M Moussavi Alashloo - School of Physics, Universiti Sains Malaysia, ۱۱۸۰۰ Penang, Malaysia
S.Y Moussavi Alashloo - Department of Geosciences, Universiti Teknologi PETRONAS, ۳۲۶۱۰ Seri Iskandar, Perak Malaysia
Lim Hwee San - School of Physics, Universiti Sains Malaysia, ۱۱۸۰۰ Penang, Malaysia

Remote sensing method is a powerful tool for water quality monitoring and modeling via analyzing satellite images of a widespread area. This study presents the development of regression models for estimating and mapping concentrations of total suspended sediment (TSS) over the coastal waters of Langkawi Island, Malaysia from Advanced Land Observation Satellite (ALOS) images. Two ALOS images and nearly contemporaneous in situ measurements of TSS were utilized. The digital numbers for each visible band corresponds to the sea-truth positions were identified and were transformed into reflectance values. The relationships were investigated between TSS concentrations and reflectance of ALOS bands. The non-linear relationship between in-situ TSS and reflectance combinations of the three visible bands demonstrated the highest correlation with a low root-mean-square error (RMSE ≈ ۳.۵۲mg/l) and high correlation coefficient (R۲ = ۰.۹۱). The results confirm that the proposed algorithm obtained from ALOS data is successful for TSS mapping of the coastal waters of Langkawi Island, Malaysia.

ALOS imagery; Remote sensing; Langkawi Island; TSS; Suspended sediment