Seagrass Resource Assessment Using WorldView-2 Imagery in the Redfish Bay, Texas

被引:18
作者
Su, Lihong [1 ]
Huang, Yuxia [2 ]
机构
[1] Texas A&M Univ, Harte Res Inst Gulf Mexico Studies, 6300 Ocean Dr,Unit 5869, Corpus Christi, TX 78412 USA
[2] Texas A&M Univ, Dept Comp Sci, 6300 Ocean Dr,Unit 5824, Corpus Christi, TX 78412 USA
关键词
coastal water; water depth correction; seagrass; object-based image analysis; WorldView-2; SHALLOW-WATER BATHYMETRY; BENTHIC HABITATS; OCEAN COLOR; SPECTRAL REFLECTANCE; DIFFUSE-REFLECTANCE; HALODULE-WRIGHTII; SUN GLINT; REMOTE; SATELLITE; CLASSIFICATION;
D O I
10.3390/jmse7040098
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Seagrass meadows play important roles as habitats for many marine organisms, traps for sediment, and buffers against wave actions. The objective of this paper is to map seagrass meadows in the Redfish Bay, Texas from WorldView-2 imagery. Seagrass meadows grow in shallow and clear water areas in the Redfish Bay. The WorldView-2 satellite can acquire multispectral imagery from the bay bottom with 2 m spatial resolution 8 multispectral bands and 0.46 m panchromatic imagery. The top of atmosphere radiance was transformed to the bottom reflectance through the atmospheric correction and the water column correction. The object based image analysis was used to identify seagrass meadows distributions in the Redfish Bay. This investigation demonstrated that seagrass can be identified with 94% accuracy, although seagrass species cannot be satisfactorily recognized. The results implied that the WorldView-2 satellite imagery is a suitable data source for seagrass distribution mapping.
引用
收藏
页数:16
相关论文
共 50 条
[31]   Testing high spatial resolution WorldView-2 Imagery for retrieving the Leaf Area Index [J].
Tarantino, Eufemia ;
Novelli, Antonio ;
Laterza, Maurizio ;
Gioia, Andrea .
THIRD INTERNATIONAL CONFERENCE ON REMOTE SENSING AND GEOINFORMATION OF THE ENVIRONMENT (RSCY2015), 2015, 9535
[32]   Application of feature selection methods and machine learning algorithms for saltmarsh biomass estimation using Worldview-2 imagery [J].
Rasel, Sikdar M. M. ;
Chang, Hsing-Chung ;
Ralph, Timothy J. ;
Saintilan, Neil ;
Diti, Israt Jahan .
GEOCARTO INTERNATIONAL, 2021, 36 (10) :1075-1099
[33]   Using multi-angle WorldView-2 imagery to determine ocean depth near the island of Oahu, Hawaii [J].
Lee, Krista R. ;
Olsen, Richard C. ;
Kruse, Fred A. .
ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XVIII, 2012, 8390
[34]   STATISTICAL BUILDING ROOF RECONSTRUCTION FROM WORLDVIEW-2 STEREO IMAGERY [J].
Partovi, T. ;
Huang, H. ;
Krauss, T. ;
Mayer, H. ;
Reinartz, P. .
PIA15+HRIGI15 - JOINT ISPRS CONFERENCE, VOL. I, 2015, 40-3 (W2) :161-167
[35]   The Optimal Parameter Combination For Vehicle Detection From WorldView-2 Imagery [J].
Liang, Yanping ;
Yang, Qiang .
2016 INTERNATIONAL CONFERENCE ON LOGISTICS, INFORMATICS AND SERVICE SCIENCES (LISS' 2016), 2016,
[36]   Using WorldView-2 to determine bottom-type and bathymetry [J].
Lee, Krista R. ;
Kim, Angela M. ;
Olsen, R. C. ;
Kruse, Fred A. .
OCEAN SENSING AND MONITORING III, 2011, 8030
[37]   BATHYMETRIC EXTRACTION USING WORLDVIEW-2 HIGH RESOLUTION IMAGES [J].
Deidda, M. ;
Sanna, G. .
XXII ISPRS CONGRESS, TECHNICAL COMMISSION VIII, 2012, 39-B8 :153-157
[38]   OBJECT-BASED ANALYSIS OF WORLDVIEW-2 IMAGERY OF URBAN AREAS [J].
Rizvi, Imdad Ali ;
Mohan, B. Krishna .
2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, :431-434
[39]   A Hierarchical Object-oriented Urban Land Cover Classification Using WorldView-2 Imagery and Airborne LiDAR data [J].
Wu, M. F. ;
Sun, Z. C. ;
Yang, B. ;
Yu, S. S. .
6TH DIGITAL EARTH SUMMIT, 2016, 46
[40]   Classification of Coral Reef Benthos around Ganquan Island Using WorldView-2 Satellite Imagery [J].
Xu, Hui ;
Liu, Zhen ;
Zhu, Jinshan ;
Lu, Xiushan ;
Liu, Qiang .
JOURNAL OF COASTAL RESEARCH, 2019, :466-474