Classification of tropical peatland degradation using remote sensing and GIS technique

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Abstract

This paper presents a method to identify tropical peatland degradation using satellite remote sensing and geographic information system (GIS) techniques. Mapping the spatial distribution of tropical peatland degradation is important for decision making of peatland restoration and disaster mitigation against peat fire. This study used Landsat-8 imageries as the basic data to identify the tropical peatland degradation and analyzed using GIS tools. Rupat Island and Tebing Tinggi Island in Riau Province were picked up as pilot project areas for this research because these areas historically had many fire spots in the peatland on last few years. The identification of tropical peatland degradation on Landsat-8 imageries data was carried out using Principal Component Analysis (PCA) on composites of band ratios and single band variables. The identified peatland degradation was overlaid spatially with peat fire events using GIS tools. The results of the analysis were confirmed with the ground check field survey data and other map from a separate study to estimate the accuracy of the proposed method. The results show how the approach can be used to distinguish tropical peatland degradation at locations within a map unit quickly and cost effective. The best band combination of using Landsat 8 for mapping the peatlands, and to classify them, was 753. The land cover types of study areas have a correlation with the historical peat fire, where the peat fire usually occurs in degrade peat land. The result of the degradation peatland map from this study will be useful for decision making on land management, peatland restoration and carbon storage in soil. The classification of the peat area from this study could be used to prioritize the area of restoration program by the Indonesian government and stake holder.

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Sutikno, S., Hidayati, N., Rinaldi, Nasrul, B., Putra, A., & Qomar, N. (2020). Classification of tropical peatland degradation using remote sensing and GIS technique. In AIP Conference Proceedings (Vol. 2255). American Institute of Physics Inc. https://doi.org/10.1063/5.0013881

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