Multi-site evaluation of IKONOS data for classification of tropical coral reef environments

被引:237
|
作者
Andréfouët, S
Kramer, P
Torres-Pulliza, D
Joyce, KE
Hochberg, EJ
Garza-Pérez, R
Mumby, PJ
Riegl, B
Yamano, H
White, WH
Zubia, M
Brock, JC
Phinn, SR
Naseer, A
Hatcher, BG
Muller-Karger, FE
机构
[1] Univ S Florida, Coll Marine Sci, Inst Marine Remote Sensing, 140 7th Ave S, St Petersburg, FL 33701 USA
[2] Univ Miami, Rosenstiel Sch Marine & Atmospher Sci, Miami, FL 33149 USA
[3] US Geol Survey, Ctr Coastal & Reg Marine Studies, St Petersburg, FL USA
[4] Univ Queensland, Dept Geog Sci & Planning, Biophys Remote Sensing Grp, St Lucia, Qld, Australia
[5] Univ Hawaii, Hawaii Inst Marine Biol, Honolulu, HI 96822 USA
[6] IPN, CINVESTAV, Dept Marine Resources, Coral Reef Ecosyst Ecol Lab,Unidad Merida, Merida, Mexico
[7] Univ Exeter, Marine Spatial Ecol Lab, Exeter, Devon, England
[8] Nova SE Univ, Natl Coral Reef Inst, Oceanog Ctr, Miami, FL USA
[9] Natl Inst Environm Studies, Social & Environm Syst Div, Tsukuba, Ibaraki, Japan
[10] Newcastle Univ, Dept Marine Sci & Coastal Management, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England
[11] Univ Polynesie Francaise, Lab Terre Oceans, Tahiti, France
[12] Dalhousie Univ, Dept Biol, Halifax, NS, Canada
关键词
landsat; bathymetric correction; glint; accuracy; habitat mapping; seagrass;
D O I
10.1016/j.rse.2003.04.005
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Ten IKONOS images of different coral reef sites distributed around the world were processed to assess the potential of 4-m resolution multispectral data for coral reef habitat mapping. Complexity of reef environments, established by field observation, ranged from 3 to 15 classes of benthic habitats containing various combinations of sediments, carbonate pavement, seagrass, algae, and corals in different geomorphologic zones (forereef, lagoon, patch reef, reef flats). Processing included corrections for sea surface roughness and bathymetry, unsupervised or supervised classification, and accuracy assessment based on ground-truth data. IKONOS classification results were compared with classified Landsat 7 imagery for simple to moderate complexity of reef habitats (5-11 classes). For both sensors, overall accuracies of the classifications show a general linear trend of decreasing accuracy with increasing habitat complexity. The IKONOS sensor performed better, with a 15-20% improvement in accuracy compared to Landsat. For IKONOS, overall accuracy was 77% for 4-5 classes, 71% for 7-8 classes, 65% in 9-11 classes, and 53% for more than 13 classes. The Landsat classification accuracy was systematically lower, with an average of 56% for 5-10 classes. Within this general trend, inter-site comparisons and specificities demonstrate the benefits of different approaches. Pre-segmentation of the different geomorphologic zones and depth correction provided different advantages in different environments. Our results help guide scientists and managers in applying IKONOS-class data for coral reef mapping applications. (C) 2003 Elsevier Inc. All rights reserved.
引用
收藏
页码:128 / 143
页数:16
相关论文
共 50 条
  • [41] Software development projects in multi-site and multi-cultural environments: A discourse of challenges
    Ifinedo, Princely
    [J]. INFORMATION MANAGEMENT IN THE MODERN ORGANIZATIONS: TRENDS & SOLUTIONS, VOLS 1 AND 2, 2008, : 279 - 288
  • [42] Incorporating multi-event and multi-site data in the calibration of SWMM
    Arriero Shinma, T.
    Ribeiro Reis, L. F.
    [J]. 12TH INTERNATIONAL CONFERENCE ON COMPUTING AND CONTROL FOR THE WATER INDUSTRY, CCWI2013, 2014, 70 : 75 - 84
  • [43] Deep Learning Architecture based Multi Class Coral Reef Image Classification
    Balaji, Adithya
    Yogesh, S.
    Kalyaan, C. K.
    Narayanamoorthi, R.
    Gerard, Dooly
    Dhanalakshmi, Samiappan
    [J]. OCEANS 2023 - LIMERICK, 2023,
  • [44] Multi-Site and Multi-Pollutant Air Quality Data Modeling
    Hu, Min
    Liu, Bin
    Yin, Guosheng
    [J]. SUSTAINABILITY, 2024, 16 (01)
  • [45] Design for the distributed data locator service for multi-site data repositories
    Nakanishi, H.
    Yamanaka, K.
    Tokunaga, S.
    Ozeki, T.
    Homma, Y.
    Ohtsu, H.
    Ishii, Y.
    Nakajima, N.
    Yamamoto, T.
    Emoto, M.
    Ohsuna, M.
    Ito, T.
    Imazu, S.
    Nonomura, M.
    Yoshida, M.
    Ogawa, H.
    Maeno, H.
    Aoyagi, M.
    Yokota, M.
    Inoue, T.
    Nakamura, O.
    Abe, S.
    Urushidani, S.
    [J]. FUSION ENGINEERING AND DESIGN, 2021, 165
  • [46] Linking urban climate classification with an urban energy and water budget model: Multi-site and multi-seasonal evaluation
    Alexander, P. J.
    Bechtel, B.
    Chow, W. T. L.
    Fealy, R.
    Mills, G.
    [J]. URBAN CLIMATE, 2016, 17 : 196 - 215
  • [47] Robust multi-site MR data processing: iterative optimization of bias correction, tissue classification, and registration
    Kim, Eun Young
    Johnson, Hans J.
    [J]. FRONTIERS IN NEUROINFORMATICS, 2013, 7
  • [48] Laser line scan fluorescence and multi-spectral imaging of coral reef environments
    Strand, MP
    Coles, BW
    Nevis, AJ
    Regan, R
    [J]. OCEAN OPTICS XIII, 1997, 2963 : 790 - 795
  • [49] A multi-site verification of the rules suggested by AACC and CAP for evaluation of intralaboratory QC data.
    Plaut, D.
    Duke, J.
    Mitchell, J.
    Rainey, L.
    Tighe, S.
    Westmoreland, P.
    Yamaguchi, A.
    Mazzara, A.
    [J]. CLINICAL CHEMISTRY, 2007, 53 (06) : A204 - A204
  • [50] Re-presenting the Great Barrier Reef to tourists: Implications for tourist experience and evaluation of coral reef environments
    Fenton, DM
    Young, M
    Johnson, VY
    [J]. LEISURE SCIENCES, 1998, 20 (03) : 177 - 192