code and data for revised manuscript "Building a machine learning surrogate model for wildfire activities within a global earth system model", at GM
Wildfires are a major natural hazard that lead to deforestation, carbon emissions, and loss of human...
This paper presents a benchmark dataset called EO4WildFires; a multi-sensor (multi spectral; Sentine...
Wildfires are becoming more frequent in different parts of the globe, and the ability to predict whe...
Wildfire is an important ecosystem process, influencing land biogeophysical and biogeochemical dynam...
Replication Data for: Identifying key drivers of wildfires in the continental US using machine learn...
Using Machine Learning and Aggregated Remote Sensing Data for Wildfire Occurrence Prediction and Fea...
Wildfires present a great danger to human lives and their environments. Early detection and rapid sp...
Datasets and scripts to run the SMLFire1.0 fire model. Note that all the files generated by running ...
This dissertation presents the potential of small unmanned aircrafts systems (sUAS) to provide affor...
Across the globe, the frequency and size of wildfire events are increasing. Research focused on mini...
In recent years, the likelihood of wildfire occurrence has increased in many North American communit...
Abstract Understanding the complex interrelationships between wildfire and its environmental and ant...
Artificial intelligence has been applied in wildfire science and management since the 1990s, with ea...
Data collected by Earth observation satellites are important information sources about the environme...
Wildfires can rip through any part of the world and cause a havoc. Building technologies to analyze ...
Wildfires are a major natural hazard that lead to deforestation, carbon emissions, and loss of human...
This paper presents a benchmark dataset called EO4WildFires; a multi-sensor (multi spectral; Sentine...
Wildfires are becoming more frequent in different parts of the globe, and the ability to predict whe...
Wildfire is an important ecosystem process, influencing land biogeophysical and biogeochemical dynam...
Replication Data for: Identifying key drivers of wildfires in the continental US using machine learn...
Using Machine Learning and Aggregated Remote Sensing Data for Wildfire Occurrence Prediction and Fea...
Wildfires present a great danger to human lives and their environments. Early detection and rapid sp...
Datasets and scripts to run the SMLFire1.0 fire model. Note that all the files generated by running ...
This dissertation presents the potential of small unmanned aircrafts systems (sUAS) to provide affor...
Across the globe, the frequency and size of wildfire events are increasing. Research focused on mini...
In recent years, the likelihood of wildfire occurrence has increased in many North American communit...
Abstract Understanding the complex interrelationships between wildfire and its environmental and ant...
Artificial intelligence has been applied in wildfire science and management since the 1990s, with ea...
Data collected by Earth observation satellites are important information sources about the environme...
Wildfires can rip through any part of the world and cause a havoc. Building technologies to analyze ...
Wildfires are a major natural hazard that lead to deforestation, carbon emissions, and loss of human...
This paper presents a benchmark dataset called EO4WildFires; a multi-sensor (multi spectral; Sentine...
Wildfires are becoming more frequent in different parts of the globe, and the ability to predict whe...
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