Modeling the Ignition Risk: Analysis before and after Megafire on Maule Region, Chile
Wildland fires are a phenomenon of broad interest due to their relationship with climate change. The impacts of climate change are related to a greater frequency and intensity of wildland fires. In this context, megafires have become a phenomenon of particular concern. In this study, we develop a mo...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/18/9353 |
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| author | Gabriela Azócar de la Cruz Gabriela Alfaro Claudia Alonso Rubén Calvo Paz Orellana |
| author_facet | Gabriela Azócar de la Cruz Gabriela Alfaro Claudia Alonso Rubén Calvo Paz Orellana |
| author_sort | Gabriela Azócar de la Cruz |
| collection | DOAJ |
| description | Wildland fires are a phenomenon of broad interest due to their relationship with climate change. The impacts of climate change are related to a greater frequency and intensity of wildland fires. In this context, megafires have become a phenomenon of particular concern. In this study, we develop a model of ignition risk. We use factors such as human activity, geographic, topographic, and land cover variables to develop a bagged decision tree model. The study area corresponds to the Maule region in Chile, a large zone with a Mediterranean climate. This area was affected by a megafire in 2017. After generating the model, we compared three interface zones, analyzing the scar and the occurrences of ignition during and after the megafire. For the construction of georeferenced data, we used the geographic information system QGIS. The results show a model with high fit goodness that can be replicated in other areas. Fewer ignitions are observed after the megafire, a high recovery of urban infrastructure, and a slow recovery of forest plantations. It is feasible to interpret that the lower number of ignitions observed in the 2019–2020 season is a consequence of the megafire scar. It is crucial to remember that the risk of ignition will increase as forest crops recover. Wildland fire management requires integrating this information into decision-making processes if we consider that the impacts of climate change persist in the area. |
| first_indexed | 2024-03-10T00:47:30Z |
| format | Article |
| id | doaj.art-d6cbb7df94324897a80225a30faa373b |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T00:47:30Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-d6cbb7df94324897a80225a30faa373b2023-11-23T14:57:14ZengMDPI AGApplied Sciences2076-34172022-09-011218935310.3390/app12189353Modeling the Ignition Risk: Analysis before and after Megafire on Maule Region, ChileGabriela Azócar de la Cruz0Gabriela Alfaro1Claudia Alonso2Rubén Calvo3Paz Orellana4Department of Social Work, University of Chile, Av. Ignacio Carrera Pinto 1045, Ñuñoa, Santiago 7800284, ChileNucleus of Transdisciplinary Systemic Studies, University of Chile, Santiago 7820436, ChileCenter for Climate and Resilience Research (CR), Blanco Encalada 2002, Floor 4, Santiago 8370449, ChileNucleus of Transdisciplinary Systemic Studies, University of Chile, Santiago 7820436, ChileNucleus of Transdisciplinary Systemic Studies, University of Chile, Santiago 7820436, ChileWildland fires are a phenomenon of broad interest due to their relationship with climate change. The impacts of climate change are related to a greater frequency and intensity of wildland fires. In this context, megafires have become a phenomenon of particular concern. In this study, we develop a model of ignition risk. We use factors such as human activity, geographic, topographic, and land cover variables to develop a bagged decision tree model. The study area corresponds to the Maule region in Chile, a large zone with a Mediterranean climate. This area was affected by a megafire in 2017. After generating the model, we compared three interface zones, analyzing the scar and the occurrences of ignition during and after the megafire. For the construction of georeferenced data, we used the geographic information system QGIS. The results show a model with high fit goodness that can be replicated in other areas. Fewer ignitions are observed after the megafire, a high recovery of urban infrastructure, and a slow recovery of forest plantations. It is feasible to interpret that the lower number of ignitions observed in the 2019–2020 season is a consequence of the megafire scar. It is crucial to remember that the risk of ignition will increase as forest crops recover. Wildland fire management requires integrating this information into decision-making processes if we consider that the impacts of climate change persist in the area.https://www.mdpi.com/2076-3417/12/18/9353wildfireignition riskmodelmegafireclimate changebagged decision tree |
| spellingShingle | Gabriela Azócar de la Cruz Gabriela Alfaro Claudia Alonso Rubén Calvo Paz Orellana Modeling the Ignition Risk: Analysis before and after Megafire on Maule Region, Chile Applied Sciences wildfire ignition risk model megafire climate change bagged decision tree |
| title | Modeling the Ignition Risk: Analysis before and after Megafire on Maule Region, Chile |
| title_full | Modeling the Ignition Risk: Analysis before and after Megafire on Maule Region, Chile |
| title_fullStr | Modeling the Ignition Risk: Analysis before and after Megafire on Maule Region, Chile |
| title_full_unstemmed | Modeling the Ignition Risk: Analysis before and after Megafire on Maule Region, Chile |
| title_short | Modeling the Ignition Risk: Analysis before and after Megafire on Maule Region, Chile |
| title_sort | modeling the ignition risk analysis before and after megafire on maule region chile |
| topic | wildfire ignition risk model megafire climate change bagged decision tree |
| url | https://www.mdpi.com/2076-3417/12/18/9353 |
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