Editorial: EVA 2021 data challenge on spatiotemporal prediction of wildfire extremes in the USA
Author:
Publisher
Springer Science and Business Media LLC
Subject
Economics, Econometrics and Finance (miscellaneous),Engineering (miscellaneous),Statistics and Probability
Link
https://link.springer.com/content/pdf/10.1007/s10687-023-00465-x.pdf
Reference7 articles.
1. Jones, M.W., Smith, A., Betts, R., et al.: Climate change increases risk of wildfires. Sci. J. Rev. (2020)
2. Koh, J., Pimont, F., Dupuy, J.L., et al.: Spatiotemporal wildfire modeling through point processes with moderate and extreme marks. Ann. Appl. Stat. 17, 560–582 (2023)
3. Pereira, J., Turkman, K.: Statistical models of vegetation fires: spatial and temporal patterns. In: Handbook of Environmental and Ecological Statistics, pp. 401–420. Chapman and Hall/CRC (2019)
4. Preisler, H.K., Brillinger, D.R., Burgan, R.E., et al.: Probability based models for estimation of wildfire risk. Int. J. Wildland Fire 13(2), 133–142 (2004)
5. Short, K.C.: Spatial wildfire occurrence data for the United States, 1992–2015. Tech. rep., Forest Service Research Data Archive, Fort Collins, CO. (2017). https://doi.org/10.2737/RDS-2013-0009.4
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