An integrated field and remote sensing approach for mapping seagrass cover, Moreton Bay, Australia

Roelfsema, C. M., Phinn, S. R., Udy, N. and Maxwell, P. (2009) An integrated field and remote sensing approach for mapping seagrass cover, Moreton Bay, Australia. Journal of Spatial Science, 54 1: 45-62. doi:10.1080/14498596.2009.9635166

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Author Roelfsema, C. M.
Phinn, S. R.
Udy, N.
Maxwell, P.
Title An integrated field and remote sensing approach for mapping seagrass cover, Moreton Bay, Australia
Journal name Journal of Spatial Science   Check publisher's open access policy
ISSN 0005-0326
Publication date 2009-06
Year available 2009
Sub-type Article (original research)
DOI 10.1080/14498596.2009.9635166
Volume 54
Issue 1
Start page 45
End page 62
Total pages 18
Editor Eugene Browne
Ken Alexander
Place of publication Singapore, Singapore
Publisher Taylor & Francis Asia Pacific
Collection year 2010
Language eng
Subject C1
0909 Geomatic Engineering
Formatted abstract
Creating accurate maps of seagrass cover is a challenging procedure in coastal waters with variable water clarity and depths. This paper presents an approach for mapping seagrass cover from data sources commonly collected by natural resource management agencies responsible for coastal environments. The aim of the study was to develop an approach for mapping classes of seagrass cover from field and/or image data for an area with variable water clarity and depths. The study was carried out in Moreton Bay in eastern Australia. A Landsat 5 Thematic Mapper satellite image was acquired for the same area in August 2004. The image data were used to map seagrass cover in the exposed inter‐tidal and clear shallow water areas to depths of 3 m. Field survey data were collected, in July – August 2004, to map deep (> 3 m) and turbid sub‐tidal areas, using: real time video, snorkeller observations and transect surveys . The resulting maps were combined into a single layer of polygons, with the same seagrass cover classes used as existing mapping programs and with each polygon assigned to one of five cover classes (0 %, 1–25 %, 25–50 %, 50–75 %, 75–100 %). As independent field data were not available for accuracy assessment, a reliability assessment indicated that > 75 percent of the Bay was mapped with high categorical reliability. Most previously published seagrass mapping projects covered areas < 400 km2, were based on single data sets, and lacked assessment of accuracy or reliability. Our approach and methods address this gap and present guidelines for a generally applicable method to integrate image and field data sets over large areas (> 1000 km2) commonly used for monitoring and management.
Keyword Seagrass cover
Marine protected area
Landsat thematic mapper
Benthic surveys
Integrated field-image mapping
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

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Created: Thu, 03 Sep 2009, 07:45:46 EST by Mr Andrew Martlew on behalf of Centre for Marine Studies