Topic: wildfires Goto Github
Some thing interesting about wildfires
Some thing interesting about wildfires
wildfires,Notebooks and code for evaluating the effect of vegetation mortality on wildfire burn severity in the Woolsey Fire
User: adamancer
wildfires,http://ibm.biz/cfcsc-wildfires - predict the wildfire/bushfire area for 7 regions in Australia for each day in February 2021
Organization: call-for-code
wildfires,Systematic assessment of the impacts of climate change on human pathogenic diseases
User: camilo-mora
Home Page: https://camilo-mora.github.io/Diseases/
wildfires,🔥 Regression: Predict acres burned in a California wildfire
User: corralm
wildfires,Project Athena - Quadrupedal Objection Detection System
User: danielgonzalez3
wildfires,Download wildfires data from CalFire
Organization: datadesk
Home Page: https://palewi.re/docs/calfire-wildfires/
wildfires,Download wildfire incidents data from InciWeb
Organization: datadesk
Home Page: https://palewi.re/docs/inciweb-wildfires/
wildfires,Download wildfire hotspots detected by NASA satellites and the Fire Information for Resource Management System (FIRMS)
Organization: datadesk
Home Page: https://palewi.re/docs/nasa-wildfires/
wildfires,Download wildfires data from the National Interagency Fire Center
Organization: datadesk
Home Page: https://palewi.re/docs/nifc-wildfires/
wildfires,Download wildfires data from NOAA satellites
Organization: datadesk
Home Page: https://palewi.re/docs/noaa-wildfires/
wildfires,Download watch, warning and advisory data from the National Weather Service
Organization: datadesk
Home Page: https://palewi.re/docs/nws-wwa/
wildfires,Fire climate dataset creation from NOAA API based on location and time for use in machine learning model. Is the project that motivated the creation of the library simple_noaa.
User: devinrshaw
wildfires,Building models that can predict whether an area is at risk of a wildfire or not on satellite images.
User: doguilmak
wildfires,A clean and lightweight website to provide essential information, resources, and links about the SCU Lightning Complex Fires.
User: dotimothy
Home Page: https://dotimothy.github.io/scucomplexfires/
wildfires,Data Science implementations and models
User: enginbozkurt
wildfires,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.
Organization: esa-philab
Home Page: https://esa-philab.github.io/PyRawS/
wildfires,Soil Heating in Fire (SheFire) Model: Annotated .Rmd scripts and an R package to build and use a SheFire model for how different soil depths heat and cool during fires
Organization: fire-and-dryland-ecosystems-lab
wildfires,Forecast app from many provinces in Argentina
User: gabrielcarames
Home Page: https://argview-data-visualization.vercel.app/
wildfires,Agent-based modeling 2D wildfire suppression simulator tool built on the mesa framework in Python
User: hildobby
wildfires,Live wild fire data visualization, historical data analysis, future fires prediction based on Machine Learning model
User: ireneshtepa
wildfires,Documentation: Methodology and Exploratory Data Analysis
User: isaacarroyov
wildfires,Convolutional neural network model based on the architecture of the Faster-RCNN for wildfire smoke detection.
User: jasonmanesis
wildfires,How to map large geojson data sources on the web using vector tiles and MapLibre GL JS, an open-source version of Mapbox GL JS
User: jebowe3
wildfires,Implementation of several state-of-the-art Deep Learning models for fire semantic segmentation.
User: jorgefcs
wildfires,Welcome to my Wildfire capstone project. This project develops a classification model to predict wildfires management complexity levels. This is a wildfire risk, size, and impact based project.
User: keanang
Home Page: https://keanang.github.io/ClassiFire/
wildfires,Exploring California Wildfire Data
User: kiran-a-singh
wildfires,Project FITA: Fires in the Amazon. WebApp para análise e classificação de imagens de satélite da Amazônia.
User: laulloliv
wildfires,A global scale study of the factors affecting wildfires' distribution over the past 10 years. We used Google Earth Engine for retrieving data and Python for analysis.
User: madeleinemadeleinemadeleine
wildfires,Collaborated with a team to perform a deep dive of existing California wildfire data using machine learning. Dataset contains qualitative and quantitative data from California wildfires between 2013 and 2020.
User: mallorykuba24
Home Page: https://github.com/mallorykuba24/Wildfires.git
wildfires,Environmental issues reports from Argentina
User: manucabral
wildfires,A superset of various wildfire smoke datasets.
User: mattdorling
wildfires, A large dataset (500+ images) of past wildfire from Copernicus EMS using Sentinel-2 images in the period 2017- 2023
User: matteom95
Home Page: https://emergency.copernicus.eu/mapping/list-of-activations-rapid
wildfires,Created for but not limited to boreal forest wildfires. This repository contains code to calculate the radiative forcing from dry organic matter combustion or other releases of gaseous emissions.
User: michaelmoubarak
wildfires,Map of the Thomas Fire, using data from NASA's MODIS and VIIRS satellites
User: mkmcc
wildfires,A deep learning approach for mapping and dating burned areas using temporal sequences of satellite images
User: mnpinto
Home Page: https://mnpinto.github.io/banet/
wildfires,Simulator based on the real physical phenomenons acting in a wildfire, deals with wind, heat capacities..an more.
User: multielio
wildfires,SAVeTrEE is a script within Google Earth Engine for classifying areas of vegetation mortality. It prompts the user for a year, duration, and spectral index for which a mortality map should be produced, then fits a trend line to an imagery time sequence of vegetative spectral index values calculated from Landsat multispectral data. The slope of the trend line, as well as the spectral index values, are used in determining the final classification of each pixel within the study area. Classification categories are: 1) Growing 2) Mortality (declining) 3) Stable Vegetation and 4) Stable Barren.
Organization: nasa-develop
wildfires,Teleconnection-driven vision transformers for improved long-term forecasting
Organization: orion-ai-lab
Home Page: https://orion-ai-lab.github.io/televit/
wildfires,Deep Learning Models for Wildfire Danger Forecasting
Organization: orion-ai-lab
wildfires,Predicting wildfire risk using classification and regression tools. My final project as part of the Metis data science bootcamp.
User: pjn51
wildfires,Detection & monitoring platform of wildfires
Organization: pyronear
Home Page: https://platform.pyronear.org/
wildfires,Modelo desarrollado en el ensamblador de modelos de QGIS; este modelo permite estimar el área quemada y la severidad de la quema.
Organization: qgispe
Home Page: https://qgispe.github.io/Modelo-QGIS_Incendios_Forestales/
wildfires,This work explores the wildfire data collected over a period of time for the United States.
User: r-mishra
wildfires,A 1D numerical model for Soil Heating and Soil Organic Matter Combustion after wildfire events. Based on Aedo and Bonilla (2021)
User: saedoquililongo
Home Page: https://doi.org/10.1016/j.ecolmodel.2021.109506
wildfires,🌲 App to track forest fire location and news
Organization: simple-cod3
wildfires,
User: treboryx
Home Page: https://greecefires.eu
wildfires,Alaska Project Ideas, mentored by the researchers and collaborators of University of Alaska and supported by open-source entities and enthusiasts in Alaska.
Organization: uaanchorage
Home Page: https://www.uaa.alaska.edu/research
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