TY - GEN
T1 - Benthic habitat mapping using hyperspectral remote sensing
AU - Vélez-Reyes, Miguel
AU - Goodman, James A.
AU - Castrodad-Carrau, Alexey
AU - Jiménez-Rodriguez, Luis O.
AU - Hunt, Shawn D.
AU - Armstrong, Roy
PY - 2006
Y1 - 2006
N2 - Benthic habitats are the different bottom environments as defined by distinct physical, geochemical, and biological characteristics. Remote sensing is increasingly being used to map and monitor the complex dynamics associated with estuarine and nearshore benthic habitats. Advantages of remote sensing technology include both the qualitative benefits derived from a visual overview, and more importantly, the quantitative abilities for systematic assessment and monitoring. Advancements in instrument capabilities and analysis methods are continuing to expand the accuracy and level of effectiveness of the resulting data products. Hyperspectral sensors in particular are rapidly emerging as a more complete solution, especially for the analysis of subsurface shallow aquatic systems. The spectral detail offered by hyperspectral instruments facilitates significant improvements in the capacity to differentiate and classify benthic habitats. This paper reviews two techniques for mapping shallow coastal ecosystems that both combine the retrieval of water optical properties with a linear unmixing model to obtain classifications of the seafloor. Example output using AVIRIS hyperspectral imagery of Kaneohe Bay, Hawaii is employed to demonstrate the application potential of the two approaches and compare their respective results.
AB - Benthic habitats are the different bottom environments as defined by distinct physical, geochemical, and biological characteristics. Remote sensing is increasingly being used to map and monitor the complex dynamics associated with estuarine and nearshore benthic habitats. Advantages of remote sensing technology include both the qualitative benefits derived from a visual overview, and more importantly, the quantitative abilities for systematic assessment and monitoring. Advancements in instrument capabilities and analysis methods are continuing to expand the accuracy and level of effectiveness of the resulting data products. Hyperspectral sensors in particular are rapidly emerging as a more complete solution, especially for the analysis of subsurface shallow aquatic systems. The spectral detail offered by hyperspectral instruments facilitates significant improvements in the capacity to differentiate and classify benthic habitats. This paper reviews two techniques for mapping shallow coastal ecosystems that both combine the retrieval of water optical properties with a linear unmixing model to obtain classifications of the seafloor. Example output using AVIRIS hyperspectral imagery of Kaneohe Bay, Hawaii is employed to demonstrate the application potential of the two approaches and compare their respective results.
KW - Bathymetry
KW - Benthic habitat mapping
KW - Coastal remote sensing
KW - Hyperspectral imagery
KW - Unmixing
KW - Water optical properties
UR - http://www.scopus.com/inward/record.url?scp=33845660388&partnerID=8YFLogxK
U2 - 10.1117/12.692996
DO - 10.1117/12.692996
M3 - Conference contribution
AN - SCOPUS:33845660388
SN - 0819464554
SN - 9780819464552
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Remote Sensing of the Ocean, Sea Ice, and Large Water Regions 2006
T2 - Remote Sensing of the Ocean, Sea Ice, and Large Water Regions 2006
Y2 - 11 September 2006 through 13 September 2006
ER -