A New Vegetation Index to Detect Periodically Submerged Mangrove Forest Using Single-Tide Sentinel-2 Imagery

doi:10.3390/rs11172043

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	A New Vegetation Index to Detect Periodically Submerged Mangrove Forest Using Single-Tide Sentinel-2 Imagery
	Jia, Mingming 2,3; Wang, Zongming 2; Wang, Chao 3; Mao, Dehua 2; Zhang, Yuanzhi 1,4
刊名	REMOTE SENSING
	2019-09-01
卷号	11 期号:17 页码:17
关键词	Sentinel-2 MultiSpectral Instrument (MSI) red-edge band aquatic vegetation tidal condition vegetation index coastal vegetation
DOI	10.3390/rs11172043
英文摘要	Mangrove forests are tropical trees and shrubs that grow in sheltered intertidal zones. Accurate mapping of mangrove forests is a great challenge for remote sensing because mangroves are periodically submerged by tidal floods. Traditionally, multi-tides images were needed to remove the influence of water; however, such images are often unavailable due to rainy climates and uncertain local tidal conditions. Therefore, extracting mangrove forests from a single-tide imagery is of great importance. In this study, reflectance of red-edge bands in Sentinel-2 imagery were utilized to establish a new vegetation index that is sensitive to submerged mangrove forests. Specifically, red and short-wave near infrared bands were used to build a linear baseline; the average reflectance value of four red-edge bands above the baseline is defined as the Mangrove Forest Index (MFI). To evaluate MFI, capabilities of detecting mangrove forests were quantitatively assessed between MFI and four widely used vegetation indices (VIs). Additionally, the practical roles of MFI were validated by applying it to three mangrove forest sites globally. Results showed that: (1) theoretically, Jensen-Shannon divergence demonstrated that a submerged mangrove forest and water pixels have the largest distance in MFI compared to other VIs. In addition, the boxplot showed that all submerged mangrove forests could be separated from the water background in the MFI image. Furthermore, in the MFI image, to separate mangrove forests and water, the threshold is a constant that is equal to zero. (2) Practically, after applying the MFI to three global sites, 99-102% of submerged mangrove forests were successfully extracted by MFI. Although there are still some uncertainties and limitations, the MFI offers great benefits in accurately mapping mangrove forests as well as other coastal and aquatic vegetation worldwide.
资助项目	Science and Technology Basic Resources Investigation Program of China[2017FY100706] ; National Natural Science Foundation of China[41601470] ; National Natural Science Foundation of China[41601406] ; Strategic Planning Project of the Institute of Northeast Geography and Agroecology (IGA), Chinese Academy of Sciences[Y6H2091000] ; Youth Innovation Promotion Association of Chinese Academy of Sciences[2017277] ; Youth Innovation Promotion Association of Chinese Academy of Sciences[2012178] ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University[19I02]
WOS关键词	DIFFERENCE WATER INDEX ; AQUATIC VEGETATION ; TAIHU LAKE ; LANDSAT ; CHINA ; TREE ; RED ; CLASSIFICATION ; CONSERVATION ; ECOSYSTEMS
WOS研究方向	Remote Sensing
语种	英语
出版者	MDPI
WOS记录号	WOS:000486874300087
资助机构	Science and Technology Basic Resources Investigation Program of China ; Science and Technology Basic Resources Investigation Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Strategic Planning Project of the Institute of Northeast Geography and Agroecology (IGA), Chinese Academy of Sciences ; Strategic Planning Project of the Institute of Northeast Geography and Agroecology (IGA), Chinese Academy of Sciences ; Youth Innovation Promotion Association of Chinese Academy of Sciences ; Youth Innovation Promotion Association of Chinese Academy of Sciences ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Science and Technology Basic Resources Investigation Program of China ; Science and Technology Basic Resources Investigation Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Strategic Planning Project of the Institute of Northeast Geography and Agroecology (IGA), Chinese Academy of Sciences ; Strategic Planning Project of the Institute of Northeast Geography and Agroecology (IGA), Chinese Academy of Sciences ; Youth Innovation Promotion Association of Chinese Academy of Sciences ; Youth Innovation Promotion Association of Chinese Academy of Sciences ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Science and Technology Basic Resources Investigation Program of China ; Science and Technology Basic Resources Investigation Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Strategic Planning Project of the Institute of Northeast Geography and Agroecology (IGA), Chinese Academy of Sciences ; Strategic Planning Project of the Institute of Northeast Geography and Agroecology (IGA), Chinese Academy of Sciences ; Youth Innovation Promotion Association of Chinese Academy of Sciences ; Youth Innovation Promotion Association of Chinese Academy of Sciences ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Science and Technology Basic Resources Investigation Program of China ; Science and Technology Basic Resources Investigation Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Strategic Planning Project of the Institute of Northeast Geography and Agroecology (IGA), Chinese Academy of Sciences ; Strategic Planning Project of the Institute of Northeast Geography and Agroecology (IGA), Chinese Academy of Sciences ; Youth Innovation Promotion Association of Chinese Academy of Sciences ; Youth Innovation Promotion Association of Chinese Academy of Sciences ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University
内容类型	期刊论文
源URL	[http://ir.bao.ac.cn/handle/114a11/27868]
专题	中国科学院国家天文台
通讯作者	Wang, Zongming
作者单位	1.Chinese Univ Hong Kong, Ctr Housing Innovat, Shatin, Hong Kong, Peoples R China 2.Chinese Acad Sci, Key Lab Wetland Ecol & Environm, Northeast Inst Geog & Agroecol, 4888 Shengbei St, Changchun 130102, Jilin, Peoples R China 3.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, 129 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China 4.Chinese Acad Sci, Key Lab Lunar Sci & Deep Explorat, Natl Astron Observ, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Jia, Mingming,Wang, Zongming,Wang, Chao,et al. A New Vegetation Index to Detect Periodically Submerged Mangrove Forest Using Single-Tide Sentinel-2 Imagery[J]. REMOTE SENSING,2019,11(17):17.
APA	Jia, Mingming,Wang, Zongming,Wang, Chao,Mao, Dehua,&Zhang, Yuanzhi.(2019).A New Vegetation Index to Detect Periodically Submerged Mangrove Forest Using Single-Tide Sentinel-2 Imagery.REMOTE SENSING,11(17),17.
MLA	Jia, Mingming,et al."A New Vegetation Index to Detect Periodically Submerged Mangrove Forest Using Single-Tide Sentinel-2 Imagery".REMOTE SENSING 11.17(2019):17.