An exploration of wildfires and acres burned in the United States since 1983.
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Updated
Apr 5, 2022 - Python
An exploration of wildfires and acres burned in the United States since 1983.
Agent-based modeling 2D wildfire suppression simulator tool built on the mesa framework in Python
A dashboard for visualization of Oregon Wildfire Data from 1961-2019
Wildfire prediction machine learning model
An on-the-ground live feed of updates to keep you prepared for the worst!
Simulator based on the real physical phenomenons acting in a wildfire, deals with wind, heat capacities..an more.
Environmental issues reports from Argentina
Implementation of several state-of-the-art Deep Learning models for fire semantic segmentation.
Download wildfire incidents data from InciWeb
Download wildfires data from NOAA satellites
Download watch, warning and advisory data from the National Weather Service
Download wildfires data from the National Interagency Fire Center
Live wild fire data visualization, historical data analysis, future fires prediction based on Machine Learning model
Teleconnection-driven vision transformers for improved long-term forecasting
Python for Raw Sentinel-2 data (PyRawS) is an open-source software providing utilities to open and process Sentinel 2 RAW data, which corresponds to a decompressed version of Level-0 data with additional metadata. The software is demonstrated on the first Sentinel-2 dataset containing raw data for warm temperature hotspots detection/classification.
Download wildfire hotspots detected by NASA satellites and the Fire Information for Resource Management System (FIRMS)
Download wildfires data from CalFire
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