Applying Artificial Neural Networks and Remote Sensing to Estimate Chlorophyll-a Concentration in Water Body

Author

Wang, Tai-Sheng ; Tan, Chih-Hung ; Chen, Li ; Tsai, Yu-Chu

Author_Institution

Dept. of Civil Eng. & Eng. Inf., Chung Hua Univ., Hsinchu

Volume

1

fYear

2008

fDate

20-22 Dec. 2008

Firstpage

540

Lastpage

544

Abstract

The artificial neural networks (ANNs) were adopted to improve the monitoring capability of water quality in a reservoir using remote sensing images. Simultaneous measurement of chlorophyll-a concentration along the Feitsui reservoir, the primary water supply of Taipei city, was conducted by ferryboat. Those ground measured values were used to calibrate empirical functions with multiple spectral parameters from Landsat 7 satellite images. The predictive capability of ANNs approach was evaluated and showed satisfied results.

Keywords

neural nets; remote sensing; reservoirs; water quality; water supply; Feitsui reservoir; Landsat 7 satellite images; artificial neural networks; chlorophyll-a concentration estimation; empirical functions; multiple spectral parameters; remote sensing images; water body; water quality monitoring capability; water supply; Agricultural engineering; Artificial neural networks; Neural networks; Neurons; Remote monitoring; Remote sensing; Reservoirs; Satellites; Transfer functions; Water resources; Artificial neural networks; Feitsui Reservoir; chlorophyll-a;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3497-8

Type

conf

DOI

10.1109/IITA.2008.279

Filename

4739631