• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.1
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• pp.27-33
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• 2001

SDD(Secchi disk depth) algorithm were composed of SeaWiFS bands combination using in-water optical data sets obtained Lake Sihwa, Kyungki Bay, Chunsu Bay, and Chinhae Bay. SDD algorithm were compared with in-situ data. Reflectance band ratio, $R_{rs}$(490/665) had the highest correlation($R^2$=0.8188) with in-situ data. For in-water algorithm applied to satellite data, reflectance band ratios of Landsat TM data were calculated. However, the results of applied Landsat TM had the low correlation, these reason were discussed in this paper.

• 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.2
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• pp.59-68
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• 1999

The study for detecting suspended sediment distribution in Lake Sihwa, which has a large surface area and coastal area, using remote sensing technique was carried out with development of satellite data collected since 1970. The research, however, analysis of spatial distribution and quantity, is not common in domestic study and useful algorithms have not been proposed. In this study, a suspended sediment algorithm was composed with in-situ data obtained in study area and remote sensing reflectance obtained in-water optical instrument, which has SeaWiFS wavelength bands. However, when the algorithm was applied to Landsat TM data, including an in-situ data set, and some problems arose. The composition of the algorithm which was structured with band difference and band ratio showed the correlation of $R^2$=0.7649 with concentration of suspended sediments. And, between calculated and observed concentration of suspended sediments there was a correlation of $R^2$=0.6959. However, remote sensing reflectance obtained from Landsat TM is not good for the estimation of concentration of suspended sediments, because of high concentration of chlorophyll and CDOM(colored dissolved organic matter).

• Korean Journal of Remote Sensing
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• v.16 no.1
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• pp.37-45
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• 2000

Since being launched for ocean observing in 1997, the SeaWiFS sensor has supplied data on ocean chlorophyll distribution and environmental conditions of the atmosphere. Until now, a lot of SeaWiFS data have been archived and utilized for ocean monitoring and land observation. The SeaWiFS sensor has 1km spatial resolution, therefore, it is difficult to obtain data at the coastal zone. Since atmospheric correction algorithms at the coastal area have not been confirmed for chlorophyll algorithm, the ocean color data analysis for coastal zone is not common. In particular, domestic coastal areas have high suspended sediments concentrations and higher absorption influence of colored dissolved organic matter (CDOM), released from in-land, than open-sea. Thus, a useful algorithm for analysis of chlorophyll distribution in domestic coastal areas has not been developed. In this study, empirical algorithms, using data from the ocean color sensor, were developed for monitoring of chlorophyll distribution of coastal areas. In the process of the development of the algorithms, we can find that the red band (665nm) should be used for analyzing of domestic coastal areas near the Yellow Sea.