Modelling coral reef habitat trajectories:: Evaluation of an integrated timed automata and remote sensing approach

被引:18
|
作者
Scopelitis, Julie
Andrefouet, Serge
Largouet, Christine
机构
[1] IRD, Noumea 98848, New Caledonia
[2] UNC, Noumea 98851, New Caledonia
基金
美国国家航空航天局;
关键词
Abore reef; New Caledonia; phase-shift; strategy-shift; hurricane; coral bleaching; Acanthaster; disturbance; ecological trajectories; IKONOS; quickbird;
D O I
10.1016/j.ecolmodel.2007.02.011
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The rapid degradation of many reefs worldwide calls for more effective monitoring and predictions of the trajectories of coral reef habitats as they cross cycles of disturbance and recovery. Current approaches include in situ monitoring, computer modelling, and remote sensing observations. We aimed to combine these three sources of information for Abore Reef in New Caledonia by using: (1) a generic timed automata model of reef habitat trajectories, (2) two high spatial resolution multispectral images acquired before and after hurricane Erika in a 2-year interval (March, 2003), and (3) extensive field data on Abore's benthic community structure. Field and remote sensing observations were used to verify model predictions of habitat evolution during the 2-year interval. We also tested whether a fairly generic model of habitat evolution can be used to flag local incorrect image change detection interpretation. The automaton manipulates objects such as states, transitions and clocks (transition times), and we found that it is possible, with expert knowledge, to describe complex habitat trajectories with this formalism. On Abore Reef, we analyzed 22 heterogeneous polygons mapped before and after hurricane Erika using a 36 habitat typology. We examined 75 trajectories suggested by the before-after image classifications and critically reviewed the benefits of the combined timed automata model-image approach. The Abore Reef case study confirms that this is a fruitful path to maximize the benefits of both tools, and minimize their respective drawbacks. However, we conclude that timed automata and remote sensing analysis need to be locally optimized to achieve useful results, and suggests further improvements by using hybrid models able to manipulate continuous, and fuzzy, properties. (c) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:59 / 80
页数:22
相关论文
共 50 条
  • [1] Reef Cover, a coral reef classification for global habitat mapping from remote sensing
    Emma V. Kennedy
    Chris M. Roelfsema
    Mitchell B. Lyons
    Eva M. Kovacs
    Rodney Borrego-Acevedo
    Meredith Roe
    Stuart R. Phinn
    Kirk Larsen
    Nicholas J. Murray
    Doddy Yuwono
    Jeremy Wolff
    Paul Tudman
    Scientific Data, 8
  • [2] Modelling coral reef biodiversity and habitat destruction
    Stone, L
    Eilam, E
    Abelson, A
    Ilan, M
    MARINE ECOLOGY PROGRESS SERIES, 1996, 134 (1-3) : 299 - 302
  • [3] Coral reef habitat mapping: how much detail can remote sensing provide?
    P. J. Mumby
    E. P. Green
    A. J. Edwards
    C. D. Clark
    Marine Biology, 1997, 130 : 193 - 202
  • [4] Coral reef habitat discrimination using multivariate spectral analysis and satellite remote sensing
    Call, KA
    Hardy, JT
    Wallin, DO
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2003, 24 (13) : 2627 - 2639
  • [5] Progress of the study on coral reef remote sensing
    Huang R.
    Yu K.
    Wang Y.
    Liu J.
    Zhang H.
    Yaogan Xuebao/Journal of Remote Sensing, 2019, 23 (06): : 1091 - 1112
  • [6] Coral reef habitat-mapping: how much detail can remote sensing provide?
    Mumby, PJ
    Green, EP
    Edwards, AJ
    Clark, CD
    MARINE BIOLOGY, 1997, 130 (02) : 193 - 202
  • [7] Reef Cover, a coral reef classification for global habitat mapping from remote sensing (vol 8, 196, 2021)
    Kennedy, Emma V.
    Roelfsema, Chris M.
    Lyons, Mitchell B.
    Kovacs, Eva M.
    Borrego-Acevedo, Rodney
    Roe, Meredith
    Phinn, Stuart R.
    Larsen, Kirk
    Murray, Nicholas J.
    Yuwono, Doddy
    Wolff, Jeremy
    Tudman, Paul
    SCIENTIFIC DATA, 2021, 8 (01)
  • [8] A remote sensing model for coral recruitment habitat
    Radford, Ben
    Puotinen, Marji
    Sahin, Defne
    Boutros, Nader
    Wyatt, Mathew
    Gilmour, James
    REMOTE SENSING OF ENVIRONMENT, 2024, 311
  • [9] Autonomous Coral Reef Survey in Support of Remote Sensing
    Ackleson, Steven G.
    Smith, Joseph P.
    Rodriguez, Luis M.
    Moses, Wesley J.
    Russell, Brandon J.
    FRONTIERS IN MARINE SCIENCE, 2017, 4
  • [10] Spectral reflectance of coral reef bottom-types worldwide and implications for coral reef remote sensing
    Hochberg, EJ
    Atkinson, MJ
    Andréfouët, S
    REMOTE SENSING OF ENVIRONMENT, 2003, 85 (02) : 159 - 173