TY - JOUR
T1 - Spatial Prioritization for Wildfire Mitigation by Integrating Heterogeneous Spatial Data
T2 - A New Multi-Dimensional Approach for Tropical Rainforests
AU - Sakti, Anjar Dimara
AU - Fauzi, Adam Irwansyah
AU - Takeuchi, Wataru
AU - Pradhan, Biswajeet
AU - Yarime, Masaru
AU - Vega-Garcia, Cristina
AU - Agustina, Elprida
AU - Wibisono, Dionisius
AU - Anggraini, Tania Septi
AU - Theodora, Megawati Oktaviani
AU - Ramadhanti, Desi
AU - Muhammad, Miqdad Fadhil
AU - Aufaristama, Muhammad
AU - Perdana, Agung Mahadi Putra
AU - Wikantika, Ketut
N1 - Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/2/1
Y1 - 2022/2/1
N2 - 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.
AB - 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.
KW - GIS modeling
KW - REDD+
KW - Remote sensing
KW - Spatial data-driven approaches
KW - Tropical rainforests
KW - Wildfire mitigation
UR - https://www.scopus.com/pages/publications/85123420584
UR - https://www.scopus.com/pages/publications/85123420584#tab=citedBy
U2 - 10.3390/rs14030543
DO - 10.3390/rs14030543
M3 - Article
AN - SCOPUS:85123420584
SN - 2072-4292
VL - 14
JO - Remote Sensing
JF - Remote Sensing
IS - 3
M1 - 543
ER -