• Journal of Korean Society for Geospatial Information Science
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• v.15 no.3
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• pp.51-57
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• 2007

In this study, We analyzed change of sea surface temperature due to cooling water around nuclear power station. Study area is around of Uljin nuclear power station, which is relatively large power station. There are many problems in monitering environmental change around of nuclear power station, because area is relatively large. We used Landsat 5, 7 Imagery which are useful in temperature analysis and can be easily obtained. After we georeferenced Landsat Imagery, radiance and sea surface temperature were calculated. As a result, As we compared sea surface temperature of surrounding area of nuclear power station with same area located 3 km east, there are $2.049^{\circ}C$ temperature difference.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.861-871
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• 2019

Landsat satellite images have been increasingly used for disaster damage analysis and disaster monitoring because they can be used for periodic and broad observation of disaster damage area. However, periodic disaster monitoring has limitation because of areas having missing data due to clouds as a characteristic of optical satellite images. Therefore, a study needs to be conducted for restoration of missing areas. This study detected and removed clouds and cloud shadows by using the quality assessment (QA) band provided when acquiring Landsat-8 images, and performed image restoration of removed areas through a spatial and temporal adaptive reflectance fusion (STARFM) algorithm. The restored image by the proposed method is compared with the restored image by conventional image restoration method throught MLC method. As a results, the restoration method by STARFM showed an overall accuracy of 89.40%, and it is confirmed that the restoration method is more efficient than the conventional image restoration method. Therefore, the results of this study are expected to increase the utilization of disaster analysis using Landsat satellite images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.219-225
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• 2008

There are many problems in monitering environmental change around of nuclear power station, because interesting area is coastal and relatively large. The ground resolution of Landsat ETM+ imagery is high (30 m), but this imagery does not have enough informations for conducting atmospheric correction in evaluating sea surface temperatures. On the other hand, while it is possible to conduct atmospheric correction using MODIS imagery with it's two infrared bands, it's resolution is relatively low (1 km). Therefore, atmospheric corrected high resolution temperature information can be obtained from these two satellite images. In this study, digital numbers of Landsat ETM+ data in interesting area are georeferenced, converted to effective temperatures based on radiance value, and then the atmospheric correction is conducted using MODIS data. As a result, about $3.5^{\circ}C$ temperature differences were detected in comparing sea surface temperature of the surrounding area of Uljin nuclear power station with it of the same area located 5km far east.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.383-392
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• 1993

Identification of rice paddy fields and estimation of their areas from the images taken by LANDSAT-5/TM were attempted. The results were verified by aerial photographs and also by ground observations. Changes of the spectral characteristics of rice plants were measured with a portable spectroradiometer during the growth period. Analyzing these characteristics, an index was developed for evaluating the growth and the yield of rice . Applying the index to the data observed by LANDSAT-5.TM on Sep. 26, 1986, Oct .20, 1989 and Sep, 21, 1990, it was confirmed that the estimated derived from the index agreed with actual values. The results well demonstrated its feasibility for evaluating the yield of rice by a satellite like LANDSAT-5/TM.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.4 no.2
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• pp.27-41
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• 1986

In this study, practical use of TM (Thematic Mapper) data was evaluated by comparison of LANDSAT- 5 TM and MSS (Multispectral Scanner) data. The comparison of TM and MSS data was achieved by analyzing the result of landuse mapping of Incheon area, and in addition, the comparison of accuracy according to image enhancement method was made. From the results of this study, we found that TM data was more accurate by about 20% than MSS data in landuse mapping, and that smoothing was effective in image enhancement processing of TM data.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.229-234
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• 2006

On May 31, 2003. Landsat 7 experienced an anomaly causing the Scan Line Corrector(SLC) to stop functioning normally. The SLC-off causes individual scan lines to alternately overlap and then leave large gaps at the edge of the Image. A many scientists with ongoing experience using ETM+ data evaluated the scientific usability and validity of Landsat 7 products containing the SLC anomaly The best reference scene for gap-filling is the other SLC-on Landsat scene that provide same resolution, few changes, and similar data acquisition. But receiving of Landsat imagery is not stable in Korea. So SPOT image can be another alternative solution because it is a steady-state multispectral satellite image as Landsat image. In this study, we filled the SLC-off gap s of 2, 3, 4 bands using SPOT image by a local regression technique, and assigned the optimum spectral value to gaps of 1, 5, 7 bands based on a spectral adjacency. Through this process, we could restore Landsat SLC-off image and evaluated the accuracy of the results.

