The Indonesian wildfires in 1997 and 2015, which affected approximately 25-30% of carbon-rich and fire-susceptible peatland in the country, brought negative environmental, humanitarian, and economic impacts. Given that Indonesia has the world's second-largest peatland area, this study analyses the effectiveness of the postdisaster governance of peatland fires from 1982 to 2020. By utilising data from interviews, observations, document reviews, and open-source web apps, this study shows that the country has experienced policy transformation that adapts risk governance principles for peatland management. This transformation affects the effectiveness of the post-disaster governance of peatland wildfires.
Climate crisis and unsustainable activities in Indonesia’s marine and fisheries sector have led the ocean into troubled waters. The country must strengthen their commitments to ensure ocean resources are managed sustainably and equitably. This report aggregates the best available data and provides in-depth analysis on marine and fisheries issues to encourage evidence-based approaches in decision-making processes.
From previous research reported that tropical peatland is one of terrestrial carbon storage in Earth, and has contribution to climate change. Synthetic Aperture Radar (SAR) is one of remote sensing technology which is more efcient than optical remote sensing. Its ability to penetrate cloud makes it useful to monitor tropical environment. This research is conducted in a tropical peatland in Siak Regency, Riau Province. This research was conducted to identify tropical peatland in Siak Regency using polarimetric decomposition, unsupervised classifcation ISODATA, and Radar Vegetation Index (RVI) from SAR data that had been geometrically and radiometrically corrected. Polarimetric decomposition Freeman-Durden was performed to analyze radar backscattering mechanism in tropical peatland, which shows that volume and surface scattering was dominant because of the presence of vegetation and open area. Unsupervised classifcation ISODATA was then performed to extract “shrub class”. By assessing its accuracy, the class that represents shrub class in reference map was selected as the selected “shrub class”. RVI then was calculated using a certain formula. Spatial analysis was then conducted to acquire certain information that average value of RVI in tropical peatland tend to be higher than in non-tropical peatland. By integrating selected “shrub class” and RVI, peat classes were extracted. The best peat class was selected by comparing with peatland referenced map which is acquired from the Indonesian Agency for Agricultural Resources and Development (IAARD) using error matrix. In this research, the best peat class yielded 73.5 percent of Producer’s Accuracy (PA), 81.6 percent of User’s Accuracy (UA), 66.1 percent of Overall Accuracy (OA), and 0.1079 of Kappa coefcient (Ks).
Peatland clearing and draining are associated with many peat fires in South Sumatera. In 2020 we developed prioritization of peat land clearing areas using GLAD alert data to prevent catastrophic peat fires. GLAD alert data is near real-time alerting system that detects loss of trees, produced by University of Maryland and Global Forest Watch. This research aims to get prioritized area indicating land clearing and to test its reliability to prevent peat fires in South Sumatra. A total of 634 cluster areas indicating peatland clearing were found in between July and September 2020, which 20 of those cluster areas are selected for validation (ground truth). Validation was conducted by field survey and flying Unmanned Aerial Vehicle (UAV) in 3 districts, namely Musi Rawas Utara, Banyuasin, and Ogan Komering Ilir. The survey confirmed that 19 clusters experienced forest fires, land clearing, and rejuvenation of plantation. Meanwhile, the others became savanna from previous forest fires and former land clearing by burning. Prioritization areas using GLAD alert data was capable to detect land clearing, but further study is needed to predict peat fires due to peatland clearing.
Catatan teknis ini dibuat untuk menjelaskan pendekatan dan metode priorititasi data peringatan mingguan GLAD pada tiga kegiatan pemantauan, yaitu: (1) pemantauan kegiatan penebangan hutan ilegal; (2) pemantauan lanskap; dan (3) pemantauan pembukaan lahan dan hutan gambut.
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