DocumentCode
3317362
Title
Effect of spatial and spectral resolution of images on interpreting intertidal estuarine sediment grain size distributions
Author
Huang, Haijun ; Liu, Yanxia ; Wang, Bo
Author_Institution
Key Lab. of Marine Geol. & Environ., Chinese Acad. of Sci., Qingdao, China
fYear
2010
fDate
25-30 July 2010
Firstpage
13
Lastpage
16
Abstract
In this paper, multi- and hyper- spectral images were employed to evaluate the capacity of retrieving grain size of tidal flat sediment from space-borne remote sensing data by analyzing in situ spectral signatures and grain size parameters. The results show that the mean absolute error (MAE) of medium grain size retrieved from HJ-1A hyperspectral in wet tidal flat with a moisture content of 18-43% is 0.0036. In dry tidal flat, the MAE of medium grain size retrieved from Landsat ETM and HJ-1A images are 0.031 and 0.026 respectively. Landsat MSS can stinguish sediment types of FS, TS and ST. Contrastive analysis of three kind of images, Landsat MSS is effective in historic period large scale dry tidal flat, and HJ-1A image has high precision in recent year´s wet tidal flat sediment types.
Keywords
geophysical techniques; grain size; image resolution; oceanography; remote sensing; sediments; HJ-1A hyperspectral imagery; Landsat ETM imagery; Landsat MSS; contrastive analysis; grain size distributions; hyperspectral images; intertidal estuarine sediments; mean absolute error; medium grain size; moisture content; multispectral images; sediment types; space-borne remote sensing; tidal flat sediment; wet tidal flat; Earth; Grain size; Hyperspectral imaging; Reflectivity; Satellites; Sediments; HJ-1A; Medium grain size; Moisture content; Multi-spectral image; tidal flat sediment;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location
Honolulu, HI
ISSN
2153-6996
Print_ISBN
978-1-4244-9565-8
Electronic_ISBN
2153-6996
Type
conf
DOI
10.1109/IGARSS.2010.5650511
Filename
5650511
Link To Document