Bathymetry, water optical properties, and benthic classification of coral reefs using hyperspectral remote sensing imagery

被引:104
|
作者
Lesser, M. P. [1 ]
Mobley, C. D. [2 ]
机构
[1] Univ New Hampshire, Ctr Marine Biol, Dept Zool, Durham, NH 03824 USA
[2] Sequoia Sci Inc, Bellevue, WA 98005 USA
关键词
coral reefs; remote sensing; optical properties; hyperspectral; benthic classification;
D O I
10.1007/s00338-007-0271-5
中图分类号
Q17 [水生生物学];
学科分类号
071004 ;
摘要
The complexity and heterogeneity of shallow coastal waters over small spatial scales provides a challenging environment for mapping and monitoring benthic habitats using remote sensing imagery. Additionally, changes in coral reef community structure are occurring on unprecedented temporal scales that require large-scale synoptic coverage and monitoring of coral reefs. A variety of sensors and analyses have been employed for monitoring coral reefs: this study applied a spectrum-matching and look-up-table methodology to the analysis of hyperspectral imagery of a shallow coral reef in the Bahamas. In unconstrained retrievals the retrieved bathymetry was on average within 5% of that measured acoustically, and 92% of pixels had retrieved depths within 25% of the acoustic depth. Retrieved absorption coefficients had less than 20% errors observed at blue wavelengths. The reef scale benthic classification derived by analysis of the imagery was consistent with the percent cover of specific coral reef habitat classes obtained by conventional line transects over the reef, and the inversions were robust as the results were similar when the benthic classification retrieval was constrained by measurements of bathymetry or water column optical properties. These results support the use of calibrated hyperspectral imagery for the rapid determination of bathymetry, water optical propel-ties, and the classification of important habitat classes common to coral reefs.
引用
收藏
页码:819 / 829
页数:11
相关论文
共 50 条
  • [41] Convolutional Neural Network with Expert Knowledge for Hyperspectral Remote Sensing Imagery Classification
    Wu, Chunming
    Wang, Meng
    Gao, Lang
    Song, Weijing
    Tian, Tian
    Choo, Kim-Kwang Raymond
    KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2019, 13 (08): : 3917 - 3941
  • [42] Using hyperspectral remote sensing for land cover classification
    Zhang, W
    Sriharan, S
    MULTISPECTRAL AND HYPERSPECTRAL REMOTE SENSING INSTRUMENTS AND APPLICATIONS II, 2005, 5655 : 261 - 270
  • [43] Scene classification dataset using the Tiangong-1 hyperspectral remote sensing imagery and its applications
    Liu K.
    Zhou Z.
    Li S.
    Liu Y.
    Wan X.
    Liu Z.
    Tan H.
    Zhang W.
    Yaogan Xuebao/Journal of Remote Sensing, 2020, 24 (09): : 1077 - 1087
  • [44] Ground-level spectroscopy analyses and classification of coral reefs using a hyperspectral camera
    Caras, T.
    Karnieli, A.
    CORAL REEFS, 2013, 32 (03) : 825 - 834
  • [45] Ground-level spectroscopy analyses and classification of coral reefs using a hyperspectral camera
    T. Caras
    A. Karnieli
    Coral Reefs, 2013, 32 : 825 - 834
  • [46] Characterization and modeling of bio-optical properties of water in a lentic ecosystem using in situ Hyperspectral remote sensing
    Saluj, Ridhi
    Garg, J. K.
    REMOTE SENSING OF THE OCEANS AND INLAND WATERS: TECHNIQUES, APPLICATIONS, AND CHALLENGES, 2016, 9878
  • [47] Deriving bathymetry and water properties from hyperspectral imagery by spectral matching using a full radiative transfer model
    Gillis, David B.
    Bowles, Jeffrey H.
    Montes, Marcos J.
    Miller, W. David
    REMOTE SENSING LETTERS, 2020, 11 (10) : 903 - 912
  • [48] Classification of Urban Hyperspectral Remote Sensing Imagery Based on Optimized Spectral Angle Mapping
    Yu Liu
    Shan Lu
    Xingtong Lu
    Zheyi Wang
    Chun Chen
    Hongshi He
    Journal of the Indian Society of Remote Sensing, 2019, 47 : 289 - 294
  • [49] A comparison of satellite hyperspectral and multispectral remote sensing imagery for improved classification and mapping of vegetation
    Govender, M.
    Chetty, K.
    Naiken, V.
    Bulcock, H.
    WATER SA, 2008, 34 (02) : 147 - 154
  • [50] ROBUST LINEAR UNMIXING FOR HYPERSPECTRAL REMOTE SENSING IMAGERY BASED ON ENHANCED CONSTRAINT OF CLASSIFICATION
    Chi, Jinxue
    Shen, Xueji
    Yu, Haoyang
    Shang, Xiaodi
    Chanussot, Jocelyn
    Shi, Yimin
    2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 1628 - 1631