Retrospective seagrass change detection in a shallow coastal tidal Australian lake

Satellite imagery was used to detect the change in seagrass and macroalgal communities of a shallow coastal lake over a period of 14 years. The lake benthic material was classified into sets of spectral classes representing the patterns and texture of the ecosystem, and then linked to environmentally relevant labels through a radiative transfer model. The classification results for 2002 achieved an accuracy of 76% for the least understood areas; other areas were significantly better, but not quantified. Classification results of 1988, 1991, and 1995 were consistent with past surveys and maps. Based on the change detection from 1988 to 2002 Posidonia, Ruppia and Halophila change slightly in the 14 year period from 1988 to 2002. However, Zostera has undergone significant change and adaptation. Early in the time series (between 1988 and 1991) a reduction in Zostera beds was evident, especially in the middle and south of the lake with some areas not returning by 2002. Epiphytic growth over Zostera could be a confounding factor here, but the Landsat sensors do not have sufficient spectral resolution to detect these subtleties. Hyperspectral remote sensing could resolve this issue more clearly.

[1]  André Morel,et al.  Diffuse reflectance of oceanic shallow waters: influence of water depth and bottom albedo , 1994 .

[2]  M. Rasheed,et al.  Monitoring Seagrasses in Tropical Ports and Harbours , 1996 .

[3]  Karl Korfmacher,et al.  Remote sensing and GIS analysis of seagrass meadows in North Carolina, USA , 1997 .

[4]  R. Congalton,et al.  A Quantitative Comparison of Change-Detection Algorithms for Monitoring Eelgrass from Remotely Sensed Data , 1998 .

[5]  Vittorio E. Brando,et al.  Imaging Spectrometry of Water , 2002 .

[6]  Vittorio E. Brando,et al.  Satellite hyperspectral remote sensing for estimating estuarine and coastal water quality , 2003, IEEE Trans. Geosci. Remote. Sens..

[7]  Vittorio E. Brando,et al.  Remote Sensing of Seagrass Ecosystems: Use of Spaceborne and Airborne Sensors , 2007 .

[8]  M. Perry,et al.  Modeling in situ phytoplankton absorption from total absorption spectra in productive inland marine waters , 1989 .

[9]  F. Short,et al.  Global seagrass research methods , 2001 .

[10]  H. Ben Moussa,et al.  Télédétection des algues macrophytes de I'Archipel de Molene (France) Radiometrie de terrain et application aux donnees du satellite SPOT , 1989 .

[11]  Arnold G. Dekker,et al.  A methodology for retrieval of environmental noise equivalent spectra applied to four Hyperion scenes of the same tropical coral reef , 2004 .

[12]  A. Vodacek,et al.  Laser-induced fluorescence: Limits to the remote detection of hydrogen ion, aluminum, and dissolved organic matter☆ , 1989 .

[13]  C. Mobley Light and Water: Radiative Transfer in Natural Waters , 1994 .

[14]  A. Cracknell Remote sensing techniques in estuaries and coastal zones an update , 1999 .

[15]  I. S. Robinson,et al.  Monitoring marine ecological changes on the east coast of Bahrain with Landsat TM , 1993 .

[16]  G. Kendrick,et al.  Changes in seagrass cover on Success and Parmelia Banks, Western Australia between 1965 and 1995 , 2000 .

[17]  M. Liceaga-Correa,et al.  Assessment of coral reef bathymetric mapping using visible Landsat Thematic Mapper data , 2002 .

[18]  Chris D. Clark,et al.  Coral reef habitat mapping: how much detail can remote sensing provide? , 1997 .

[19]  John Parslow,et al.  Optical properties of waters in the Australasian sector of the Southern Ocean , 2001 .

[20]  David C. Douglas,et al.  Distribution and stability of eelgrass beds at Izembek Lagoon, Alaska , 1997 .

[21]  S. Fyfe,et al.  Spatial and temporal variation in spectral reflectance: Are seagrass species spectrally distinct? , 2003 .

[22]  G. Kendrick,et al.  Chapter 10 – Assessing biomass, assemblage structure and productivity of algal epiphytes on seagrasses , 2001 .

[23]  J. G. Norris,et al.  Estimating basal area coverage of subtidal seagrass beds using underwater videography , 1997 .

[24]  B. Osborne,et al.  Light and Photosynthesis in Aquatic Ecosystems. , 1985 .

[25]  Xiaoyang Zhang,et al.  On the estimation of biomass of submerged vegetation using Landsat thematic mapper (TM) imagery: A case study of the Honghu Lake, PR China , 1998 .

[26]  H. Kirkman,et al.  Baseline and Monitoring Methods for Seagrass Meadows , 1996 .

[27]  S. M. de Jong,et al.  Imaging spectrometry : basic principles and prospective applications , 2001 .

[28]  Wei Li,et al.  Spectral Signatures of Coral Reefs: Features from Space , 2001 .

[29]  E. Fry,et al.  Absorption spectrum (380-700 nm) of pure water. II. Integrating cavity measurements. , 1997, Applied optics.

[30]  L. Yarbro,et al.  Mass mortality of the tropical seagrass Thalassia testudinum in Florida Bay (USA) , 1991 .

[31]  R. Manière,et al.  Cartographie des biocénoses marines de Guadeloupe à partir de données SPOT (récifs coralliens, phanérogames marines, mangroves) , 2001 .

[32]  A. Dekker,et al.  The use of the Thematic Mapper for the analysis of eutrophic lakes: a case study in the Netherlands. , 1993 .

[33]  C. Duarte,et al.  European seagrasses: an introduction to monitoring and management , 2004 .

[34]  R. Bukata,et al.  Optical Properties and Remote Sensing of Inland and Coastal Waters , 1995 .

[35]  A. Mccomb,et al.  Decline of seagrasses , 1989 .

[36]  Steven G. Ackleson,et al.  Remote sensing of submerged aquatic vegetation in lower chesapeake bay: A comparison of Landsat MSS to TM imagery , 1987 .

[37]  P. Mumby,et al.  The cost-effectiveness of remote sensing for tropical coastal resources assessment and management , 1999 .

[38]  Chapter 14 – Measuring invertebrate grazing on seagrasses and epiphytes , 2001 .