气候变化领域集成服务门户(CCPortal): Structural characterisation of mangrove forests achieved through combining multiple sources of remote sensing data

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DOI	10.1016/j.rse.2019.111543
	Structural characterisation of mangrove forests achieved through combining multiple sources of remote sensing data
	Lucas R.; Van De Kerchove R.; Otero V.; Lagomasino D.; Fatoyinbo L.; Omar H.; Satyanarayana B.; Dahdouh-Guebas F.
发表日期	2020
ISSN	00344257
卷号	237
英文摘要	Temporal information on mangrove extent, age, structure and biomass provides an important contribution towards understanding the role of these ecosystems in terms of the services they provide (e.g., in relation to storage of carbon, conservation biodiversity), particularly given the diversity of influences of human activity and natural events and processes. Focusing on the Matang Mangrove Forest Reserve (MMFR) in Perak Province, Peninsular Malaysia, this study aimed to retrieve comprehensive information on the biophysical properties of mangroves from spaceborne optical and Synthetic Aperture Radar (SAR) to support better understanding of their dynamics in a managed setting. For the period 1988 to 2016 (29 years), forest age was estimated on at least an annual basis by combining time-series of Landsat-derived Normalised Difference Moisture Index (NDMI) and Japanese L-band Synthetic Aperture Radar (SAR) data. The NDMI was further used to retrieve canopy cover (%). Interferometric Shuttle Radar Topographic Mission (SRTM) X/C-band (2000), TanDEM-X-band (2010–2016) and stereo WorldView-2 stereo (2016) data were evaluated for their role in estimating canopy height (CH), from which above ground biomass (AGB, Mg ha−1) was derived using pre-established allometry. Whilst both L-band HH and HV data increased with AGB after about 8–10 years of growth, retrieval was compromised by mixed scattering from varying amounts of dead woody debris following clearing and wood material within regenerating forests, thinning of trees at ~15 and 20 years, and saturation of L-band SAR data after approximately 20 years of growth. Reference was made to stereo Phantom-3 DJI stereo imagery to support estimation of canopy cover (CC) and validation of satellite-derived CH. AGB estimates were compared with ground-based measurements. Using relationships with forest age, both CH and AGB were estimated for each date of Landsat or L-band SAR observation and the temporal trends in L-band SAR were shown to effectively track the sequences of clearing and regeneration. From these, four stages of the harvesting cycle were defined. The study provided new information on the biophysical properties and growth dynamics of mangrove forests in the MMFR, inputs for future monitoring activities, and methods for facilitating better characterisation and mapping of mangrove areas worldwide. © 2019 The Authors
英文关键词	Forest structure; Management; Mangroves; Remote sensing; Time-series
语种	英语
scopus关键词	Biodiversity; Digital storage; Ecology; Management; Mapping; Reforestation; Remote sensing; Satellite imagery; Stereo image processing; Synthetic aperture radar; Time series; Biophysical properties; Comprehensive information; Forest structure; Ground based measurement; L-band synthetic aperture radars; Mangroves; Monitoring activities; Temporal information; Space-based radar; biophysics; ecosystem service; forest management; Landsat; mangrove; remote sensing; satellite data; synthetic aperture radar; time series analysis; woody debris; WorldView; Malaysia; Matang Mangrove Forest Reserve; Perak; West Malaysia; Rhizophoraceae
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179528
作者单位	Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, Ceredigion SY23 3DB, United Kingdom; Centre for Ecosystem Science (CES), School of Biological, Earth and Environmental Sciences (BEES), University of New South Wales, High Street, Kensington, NSW 2052, Australia; Vlaamse Instelling Voor Technologisch Onderzoek (VITO) Research Organisation, Mol, Belgium; Systems Ecology and Resource Management Research Unit, Department of Organism Biology, Université Libre de Bruxelles (ULB), Av. F.D. Roosevelt 50, CPi 264/1, Brussels, B-1050, Belgium; Division of Forestry & Environment, Forest Research Institute Malaysia (FRIM), Kepong, Selangor 52109, Malaysia; Department of Coastal Studies, East Carolina University, 850 NC-345, Wanchese, NC 27981, United States; Biospheric Sciences Laboratory, Code 618, NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771, United States; Mangrove Research Unit, Institute of Oceanography and Environment, Universiti Malaysia Terengg...
推荐引用方式 GB/T 7714	Lucas R.,Van De Kerchove R.,Otero V.,et al. Structural characterisation of mangrove forests achieved through combining multiple sources of remote sensing data[J],2020,237.
APA	Lucas R..,Van De Kerchove R..,Otero V..,Lagomasino D..,Fatoyinbo L..,...&Dahdouh-Guebas F..(2020).Structural characterisation of mangrove forests achieved through combining multiple sources of remote sensing data.Remote Sensing of Environment,237.
MLA	Lucas R.,et al."Structural characterisation of mangrove forests achieved through combining multiple sources of remote sensing data".Remote Sensing of Environment 237(2020).