• Korean Journal of Remote Sensing
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• v.2 no.2
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• pp.117-131
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• 1986

The purpose of this study was to develop techniques acquiring hydrologic parameters that affect runoff conditions from Landsat imagery. Runoff conditions in a study area were analyzed by employing the U.S. Soil Conservation Service(SCS) Method. SCS runoff curve numbers(CN) were estimated by the computer analysis of Landsat imagery and digiral terrain model(DTM) data. The SCS Method requires land use/cover and soil conditions of the area as input parameters. A land use/cover map of 5 hydrological classes was produced from the Landsat multi-spectral scannerr imagery. Slope-gradient and contour and contour maps were also made using the DTM topographic data. Inundation areas depending on reservoir levels were able to be mapped on the Landsat scene by combining the contour data.

• 한국해양학회지
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• v.11 no.1
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• pp.9-17
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• 1976

Multispectral scanner data collected by LANDSAT-1 over the mid West Sea of Korea were analyzed and interpreted for delineation of coastal features and turbidity distribution patterns during different portions of the tidal cycle. Imagery from two successful LANDSAT-1 overpasses of the area in October 1972 and in October 1973 had been used to prepare schematic maps of coastal features and turbidity distributions. Color composite imagery of LANDSAT MSS 4, 5 and 7 gave the best representation of shorelines, coastlines and tidal flats. MSS 5 imagery was most effective in differentiating relative turbidity levels through density slicing techniques. Referring to the tidal power development of Garolim Bay, the basin area measurements assuming dyke construction at the bay entrance, have been carried out on the coastal reature maps comiled from LANDSAT imagery, and those results were correlated with existing data. General areal patterns of surface turbidity distribution in the study area revealed close similarity with bathymetry of the area. Synoptic circulation patterns were also well discriminated from the LANDSAT imagery using the suspended sediment as a tracer.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.1-8
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• 1999

The estimation technique of surface water temperature by satellite remote sensing has been applied to ocean and large lakes using AVHRR. However, the spatial resolution AVHBR is not abquate for coastal region and small lakes. Landsat 5 TM has 120 m spatial resolution, which suits better. We carried out analysis of surface water temperature in Lake Sihwa and near coastal area using Landsat 5 TM. To relate digital number to the brightness temperature, we applied Empirical, NASA, RESTEC, Quadratic methods. Comparing calculated and observed value, we obtained as follows; NASA method, $R^2=0.9343$, RMSE(Root Mean Square Error)=3.5876$^{\circ}C$; RESTEC method, $R^2=0.8937$, RMSE=3.76$^{\circ}C$; Quadratic method, $R^2=0.8967$, RMSE=2.949$^{\circ}C$. Because Landsat TM has only one band for extracting surface temperature, it was difficult to correct for the atmospheric errors. For improving the accuracy of surface temperature detection using Landsat TM, there is a need for a method to decrease the effect of atmospheric contents.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.765-779
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• 2022

This study evaluates the accuracy in identifying the burned area in South Korea using multi-temporal data from Sentinel-2 MSI and Landsat 8/9 OLI. Spectral indices such as the Difference Normalized Burn Ratio (dNBR), Relative Difference Normalized Burn Ratio (RdNBR), and Burned Area Index (BAI) were used to identify the burned area in the March 2022 forest fire in Uljin. Based on the results of six indices, the accuracy to detect the burned area was assessed for four satellites using Sentinel-2 and Landsat 8/9, respectively. Sentinel-2 and Landsat 8/9 produce images every 16 and 10 days, respectively, although it is difficult to acquire clear images due to clouds. Furthermore, using images taken before and after a forest fire to examine the burned area results in a rapid shift because vegetation growth in South Korea began in April, making it difficult to detect. Because Sentinel-2 and Landsat 8/9 images from February to May are based on the same date, this study is able to compare the indices with a relatively high detection accuracy and gets over the temporal resolution limitation. The results of this study are expected to be applied in the development of new indices to detect burned areas and indices that are optimized to detect South Korean forest fires.