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DOI10.3390/s19081933
A Review of Remote Sensing Approaches for Monitoring Blue Carbon Ecosystems: Mangroves, Seagrasses and Salt Marshes during 2010-2018
Tien Dat Pham1; Xia, Junshi1; Nam Thang Ha2,3; Dieu Tien Bui4; Nga Nhu Le5; Takeuchi, Wataru6
发表日期2019
ISSN1424-8220
卷号19期号:8
英文摘要

Blue carbon (BC) ecosystems are an important coastal resource, as they provide a range of goods and services to the environment. They play a vital role in the global carbon cycle by reducing greenhouse gas emissions and mitigating the impacts of climate change. However, there has been a large reduction in the global BC ecosystems due to their conversion to agriculture and aquaculture, overexploitation, and removal for human settlements. Effectively monitoring BC ecosystems at large scales remains a challenge owing to practical difficulties in monitoring and the time-consuming field measurement approaches used. As a result, sensible policies and actions for the sustainability and conservation of BC ecosystems can be hard to implement. In this context, remote sensing provides a useful tool for mapping and monitoring BC ecosystems faster and at larger scales. Numerous studies have been carried out on various sensors based on optical imagery, synthetic aperture radar (SAR), light detection and ranging (LiDAR), aerial photographs (APs), and multispectral data. Remote sensing-based approaches have been proven effective for mapping and monitoring BC ecosystems by a large number of studies. However, to the best of our knowledge, this is the first comprehensive review on the applications of remote sensing techniques for mapping and monitoring BC ecosystems. The main goal of this review is to provide an overview and summary of the key studies undertaken from 2010 onwards on remote sensing applications for mapping and monitoring BC ecosystems. Our review showed that optical imagery, such as multispectral and hyper-spectral data, is the most common for mapping BC ecosystems, while the Landsat time-series are the most widely-used data for monitoring their changes on larger scales. We investigate the limitations of current studies and suggest several key aspects for future applications of remote sensing combined with state-of-the-art machine learning techniques for mapping coastal vegetation and monitoring their extents and changes.


WOS研究方向Chemistry ; Engineering ; Instruments & Instrumentation
来源期刊SENSORS
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/96244
作者单位1.RIKEN, Geoinformat Unit, Ctr Adv Intelligence Project AIP, Chuo Ku, Mitsui Bldg,15th Floor,1-4-1 Nihonbashi, Tokyo 1030027, Japan;
2.Univ Waikato, Environm Res Inst, Sch Sci, Hamilton 3240, New Zealand;
3.Hue Univ Agr & Forestry, Fac Fisheries, Hue 49000, Vietnam;
4.Univ South Eastern Norway, Geog Informat Syst Grp, Dept Business & IT, Gullbringvegen 36, N-3800 BoiTelemark, Norway;
5.VAST, Inst Mech, Dept Marine Mech & Environm, 264 Doi Can St, Hanoi 100000, Vietnam;
6.Univ Tokyo, Inst Ind Sci, Meguro Ku, 4-6-1 Komaba, Tokyo 1538505, Japan
推荐引用方式
GB/T 7714
Tien Dat Pham,Xia, Junshi,Nam Thang Ha,et al. A Review of Remote Sensing Approaches for Monitoring Blue Carbon Ecosystems: Mangroves, Seagrasses and Salt Marshes during 2010-2018[J],2019,19(8).
APA Tien Dat Pham,Xia, Junshi,Nam Thang Ha,Dieu Tien Bui,Nga Nhu Le,&Takeuchi, Wataru.(2019).A Review of Remote Sensing Approaches for Monitoring Blue Carbon Ecosystems: Mangroves, Seagrasses and Salt Marshes during 2010-2018.SENSORS,19(8).
MLA Tien Dat Pham,et al."A Review of Remote Sensing Approaches for Monitoring Blue Carbon Ecosystems: Mangroves, Seagrasses and Salt Marshes during 2010-2018".SENSORS 19.8(2019).
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