Information extraction of suspended sediment's relative density and distribution change in Lake Chaohu based on Landsat TM/ETM+ data

Xinyuan Wang; Changqing Mei; Wenda Li; Xihui Zhang

doi:10.1117/12.760705

26 July 2007 Information extraction of suspended sediment's relative density and distribution change in Lake Chaohu based on Landsat TM/ETM+ data

Xinyuan Wang, Changqing Mei, Wenda Li, Xihui Zhang

Author Affiliations +

Proceedings Volume 6752, Geoinformatics 2007: Remotely Sensed Data and Information; 67521R (2007) https://doi.org/10.1117/12.760705
Event: Geoinformatics 2007, 2007, Nanjing, China

Abstract

Suspended sediment is one of the most important parameters for water quality. Numerous experiential or deductive models have been advanced for detecting suspended sediment using remote sensing technology. However, due to the lack of atmospheric parameters and sufficient statistics, the precision or accuracy of these models cannot be guaranteed. In this paper, we take Lake Chaohu as an example area and process its TM/ETM+ data by applying the method of internal average relative reflectance for atmospheric correction and by extracting sediment information according to the value of SI (SI=(TM2+TM3)/(TM2/TM3)). The results show that: (1) an accurate extraction of water information of Lake Chaohu can be obtained by considering the relationship between the spectrums, (2) the data of relative suspended sediment revealed are in accordance with the instrumental data in situ, (3) the high-density suspended sediment area has expanded 1.5 times during the past 13 years, indicating changes of the lake's estuary, shoreline, and its suspended sediment content, and (4) the main sources of suspended sediment of Lake Chaohu are river transportation and erosion of the lakeshore.

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Xinyuan Wang, Changqing Mei, Wenda Li, and Xihui Zhang "Information extraction of suspended sediment's relative density and distribution change in Lake Chaohu based on Landsat TM/ETM+ data", Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 67521R (26 July 2007); https://doi.org/10.1117/12.760705

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KEYWORDS

Atmospheric modeling

Remote sensing

Mouth

Data modeling

Aerosols

Earth observing sensors

Landsat

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