Study of retrieving models for chlorophyll-a concentration based on classification of above-water remote sensing reflectance

Author

Xu, Xin ; Li, Yunmei ; Lv, Heng ; Tan, Jing ; Guo, Yulong ; Huang, Jiazhu

Author_Institution

Key Lab. of Virtual Geographic Environ. of Educ. Minist., Nanjing Normal Univ., Nanjing, China

fYear

2011

fDate

24-26 June 2011

Firstpage

1609

Lastpage

1613

Abstract

In this study, according to the characteristics of above-water remote sensing reflectance (Rrs) curves, we put our samples into different classes, and for each class, find a best retrieving model among the first-derivative model, band ratio model and three-band model to show the correlation between Rrs data and the concentration of chlorophyll-a. As a result, it is proved that Rrs curves can be classified into 6 classes by differences in peaks around the wavelength of 560nm or 705nm, as well as valleys around the wavelength of 630nm or 680nm. Compared with non-classified retrieving models based on the whole data set, classified models reduce the absolute value of average relative error (RE) range from 7.39% to 39.85%, effectively improve the retrieving precision.

Keywords

hydrological techniques; ocean chemistry; oceanographic techniques; organic compounds; reflectivity; remote sensing; underwater optics; water quality; above water remote sensing reflectance classification; band ratio model; chlorophyll-a concentration retrieval models; first derivative model; remote sensing reflectance curves; three band model; wavelength 560 nm; wavelength 630 nm; wavelength 680 nm; wavelength 705 nm; Data models; Estimation; Hyperspectral sensors; Lakes; Reflectivity; Variable speed drives; Lake Taihu; chlorophyll-a concentration; classification; remote sensing reflectance; retrieving models;

fLanguage

English

Publisher

ieee

Conference_Titel

Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-9172-8

Type

conf

DOI

10.1109/RSETE.2011.5964596

Filename

5964596