Influence of atmospheric correction and number of sampling points on the accuracy of water clarity assessment using remote sensing application

The main objectives of the research described in this paper are to assess the influence of atmospheric correction and the number of sampling points on the accuracy of lake water clarity using remote sensing. For this purpose field experiments were carried out at Bung Boraphet – the largest fresh water lake in Central Thailand. Two clarity parameters, secchi disk transparency (SDT), at 80 locations for three events on April 15th 2008 and March 24th and 31st 2009, and suspended sediment concentration (SSC) for the last two events were collected. These field data were collected nearly contemporaneous or contemporaneous to three Landsat 5 TM images, which were acquired on April 13th 2008 and March 24th and 31st 2009, respectively. Digital numbers of the Thematic Mapper (TM) image bands were transformed to at-sensor radiance by a radiometric correction process and then atmospheric correction was made using the Second Simulation of Satellite Signal in the Solar Spectrum (6S) code to acquire the surface reflectance. Linear regression equations between the log-transformed of clarity parameters and surface reflectance of each band and their band ratios at the same pixels were then determined. The band combinations TM1/TM3 and TM1 to estimate ln(SDT), and TM3/TM1 and TM1 to determine ln(SSC) for all satellite images were selected. These equations were later used to estimate the SDT and SSC values distributed across the whole lake. The results showed that lake wide average values of SDT for the three images are approximately 37, 97 and 81cm, respectively, while the values of SSC for the second and third images are around 11 and 13mg/l, respectively. The application of atmospheric correction to the TM data has proved to have the effect on the average values of SDT and SSC, and especially on their maximum and minimum values. Finally, it is possible to reduce the ground observation data of SDT and SSC substantially and still obtain reliable empirical relationships for the estimation of lake wide SDT and SSC values from TM data within the lake.