• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.132-137
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• 2005

재해분야에 인공위성의 활용도가 높아짐에 따라 본 연구에서는 Landsat 영상과 RADARSAT 영상을 이용하여 안성천유역을 대상으로 침수지역을 추출하고자 하였다. Landsat 영상은 침수 전과 후의 영상을 각각 선정하였으며 RADARSAT 영상은 침수 중과 침수 후 의 영상을 선정하였다. 각 영상에 대하여 전처리와 기하보정을 걸친 후 침수지역을 파악하기 위한 방법으로 토지피복분류 방법을 사용하였고, 그 중 Landsat 영상은 분광반사계를 이용하여 감독분류를 실시하였고, RADARSAT 영상은 무감독 분류를 실시하여 침수 지역을 확인할 수 있었다.

• Journal of Environmental Impact Assessment
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• v.20 no.2
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• pp.199-205
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• 2011

The Saemangeum embankment construction have changed the flowing on the topography of the coastal marine environment. However, the variety of ecological factors are changing from outside of Saemangeum embankment area. The ecosystem of various marine organisms have led to changes by sea surface temperature. The aim of this study is to monitoring of sea surface temperature(SST) changes were measured by using thermal infrared satellite imagery, MODIS and Landsat. The MODIS data have the high temporal resolution and Landsat satellite data with high spatial resolution was used for time series monitoring. The extracted informations from sea surface temperature changes were compared with the dyke to allow them inside and outside of Saemangeum embankment. The spatial extent of the spread of sea water were analyzed by SST using MODIS and Landsat thermal channel data. The difference of sea surface temperature between inland and offshore waters of Saemangeum embankment have changed by seasonal flow and residence time of sea water in dyke.

• 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.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.4 no.2
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• pp.36-44
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• 2001

The main purpose of this study was to classify forest vegetation effectively using Landsat Thematic Mapper data(June, 1994) in mountainous region. The research area was the Mt. Wolak Experimental Forest of Chungbuk National University, near Chungju and Jecheon city, Chungcheongbuk-do. To classify forest vegetation effectively, Normalized Difference Vegetation Index(NDVI) was used to reduce topographic effects. This NDVI was modified and transformed to the value of 0 to 255, and then the modified values were combined with other Landsat Thematic Mapper bands. To classify forest and land cover types, unsupervised classification method was used. The results of this study are summarized as follows. 1. Combinations of band "3, 5, NDVI" in Landsat Thematic Mapper data showed a good separation with high accuracy. The expected classification accuracy was 95.1% in Landsat Thematic Mapper data. 2. The Land Cover types were classified into six groups : coniferous forest, deciduous forest, mixed forest, paddy and grass, non-forest, and other undetectable areas. As these classified results were compared with the reconnaissance survey and aerial black and white infrared photographs, the overall classification accuracy was 76.5% in Landsat Thematic Mapper data. 3. The portion of non-forest in Mt. Wolak area was 1.9%. The percentages of coniferous, deciduous and mixed forests were 30.9%, 35.7% and 26.4%, respectively. 4. As these classified results were compared with other reference data, the percentages of coniferous, deciduous and mixed forests increased, but the portion of non-forest was exceedingly diminished. These differences are thought to be from the different research method and the different season of received Landsat Thematic Mapper data.

• Korean Journal of Soil Science and Fertilizer
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• v.30 no.2
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• pp.135-139
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• 1997

Vegetation indices were analyzed from the LANDSAT images of Yeoju, Kwangju and Yangpyong Gun of Kyunggi Province, obtained on September 22, 1983 and September 12, 1994, to evaluate the changes in landuses. It was found that there were notable changes in the landuses in the observed area over 11 years. Particularly, in Choweol Myun of Kwanju Gun, in Yangpyong Eup of Yangpyong Gun, and in Heungcheon Myun of Yeoju Gun, decrease in the area under vegetatin was most remarkable. These changes in the area under vegetatin are considered as the results of the construction of highways and the expansion of urban areas. The LANDSAT images overestimated the area under rice cultivation, when compared to the official statistic year book. However, it was found that the areas of the land under rice cultivation estimated by LANDSAT images for each Myun were close enough to those from the official statistics suggesting that the LANDSAT images can be used for the estimation of landuse status.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.1
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• pp.46-56
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• 2016

In order to analyze the surface temperature in accordance with the surface material, surface temperatures between Thermal InfraRed Image (TIRI) and Landsat 8 satellite observed at the commercial area (Gwanghwamun) and residential area (Jungnang) are compared. The surface temperature from TIRI had applied atmospheric correction and compared with that from Landsat 8. The surface temperatures from Landsat 8 at Gwanghwamun and Jungnang are underestimated in comparison with that from TIRI. The difference of surface temperature between the two methods is greater in summer than in winter. When the analysis area was divided into detailed regions, depending on the material and the position of the surface, correlation of surface temperature between TIRI with Landsat 8 is as low as 0.29 (Gwanghwamun) and 0.18 (Jungnang), respectively. The results were caused from the resolution difference between the two methods. While the surface temperatures of each zone from Landsat 8 were observed almost constant, high-resolution TIRI observed relatively precise surface temperatures. When the each area was averaged as one space, correlation of surface temperature between TIRIs and Landsat 8 is more than 0.95. The spatially averaged surface temperature is higher at Jungnang, representing residential areas, than at Gwanghwamun, representing commercial areas. As a result, the observation of high resolution is required in order to observe the precise surface temperature. This is because it appears that the spatial distribution of the various surface temperature in the range of micro-scale according to the conditions of the ground surface.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.233-242
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• 2010

SEBAL (Surface Energy Balance Algorithm for Land) developed by Bastiaanssen (1995) is an image-processing model comprisedof twenty-five sub models that calculates spatial evapotranspiration (ET) and other energy exchanges at the surface. SEBAL uses image data from Landsat or other satellites measuring thermal infrared radiation, visible and near infrared. In this study, the model was applied to Gyeongancheon watershed, the main tributary of Han river Basin. ET was computed on apixel-by-pixel basis from an energy balance using 4 years (2001-2004) Landsat and MODIS images. The scale effect between Landsat (30 m) and MODIS (1 km) was evaluated. The results both from Landsat and MODIS were compared with FAO Penman-Monteith ET. The absolute errors between satellite ETs and Penman-Monteith ET were within 12%. The spatial and temporal characteristics of ET distribution within the watershed were also analyzed.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.735-743
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• 2001

CN procedure has been proven to be useful method for evaluating the effects of changes in land-use and treatment on hydrology. In this study, the use of Landsat multi-spectral image was investigated for analyzing the land-use distribution. From the Landsat data, forest areas were classified according to the density of trees. Watershed CN's were calculated to analyze the effects of the density of trees and soil cover types on direct runoff. According to the results, the density of trees had a little effect while soil cover types had a large effect on CN, From the comparison of estimated runoffs from CN method with observed runoffs, detailed soil cover map provides improved results.