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

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.

Spatial Modeling of Multi-Scenario Optimal Solar Pv Power Plant Distribution to Support Indonesia's Clean Energy Achievement Targets

“…For easier access and more informative information, WebGIS can be developed to interactive WebGIS (Ihsan et al, 2021(c)). Furthermore, to find out the specific impact of the role of solar PV on the provision of clean energy, analysis can be done using calculations of carbon stock and carbon emission models (Sakti et al, 2022). In this study, there has also been no analysis by considering multidisaster aspects (landslides, floods, earthquakes, fires, etc.)…”

Multi-Criteria Assessment for City-Wide Rooftop Solar PV Deployment: A Case Study of Bandung, Indonesia

“…In addition, load matching indicators such as selfconsumption and self-sufficiency are also recommended to be included in future studies. Moreover, city-wide household analysis can be integrated into a multi-hazard analysis assessment [97][98][99] that will benefit spatial planning of vital infrastructure strategic.…”

Multi-Scenario Spatial Modeling of Health Facilities Development to Support the Achievement of Universal Health Coverage

“…The third is modeling forest fire hazards by integrating data on land cover, precipitation, wind speed, and KBDI. The higher the drought rate (KBDI), the lower the rainfall, the higher the wind speed will increase the danger of forest fires (Amri et al, 2016;Sakti et al, 2022;Takeuchi et al, 2015).…”

“…However, the research of Abdullahi et al, (2014) did not consider the disaster aspects of determining the construction site of health facilities. Another study from Sakti et al, (2022) conducted modeling of school conformity areas in West Java by considering aspects of multidisaster, school accessibility, and comfort aspects. Sakti et al, (2022) research has advantages because it reviews multi-disaster aspects, but they do not use weighting.…”

“…Another study from Sakti et al, (2022) conducted modeling of school conformity areas in West Java by considering aspects of multidisaster, school accessibility, and comfort aspects. Sakti et al, (2022) research has advantages because it reviews multi-disaster aspects, but they do not use weighting. Based on the above research, there has been no study that models health facilities by considering accessibility aspects, comfort aspects, and multi-disasters on the island of Kalimantan.…”