• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.224-232
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• 2006

This study investigates to detect Sea Surface Temperature (SST) and land cover change after tide embankment construction using Landsat Thematic Mapper (TM) Thermal Infrared (TIR) band data at Shihwa Lake and surrounding area. SST measurement is important for studies of both the structure of the ocean and as the thermal boundary between the ocean and the atmosphere. Since 1970s, the derivation of SST by satellite remote sensing (RS) has been applied to earth surface using Advanced Very High Resolution Radiometer (AVHRR) and Landsat TM. However, AVHRR has restriction in deriving SST in the area whose shoreline is complicated like western coast in South Korea because of coarse spatial resolution. The TIR band of TM images can be used to detect SST change whose shoreline is complicated and narrow like the study site. Thus, multi-temporal TM images were used for SST change detection in this study.

• 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.

• Economic and Environmental Geology
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• v.28 no.4
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• pp.405-414
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• 1995

An algorithm for monitoring geomorphological change using remote sensing data is investigated and tested using two LANDSAT TM data sets acquired over the Kyunggi Bay on April 15 1986 and September 22 1992, respectively. The algorithm exploits change vector analysis and tasseled cap transform. Although change vector analysis is effective for change detection, efficiency is decreased as the number of variables are increased. In this algorithm, we overcome the problem by utilizing the tasseled cap transform which can reduce six bands of LANDSAT TM data into only two components called Brightness and Greenness. The test results demonstrate that the algorithm is very effective in monitoring small-scaled changes over coastal area as well as significant changes in geomorphology. The resulting change vector image, however, is more sensitive to the changes occurred by human activities than by pure geological processes mainly because of relatively short time interval between two LANDSAT TM data sets.

• Ocean Science Journal
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• v.41 no.2
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• pp.97-104
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• 2006

A useful radiance-converting method was developed to convert the Landsat-7 ETM+thermal-infrared (TIR) band's radiance ($L_{{\lambda},L7/ETM+}$) to that of Landsat-5 TM TIR ($L_{{\lambda},L5/TM+})$ as: $L_{{\lambda},L5/TM}=0.9699{\times}L_{{\lambda},L7/ETM+}+0.1074\;(R^2=1)$. In addition, based on the radiance-converting equation and the linear relation between digital number (DN) and at-satellite radiance, a DN-converting equation can be established to convert DN value of the TIR band between Landsat-5 and Landsat-7. Via this method, it is easy to integrate Landsat-5 and Landsat-7 TIR data to retrieve the sea surface temperature (SST) in coastal waters on the basis of local empirical algorithms in which the radiance or DN of Lansat-5 and 7 TIR band is usually the only input independent variable. The method was employed in a local empirical algorithm in Daya Bay, China, to detect the thermal pollution of cooling water discharge from the Daya Bay nuclear power station (DNPS). This work demonstrates that radiance conversion is an effective approach to integration of Landsat-5 and Landsat-7 data in the process of a SST retrieval which is based on local empirical algorithms.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.163-169
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• 2003

• Journal of Environmental Impact Assessment
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• v.9 no.3
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• pp.177-183
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• 2000

The Landsat Thematic Mapper (TM) has suggested that spatial and spectral characteristics would be suited to evaluate water quality of lake. But, TM has not been commonly used for the analysis of in-land water quality, such as surface water temperature, chlorophyll-a, suspended sediments, and Secchi depth in domestic research. This paper summarizes the analysis of Landsat 5 - TM image collected on 22 Feb 1996 for evaluation of chlorophyll-a and surface temperature in the Lake Soyang. And, field measurements collected in the Lake Soyang were used to obtain water optical algorithms for calibration of satellite data. It is concluded that we can assess chlorophyll-a with remote sensing reflectance and surface temperature with thermal band in lake Soyang. However, surface temperature calculated with thermal band of Landsat TM are underestimated. Relationship between remote sensing reflectance and chlorophyll-a using the ratio of TM band 1 and band 3 is as follows; Y = 17.206 - 6.4711 * (Rrs(band1) / Rrs(band3)) $R^2$=0.8762 and, using the ratio of TM band 1 and band 2 as follows; Y = 57.77 - 35.771 * (Rrs(band1) / Rrs(band2)) $R^2$=0.8317.

• Journal of Forest and Environmental Science
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• v.15 no.1
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• pp.65-70
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• 1999

The study analyze Conifer and Hardwood area and their distribution to seek an efficient survey for Experimental Forest of Kangwon National University using Landsat-5 TM data. Through forest cover types, we try to study on the possibility to use Satellite Data. development of Satellite Interpretation Skill and Digital Mapping Method. As analysis tools we use IMAGINE 8.3 and ArcView 3.0 software. The result showed that Hardwood took approximately 73%, 2,224ha of the total 3,058ha and Conifer takes 27%, 832ha.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.1
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• pp.73-83
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• 1999

The land use/cover information, which is periodically obtained from satellite imagery, can be effectively applied to change detection in rapidly changing urban areas. Also it can be used not only as base maps for spatial database in urban information system but as decision-making data for desired urban planning and development direction. In this study, we carried out both unsupervised and supervised classification on land use from Landsat TM and JERS-1 OPS data, which were collected respectively in 1991 and 1997, covering Kumi City and then detected land use changes.

• Economic and Environmental Geology
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• v.38 no.4 s.173
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• pp.395-409
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• 2005

To explore submarine groundwater discharge (SGD) into the coastal zone of Jeju Island, the water quality analysis with seasonal remotely sensed data was carried out. If the groundwater is directly discharged into the ocean, the water quality of coastal zone is influenced. Therefore sea surface temperature (SST), the transparency, and Chlorophyll-a's concentration were analyzed for extracting the anomaly zone related with SGD using Landsat Thematic Mapper (TM) data acquired on April, August, and December. Then the spatial characteristics of springs, which located along the coastal area, were analyzed by CIS data integration based on Fuzzy logic. The integration results were compared with the anomaly zone extracted from Landsat TM data, and it is considered that springs has close relationship with SGD.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.211-214
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• 2007

After the forest fire, as access is not easy, forest damage degree are determined with Landsat TM image rather than visual inspection. Therefore in this study, damaged areas are extracted with factor analysis and cluster analysis. Second factor analysis was performed for areas suspicious as forest fire damage areas to evaluate accuracy after separating into strong, medium and light forest fire areas.