Preprints
https://doi.org/10.5194/nhess-2021-131
https://doi.org/10.5194/nhess-2021-131

  12 May 2021

12 May 2021

Review status: this preprint is currently under review for the journal NHESS.

Data-based wildfire risk model for Mediterranean ecosystems. Study case of Concepcion Metropolitan Area in Central Chile

Edilia Jaque Castillo1, Alfonso Fernández1, Rodrigo Fuentes Robles2, and Carolina G. Ojeda3 Edilia Jaque Castillo et al.
  • 1Department of Geography, Universidad de Concepción, Concepción, Chile
  • 2Department of Forestry Sciences, Universidad de Concepción, Chile
  • 3Facultad de Arquitectura, Diseño y Estudios Urbanos, Pontificia Universidad Católica de Chile, Santiago Chile

Abstract. Wildfire risk is latent in Chilean metropolitan areas characterized by the strong presence of Wildland-Urban Interfaces (WUI). The Metropolitan Area of Concepción (CMA) constitutes one of the most representative samples of that dynamic. The wildfire risk in the CMA was addressed by establishing a model of 5 categories (Near Zero, Low, Medium, 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 spots 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 medium 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 to trigger more severe and large wildfires because of human activities.

Edilia Jaque Castillo et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-131', Paul Santi, 08 Jun 2021
  • RC2: 'Comment on nhess-2021-131', Damiano Vacha, 10 Aug 2021

Edilia Jaque Castillo et al.

Edilia Jaque Castillo et al.

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Short summary
Wildfires pose risks to lives and livelihoods in many regions of the world. Particularly in Chile's Central South region, climate change, widespread land use change, and urban growth tend to increase the likelihood of fire occurrence. Our work focused on the Concepción Metropolitan Area where we developed a model using Machine Learning in order to map wildfire risks. We found that the interface between urban areas and forestry plantations presents highest risks.
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