Identifying Key Drivers of Wildfires in the Contiguous US Using Machine Learning and Game Theory Interpretation-Reference-Cited by-同舟云学术

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Identifying Key Drivers of Wildfires in the Contiguous US Using Machine Learning and Game Theory Interpretation

Published:2021-06 Issue:6 Volume:9 Page:
ISSN:2328-4277
Container-title:Earth's Future
language:en
Short-container-title:Earth's Future

Author:

Wang Sally S.‐C.¹^ORCID,Qian Yun¹^ORCID,Leung L. Ruby¹^ORCID,Zhang Yang²^ORCID

Affiliation:

1. Atmospheric Sciences and Global Change Division Pacific Northwest National Laboratory Richland WA USA

2. Department of Civil and Environmental Engineering Northeastern University Boston MA USA

Funder

U.S. Environmental Protection Agency

U.S. Department of Energy

Pacific Northwest National Laboratory

Publisher

American Geophysical Union (AGU)

Subject

Earth and Planetary Sciences (miscellaneous),General Environmental Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020EF001910

Reference81 articles.

1. Development of gridded surface meteorological data for ecological applications and modelling

2. Relationships between climate and macroscale area burned in the western United States

3. Impact of anthropogenic climate change on wildfire across western US forests

4. Global warming and changes in risk of concurrent climate extremes: Insights from the 2014 California drought

5. Global and regional analysis of climate and human drivers of wildfire

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1. On the use of hydrodynamic modelling and random forest classifiers for the prediction of hypoxia in coastal lagoons;Science of The Total Environment;2024-11

2. Integrating machine learning for enhanced wildfire severity prediction: A study in the Upper Colorado River basin;Science of The Total Environment;2024-11

3. A Data-Driven Model for Wildfire Prediction in California;2024 International Conference on Smart Applications, Communications and Networking (SmartNets);2024-05-28

4. Land, jet stream, and other atmospheric effects on burned area estimation during the South Asian heatwave of 2022;International Journal of Applied Earth Observation and Geoinformation;2024-04

5. Systematically tracking the hourly progression of large wildfires using GOES satellite observations;Earth System Science Data;2024-03-15

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