Reflectance Interpretation of ALOS AVNIR-2 Satellite Data for Ocean Monitoring by Means of Principal Component Analysis

Physical sea surface parameters such as irradiance reflectance are most commonly used in ocean color remote sensing. Algorithms are developed to relate irradiance reflectance (R) and quantities such as chlorophyll and suspended sediment concentration. The study interpreted how many independent parameters of ALOS satellite data collected can be found to assess the sediment concentration in Langkawi Island, Malaysia by using principal component analysis (PCA). PCA is a technique designed for reducing the dimensionality of multivariate set of data. This method can reduce the variables which are highly correlated with one another without losing any information. In order to extract the reflectance quantities, all satellite data sets have been atmospherically corrected using ATCOR-2. PCA and band ratios were applied on the four independent bands (band 1-4). The result from independent band show that the PC(1)and PC(2)composed mostly of band 2(R-AV2) and band 3 (R-AV3) reflectances, while the band ratios show that the PC1, PC2 and PC3 composed mostly of all band ratios. In this study, the both components PC1 and PC2 can be considered strong in interpreted the structure of the data of independent band, due to it can explain 98.45 percent of the diversity of data. On the other hand, PC1, PC2 and PC3 can be considered strong in interpreted the structure of the data of band ratios. As a result, multivariate model from band ratios gives adequate relationship between the PC1, PC2 and PC3 against suspended sediment concentrations (SSC) with equation: SSC [mg.L-1] = 89.4 - 1.78PC(1) - 7.33 PC2 - 90.6PC(3) (SE=6.6, R-2=0.94.6).