Total Suspended Sediments Mapping by Using ALOS Imagery Over the Coastal Waters of Langkawi Island, Malaysia
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RESEARCH ARTICLE
Total Suspended Sediments Mapping by Using ALOS Imagery Over the Coastal Waters of Langkawi Island, Malaysia M. Moussavi Alashloo & Hwee-San Lim & Robabeh Asadpour & Sahabeh Safarpour
Received: 1 August 2012 / Accepted: 19 November 2012 # Indian Society of Remote Sensing 2013
Abstract Remote sensing has been extensively used for water delineation and has played an important role in water quality evaluation and environmental management strategies. Suspended sediments are important determinants of water quality in coastal zones. Remote sensing enables the effective monitoring of total suspended sediments (TSS) and the detection of areas with critical water quality issues. This study aims to develop and implement regression models for estimating and mapping TSS concentrations from Advanced Land Observation Satellite (ALOS) images over the coastal waters of Langkawi Island, Malaysia. The algorithm was developed based on the water reflectance model, which is a function of the inherent optical properties of water. Such properties can then be linked to TSS concentration. In this study, an ALOS Advanced Visible and Near Infrared Radiometer type M. M. Alashloo : H. S. Lim : S. Safarpour School of Physics, Universiti Sains Malaysia, 11800 Penang, Malaysia R. Asadpour Faculty of Geoscience and Petroleum Engineering, Universiti Teknologi PETRONAS, Tronoh 31750, Perak, Malaysia M. M. Alashloo (*) No. 6, Bandar U13, Bandar Universiti, 32610 Tronoh, Perak, Malaysia e-mail: [email protected]
2 device was used as the imaging sensor system. Concurrent complementary in-situ water samples were collected within the area coverage of the sensor, and digital numbers (DN) for each band corresponding to the sea-truth locations were determined. The extracted DN values were converted into reflectance values and then regressed with their respective sea-truth data. An algorithm was proposed to obtain the regression coefficient. This algorithm can estimate TSS concentrations with a high correlation coefficient (R2 =0.96) and low root-mean-square error (RMSE=1.98 mg/l). Finally, a map of the TSS concentration was generated by using the proposed algorithm. This study found that TSS mapping can be conducted by using ALOS data over the coastal waters of Langkawi Island, Malaysia. Keywords TSS . ALOS imagery . Langkawi Island . Regression analysis
Introduction As one of the most important natural resources, water serves as the life blood that sustains economic development in any country. With diminishing water resources, water resource protection and environmental management have become essential in sustaining the quality of life on Earth. The quality of surface
J Indian Soc Remote Sens
water in the estuaries of streams, lakes, reservoirs, and oceans is an important indicator of the overall health of the coastal ecosystem. A key factor affecting water quality in coastal waters is the concentration of suspended sediments, which causes non-point source pollution in the area (Guan et al. 2011). Coastal waters are often characterized
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