Evaluating Lightning‐Caused Fire Occurrence Using Spatial Generalized Additive Models: A Case Study in Central Spain-Reference-Cited by-同舟云学术

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Evaluating Lightning‐Caused Fire Occurrence Using Spatial Generalized Additive Models: A Case Study in Central Spain

Published:2020-04-29 Issue:7 Volume:40 Page:1418-1437
ISSN:0272-4332
Container-title:Risk Analysis
language:en
Short-container-title:Risk Analysis

Author:

Rodríguez‐Pérez José Ramón¹^ORCID,Ordóñez Celestino²^ORCID,Roca‐Pardiñas Javier³^ORCID,Vecín‐Arias Daniel¹^ORCID,Castedo‐Dorado Fernando¹^ORCID

Affiliation:

1. GEOINCA Research GroupUniversidad de León Ponferrada León Spain

2. Department of Mining Exploitation and Prospecting, Polytechnic School of MieresUniversidad de Oviedo Mieres Asturias Spain

3. Department of Statistics and Operations Research, SIDOR Research GroupUniversidad de Vigo Vigo Pontevedra Spain

Funder

University of León

Publisher

Wiley

Subject

Physiology (medical),Safety, Risk, Reliability and Quality

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/risa.13488

Reference81 articles.

1. Using multi variate data mining techniques for estimating fire susceptibility of Tyrolean forests

2. Probit in a Spatial Context: A Monte Carlo Analysis

3. Why and how do ecosystems burn?

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1. A Forest Fire Prediction Method for Lightning Stroke Based on Remote Sensing Data;Forests;2024-04-02

2. Lightning-Induced Wildfires: An Overview;Fire;2024-03-02

3. A novel clustering-based resampling with cost-sensitive boosting method to model and map wildfire susceptibility;Reliability Engineering & System Safety;2024-02

4. Drivers and Trends in the Size and Severity of Forest Fires Endangering WUI Areas: A Regional Case Study;Forests;2023-12-02

5. Lightning nowcasting with aerosol-informed machine learning and satellite-enriched dataset;npj Climate and Atmospheric Science;2023-08-24

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