Burned Area Mapping in Greece: Investigating the impact of precipitation, pre- and post-processing of Sentinel-1 data in Google Earth Engine".

Visualization of burned area satellite data for Australian bush fires

A simple graphic editor that you can draw and calculate the percentage of filled area. It can be used for calculating the percentage of a burned human body area.

Forest Fires Prediction using Neural Networks

Predicted Burned area of forest fires and Turbine yield energy using ANN

TFM de inteligencia artificial para predecir la severidad en incendios forestales utilizando datos históricos y modelos predictivos avanzados.