APPLICATION OF REMOTE SENSING FOR ADJUSTMENT AND CALIBRATION OF WATER QUALITY MODEL - Integrating GIS, Remote Sensing, and Mathematical Modelling for Surface Water Quality Management - page 180

processing steps to convert digital values (DN) of the SPOT satellite images to water quality variables.
Figure (8-26) s hows the raw SPOT scene.
Figure (8-26): SPOT-5 full scene.
SPOT images are delivered in digital numbers format, and the initial step in processing these images is
to convert the digital numbers into radiance, then to convert the radiance into at surface reflectance.
The first conversion is simple linear transformation using sensor-dependent parameters, and the
second conversion was done for atmospheric correction applying radiative transfer algorithms. The
atmospheric correction of the image was done using the ENVI's Fast Line-of-sight Atmospheric
Analysis of Spectral Hypercubes (FLAASH) module. The detailed procedures for atmospheric
correction are explained in Appendix (A-2). The atmospheric correction is an important image
calibration process to remove the effects of aerosols and water vapour effects. The atmospherically
corrected image was then resized to the main lake area; Figure (8-27) shows the atmospherically
corrected resized image of the lake area.
Figure (8-27): The atmospherically corrected resized SPOT image of the lake area.
The next step in the image processing was masking out of the open water body from the image taking
separating it from the mixed pixels including water, floating and submerged vegetation in the lake.
This was done using unsupervised classification. In this way the water pixels were differentiated from
the other pixels. An unsupervised classification was applied using the SPOT band 3 (NIR) image