Spatial Prioritization for Wildfire Mitigation by Integrating Heterogeneous Spatial Data: A New Multi-Dimensional Approach for Tropical Rainforests

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Date
2022
Authors
Sakti, Anjar Dimara
Fauzi, Adam Irwansyah
Takeuchi, Wataru
Pradhan, Biswajeet
Yarime, Masaru
Vega García, CristinaVega García, Cristina - ORCID ID
Agustina, Elprida
Wibisono, Dionisius
Anggraini, Tania Septi
Theodora, Megawati Oktaviani
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cc-by (c) Anjar Dimara Sakti et. al., 2022
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Abstract
Wildfires drive deforestation that causes various losses. Although many studies have used spatial approaches, a multi-dimensional analysis is required to determine priority areas for mitigation. This study identified priority areas for wildfire mitigation in Indonesia using a multi-dimensional approach including disaster, environmental, historical, and administrative parameters by integrating 20 types of multi-source spatial data. Spatial data were combined to produce susceptibility, carbon stock, and carbon emission models that form the basis for prioritization modelling. The developed priority model was compared with historical deforestation data. Legal aspects were evaluated for oil-palm plantations and mining with respect to their impact on wildfire mitigation. Results showed that 379,516 km2 of forests in Indonesia belong to the high-priority category and most of these are located in Sumatra, Kalimantan, and North Maluku. Historical data suggest that 19.50% of priority areas for wildfire mitigation have experienced deforestation caused by wildfires over the last ten years. Based on legal aspects of land use, 5.2% and 3.9% of high-priority areas for wildfire mitigation are in oil palm and mining areas, respectively. These results can be used to support the determination of high-priority areas for the REDD+ program and the evaluation of land use policies.
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Remote Sensing, 2022, vol. 14, núm. 3, art. 543