Forests 2018, 9(7), 389; https://doi.org/10.3390/f9070389
Monitoring Deforestation in Rainforests Using Satellite Data: A Pilot Study from Kalimantan, Indonesia
Hadi 1,*
, Andrey Krasovskii 2, Victor Maus 2,3, Ping Yowargana 2, Stephan Pietsch 2 and Miina Rautiainen 1,4
, Andrey Krasovskii 2, Victor Maus 2,3, Ping Yowargana 2, Stephan Pietsch 2 and Miina Rautiainen 1,4
1
Department of Built Environment, School of Engineering, Aalto University, P.O. Box 14100, 00076 Aalto, Finland
2
Ecosystems Services and Management (ESM) Program, International Institute for Applied Systems Analysis (IIASA), A-2361 Laxenburg, Austria
3
Institute for Ecological Economics, Vienna University of Economics and Business (WU), 1020 Wien, Austria
4
Department of Electronics and Nanoengineering, School of Electrical Engineering, Aalto University, P.O. Box 15500, 00076 Aalto, Finland
*
Author to whom correspondence should be addressed.
Received: 11 May 2018 / Revised: 22 June 2018 / Accepted: 26 June 2018 / Published: 2 July 2018
(This article belongs to the Special Issue Our Future Forests and Their Products—How to Get out of the Woods—Selected Papers from the IUFRO 125th Anniversary Congress)
Abstract
Monitoring large forest areas is presently feasible with satellite remote sensing as opposed to time-consuming and expensive ground surveys as alternative. This study evaluated, for the first time, the potential of using freely available medium resolution (30 m) Landsat time series data for deforestation monitoring in tropical rainforests of Kalimantan, Indonesia, at sub-annual time scales. A simple, generic, data-driven algorithm for deforestation detection based on a consecutive anomalies criterion was proposed. An accuracy assessment in the spatial and the temporal domain was carried out using high-confidence reference sample pixels interpreted with the aid of multi-temporal very high spatial resolution image series. Results showed a promising spatial accuracy, when three consecutive anomalies were required to confirm a deforestation event. Recommendations in tuning the algorithm for different operational use cases were provided within the context of satisfying REDD+ requirements, depending on whether spatial accuracy or temporal accuracy need to be optimized. View Full-TextKeywords:
tropical; deforestation; monitoring; South East Asia; Landsat; REDD+
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MDPI and ACS Style
Hadi; Krasovskii, A.; Maus, V.; Yowargana, P.; Pietsch, S.; Rautiainen, M. Monitoring Deforestation in Rainforests Using Satellite Data: A Pilot Study from Kalimantan, Indonesia. Forests 2018, 9, 389.
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