Data-based wildfire risk model for Mediterranean ecosystems – case study of the Concepción metropolitan area in central Chile
<p>Wildfire risk is latent in Chilean metropolitan areas characterized by the strong presence of wildland–urban interfaces (WUIs). The Concepción metropolitan area (CMA) constitutes one of the most representative samples of that dynamic. The wildfire risk in the CMA was addressed by establishi...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Copernicus Publications
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/f68e2c70b9b74d65a7ff8235ec9e7266 |
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| Sumario: | <p>Wildfire risk is latent in Chilean metropolitan areas
characterized by the strong presence of wildland–urban interfaces (WUIs). The Concepción metropolitan area (CMA) constitutes one of the most
representative samples of that dynamic. The wildfire risk in the CMA was
addressed by establishing a model of five categories (near zero, low, moderate,
high, and very high) that represent discernible thresholds in fire
occurrence, using geospatial data and satellite images describing anthropic–biophysical factors that trigger fires. Those were used to deliver a model
of fire hazard using machine learning algorithms, including principal
component analysis and Kohonen self-organizing maps in two experimental
scenarios: only native forest and only forestry plantation. The model was
validated using fire hotspots obtained from the forestry government
organization. The results indicated that 12.3 % of the CMA's surface area
has a high and very high risk of a forest fire, 29.4 % has a moderate
risk, and 58.3 % has a low and very low risk. Lastly, the observed main
drivers that have deepened this risk were discussed: first, the evident
proximity between the increasing urban areas with exotic forestry
plantations and, second, climate change that threatens triggering more
severe and large wildfires because of human activities.</p> |
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