Inland Water Quality Model Construction and Application for Remote Sensing

Inland Water Quality Model Construction and Application for Remote Sensing

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Seng Chung Yueh
RS & GIS Engineer
Cilix. Corp. Sdn. Bhd.,
Malaysia
Email: [email protected]

Seng Chung Yueh
RS & GIS Engineer
Cilix. Corp. Sdn. Bhd.
Email: [email protected]

Ma Yi
Scientist
First Institute of Oceanography
State Oceanic Administration
Qingdao
China
Email: [email protected]

Lim Boon Leong
RS & GIS Engineer
Cilix. Corp. Sdn. Bhd.
Email: [email protected]

Inbaraj Suppiah
RS & GIS Engineer
Cilix. Corp. Sdn. Bhd.
Email: [email protected]

Roslinah Samad, Research Officer, Macres, Malaysia

Water is one of the most important natural elements on earth. Water quality directly and indirectly influences human lives and development. Conventional water quality monitoring practices depend on extensive field work (in-situ measurements) and laboratory analysis of the water samples. Although these sampling methods may give accurate measurements, they are extremely time consuming and expensive. In this study, remote sensing methods were used to develop a set of algorithms to retrieve water quality parameters from SPOT imagery for Malaysia’s inland water. Tasil Chini (Chini Lake), which is situated in the state of Pahang, was chosen as the study area. In this study, the regression method was applied to the water quality model. Several water quality parameters were tested but only three water quality parameters were used due to the high correlation between field data and satellite imagery. The parameters are Total Suspended Sediment (TSS), Secchi Depth (SD), and Chlorophyll-a. Mean Relative Error (MRE) and Root Mean Square Error (RMSE) were applied in the generated model for model validation. All the models fulfilled the validation requirements.