Share Email Print

Proceedings Paper

Potential of hyperspectral imaging to assess the stability of mudflat surfaces by mapping sediment characteristics
Author(s): Geoff Smith; Andrew Thomson; Iris Moller; Jacco Kromkamp
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

This work assessed the suitability of hyperspectral data for estimating mudflat surface characteristics related to stability. Due to the inaccessibility of intertidal areas, precise ground-based measurements of mudflat stability are difficult to conduct. Remote sensing can provide full spatial coverage and non-intrusive measurement. As stability changes on mudflats are linked to subtle differences in mudflat surface characteristics, they can potentially be mapped by hyperspectral data. Hyperspectral images were collected along with near contemporary ground measurements. An unsupervised classification gave a map which confirmed that a channel bar was mainly sand whereas soft mud dominated an adjacent embayment. Multiple regression analysis was used to relate surface characteristics to hyperspectral data to construct regression equations. Erosion shear stress was estimated directly from the hyperspectral data and also by a relationship with the surface characteristics. The results of the thematic class map matched well with the known situation at the site during image acquisition. The maps of surface characteristics highlighted the additional information that can be extracted from hyperspectral data. Stability maps, based on the erosion shear stress, can be used as a basis for predicting the likely future behaviour in this dynamic environment and will be of use for coastal zone management.

Paper Details

Date Published: 14 March 2003
PDF: 12 pages
Proc. SPIE 4886, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology II, (14 March 2003); doi: 10.1117/12.463119
Show Author Affiliations
Geoff Smith, Ctr. for Ecology and Hydrology, Monks Wood (United States)
Andrew Thomson, Ctr. for Ecology and Hydrology, Monks Wood (United States)
Iris Moller, Univ. of Cambridge (United States)
Jacco Kromkamp, NIOO-CEMO (United States)

Published in SPIE Proceedings Vol. 4886:
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology II
Manfred Ehlers, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?