Feasibility of hyperspectral remote sensing for mapping benthic macroalgal cover in turbid coastal waters -: a Baltic Sea case study

被引:107
作者
Vahtmäe, E [1 ]
Kutser, T [1 ]
Martin, G [1 ]
Kotta, J [1 ]
机构
[1] Univ Tartu, Estonian Marine Inst, EE-12618 Tallinn, Estonia
关键词
remote sensing; benthic algae; coastal waters; hyperspectral; bio-optical modelling;
D O I
10.1016/j.rse.2006.01.009
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Quantitative analysis of coastal marine benthic communities enables to adequately estimate the state of coastal marine environment, provide better evidence for environmental changes and describe processes that are conditioned by anthropogenic forces. Remote sensing could provide a tool for mapping bottom vegetation if the substrates are spectrally resolvable. We measured reflectance spectra of green (Cladophora glomerata), red (Furcellaria lumbricalis), and brown (Focus vesiculosus) macroalgae and used a bio-optical model in estimating whether these algae distinguish optically from each other, from sandy bottom or deep water in turbid water conditions of the Baltic Sea. The simulation was carried out for three different water types: (I) CDOM-rich coastal water, (2) coastal waters not directly impacted by high CDOM discharge from rivers but with high concentration of cyanobacteria, (3) open Baltic waters. Our modelling results indicate that the reflectance spectra of C. glomerata, F. lumhricalis, F. vesiculosus differ from each other and also from sand and deep water reflectance spectra. The differences are detectable by remote sensing instruments at spectral resolution of 10 nm and SNR better than 1000:1. Thus, the lowest depth limits where the studied macroalgae grow do not exceed the depth where such remote sensing instruments could potentially detect the spectral differences between the studied species. (c) 2006 Elsevier Inc. All rights reserved.
引用
收藏
页码:342 / 351
页数:10
相关论文
共 46 条
[21]   Monitoring cyanobacterial blooms by satellite remote sensing [J].
Kutser, T ;
Metsamaa, L ;
Strömbeck, N ;
Vahtmäe, E .
ESTUARINE COASTAL AND SHELF SCIENCE, 2006, 67 (1-2) :303-312
[22]   Modeling spectral discrimination of Great Barrier Reef benthic communities by remote sensing instruments [J].
Kutser, T ;
Dekker, AG ;
Skirving, W .
LIMNOLOGY AND OCEANOGRAPHY, 2003, 48 (01) :497-510
[23]  
KUTSER T, IN PRESS P EST AC SC
[24]  
KUTSER T, 1997, THESIS U TARTUENSIS
[25]  
KUTSER T, 2002, P OC OPT 17 SANT FE
[26]  
KUTSER T., 2000, P 10 AUSTR REM SENS, P931
[27]   Optical remote sensing of benthic habitats and bathymetry in coastal environments at Lee Stocking Island, Bahamas: A comparative spectral classification approach [J].
Louchard, EM ;
Reid, RP ;
Stephens, FC ;
Davis, CO ;
Leathers, RA ;
Downes, TV .
LIMNOLOGY AND OCEANOGRAPHY, 2003, 48 (01) :511-521
[28]   Spectral signatures of coral reefs: Features from space [J].
Lubin, D ;
Li, W ;
Dustan, P ;
Mazel, CH ;
Stamnes, K .
REMOTE SENSING OF ENVIRONMENT, 2001, 75 (01) :127-137
[29]   PASSIVE REMOTE-SENSING TECHNIQUES FOR MAPPING WATER DEPTH AND BOTTOM FEATURES [J].
LYZENGA, DR .
APPLIED OPTICS, 1978, 17 (03) :379-383
[30]  
Maekivi Sirje, 1996, Proceedings of the Estonian Academy of Sciences Ecology, V6, P108