• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.1
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• pp.18-26
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• 2001

Landsat TM band ratio algorithms were made by in-water optical measurement data of each sampling points for water quality monitoring of coastal area using Landsat TM satellite data. The algorithm was derived from in-water optical reflectance data which was measuring by the PRR(profiling reflectance radiometer). And, in-water optical reflectance data were applied to Landsat TM bands. Relationship between in-water optical reflectance and pigments proposed by the ratio of TM band 1 and band 2 showed to as follows; $Y=3.8352{\times}(R(band\;1)/R(band\;2))^{-2.1978}$ ($R^2$=0.7069) and, relationship of the ratio of TM band 1 and band 3 as follows; $Y=23.288{\times}(R(band\;1)/R(band\;3))^{-1.5243}$ ($R^2$=0.8062). Calculated the upwelling radiance of water surface and radiance of TM showed the ratio of atmospheric effect. In the coastal area Rayleigh and Mie scattering of atmosphere is to make over 80% of normalized radiance of Landsat TM. In order to apply in-water algorithm obtained by PRR, we had to calculate the atmospheric effects at sampling site. And, the quantitative analysis of in-water components using Landsat TM data need the calibration of in-water algorithm and effective method of atmospheric correction.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.3
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• pp.71-80
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• 1999

The aim of the present study is to define and tentatively to interpret the distribution of polluted water released from Lake Sihwa into the Yellow Sea using Landsat TM. Since the region is an extreme Case 2 water, empirical algorithms for detecting concentration of chlorophyll-a and suspended sediments have limitations. This work focuses on the use of multi-temporal Landsat TM data. We applied PCA to detect evolution of spatial feature of polluted water after release from the lake Sihwa. The PCA results were compared with in situ data, such as chlorophyll-a, suspended sediments, Secchi disk depth(SDD), surface temperature, remote sensing reflectance at six channel of SeaWiFS. Also, the in situ remote sensing reflectance obtained by PRR-600(Profiling Reflectance Radiometer) was compared with PCA results of Landsat TM data sets to find good correlation between first Principal Component and Secchi disk depth($R^2$=0.7631), although other variables did not result in such a good correlation. Therefore, Problems in applying PCA techniques to multi-spectral remotely sensed data were also discussed in this paper.