Environmental Monitoring and Assessment

, Volume 148, Issue 1–4, pp 255–264 | Cite as

Application of MODIS satellite data in monitoring water quality parameters of Chaohu Lake in China

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Abstract

This study aims to apply Moderate Resolution Imaging Spectroradiometer (MODIS Data) to monitor water quality parameters including chlorophyll-a, secchi disk depth, total phosphorus and total nitrogen at Chaohu Lake. In this paper, multivariate regression analysis, Back Propagation neural networks (BPs), Radial Basis Function neural networks (RBFs) and Genetic Algorithms-Back Propagation (GA-BP) were applied to investigate the relationships between water quality parameters and the MODIS bands combinations. The study results indicated that a simple, efficient and acceptable model could be established through multivariate regression analysis, but the model precision was relatively low. In comparison, BPs, RBFs and GA-BP were significantly advantageous in terms of sufficient utilization of spectra information and model reliance. The relative errors of BPs, RBFs and GA-BP were below 35%. Based on method comparison, it can be concluded that GA-BP is more suitable for simulation and prediction of water quality parameters by applying genetic algorithm to optimize the weight value of BP network. This study demonstrates that MODIS data can be applied for monitoring some of the water quality parameters of large inland lakes.

Keywords

Water quality parameters Combined bands BPs RBFs GA-BP 
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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.MOE Laboratory for Surface Processes, College of Environmental SciencesPeking UniversityBeijingPeople’s Republic of China

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