Share Email Print
cover

Proceedings Paper

High resolution surface sediment type mapping using hyperspectral image and field data in muddy intertidal flat area
Author(s): Dong Zhang; Ying Zhang; Huan Li; Yong Xu
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Mapping surface sediment types is particularly challenging in muddy intertidal flat area due to muddy characteristics and tidal fluctuation. With the combination of Hyperion hyperspectral image and field survey data, two regression based image interpretation methods, namely characteristic band method (CBM) and band differential method (BDM), were used for sediment type classification and mapping. It was found that under low tidal level there was a strong correlation between surface sediment reflectance and its sand, silt and clay contents in shortwave infrared band. For 2102nm wavelength, the correlation coefficient by former method reached -0.8954, 0.9070 and 0.6547 respectively while the latter method had a relatively lower correlation capability. So choosing this band as the characteristic band, three linear regression models were constructed and the sand, silt and clay contents were quantitatively inversed from their corresponding reflectance values. A linear equilibrium corrective method was then applied to some "bad" pixels for inversed contents amendment due to regression model's linear transforming limitation. Based on these corrected component contents, Shepard triangular classification method was adopted and the sediment types for the whole intertidal flat were automatically obtained with a high interpretation precision of 87.9%. Results showed that the hyperspectral remote sensing reversion method could be well utilized for dynamic monitoring and analyzing of the depositional environment changes in muddy intertidal flat region.

Paper Details

Date Published: 7 November 2008
PDF: 11 pages
Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71471C (7 November 2008); doi: 10.1117/12.813249
Show Author Affiliations
Dong Zhang, Nanjing Normal Univ. (China)
Ying Zhang, Nanjing Normal Univ. (China)
Huan Li, Nanjing Normal Univ. (China)
Yong Xu, Nanjing Normal Univ. (China)


Published in SPIE Proceedings Vol. 7147:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang, Editor(s)

© SPIE. Terms of Use
Back to Top