• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.173-183
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• 2014

Field survey research on damages caused by volcanic activities has plenty of difficulties due to human resources, safety and costs issues. Remote sensing application using satellite image is one of very useful tools to overcome those issues. In this study, we monitored the volcanic activities of Sinabung volcano in 2010, which is located in Sumatra island, Indonesia by using Landsat 7 ETM+ satellite images acquired on 17 April, 2009 and 30 July, 2012. We found that the area of pyroclastic flow inundation after 2010 has been tripled roughly, since extracting the pyroclastic flow inundation before and after 2010 eruption from classification. The result from modeling of pyroclastic flow inundation has been compared with the extracted pyroclastic flow inundation from Landsat 7 ETM+ images. As a result, we confirmed that the length of inundation area from the modeling was calculated to 92% accurate, but the width of inundation area was somewhat imprecisely estimated in the volcanic area having the sharp slope and only calculated to 17% accurate.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.775-784
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• 2020

Recent global warming and anthropogenic activities have caused more frequent and massive wildfires with longer durations and more significant damages. MODIS has been monitoring global wildfires for almost 20 years, and GK2A and Himawari-8 are observing the wildfires in East Asia 144 times a day. However, the spatial resolution of 1 to 2 km is not sufficient for the detection of small and medium-size active fires, and therefore the studies on the active fire detection using high-resolution images are essential. However, there is no official product for the high-resolution active fire detection. Hence, we implemented the active fire detection algorithm of Landsat 8 and carried out a high-resolution-based detection of active fires in Australia in 2019, followed by the comparisons with the products of Himawari-8 and MODIS. Regarding the intense fires, the three satellites showed similar results, whereas the weak igniting and extinguishing fires or the fires in narrow areas were detected by only Landsat 8 with a 30m resolution. Small-sized fires, which are the majority in Korea, can be detected by the high-resolution satellites such as Landsat 8, Sentinel-2, Kompsat-3A, and the forthcoming Kompsat-7. Also, a comprehensive analysis together with the geostationary satellites in East Asia such as GK2A, Himawari-8, and Fengyun-3 will help the interoperability and the improvement of spatial and temporal resolutions.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.151-156
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• 2003

본 연구에서는 2000년 LANDSAT ETM+ 수도권 영상을 이용하여 도시지역 10개소, 식생지역 10개소를 선정해서 각각에 대해 표준화 주성분 분석을 적용하여 두 지역간의 고유벡터 매트릭스를 비교ㆍ분석해보았다. 도시 지역과 식생 지역각각에 대해 총 6개의 주성분이 생성되었으며 PC-2와 고유벡터 부호가 변한 밴드(band2, band7)를 RGB로 조합하여 수원지역을 대상으로 분류(Classification)한 결과의 정확도를 분광서명 분별 분석(Signature Separability Analysis)통해 얻은 밴드조합(band1, band3, band5) 영상의 분류결과와 비교해 보았다. 수원지역 2000년 IKONOS 영상의 다중분광 밴드(4×4m)와 전정색 밴드(1x1m)를 융합한 영상이 분류 정확도를 판단하는 기준으로 사용되었다. 비교결과 분류 전체 정확도는 각각 87.7%, 77.29% Khat 지수는 0.83, 0.68로 나타나 PC-2, 밴드2, 밴드7을 이용했을 때 분류 정확도를 높일 수 있다는 결과를 얻었다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.157-162
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• 2003

중저해상도 광학영상의 순간시야각(instantaneous filed of view -IFOV)에 포함되는 공간에는 반사특성이 상이한 두 개 이상의 지표물이 존재하는 경우가 대부분이다. 영상분류와 같은 기존의 영상처리기법에서는 하나의 화소가 단일의 지표물을 대표한다는 가정에서 접근하였으나, 최근 화소의 혼합정도를 세분하는 분광혼합분석(spectral mixture analysis)기법이 개발되고 있다. 분광혼합분석법을 이용하여 혼합된 화소에 포함된 지표물을 분해(unmixing) 하고 그 효과를 분석하고자 하여 경기도 광릉국립수목원의 시험림 지역을 대상으로 Landsat-7 ETM＋영상을 이용하여 선형혼합 모델을 적용하였고, 그 결과 각각의 화소를 6개의 End-member의 혼합비로 구분하였다. Endmember의 비율을 나타낸 영상을 분석하여 점유비율에 따른 활엽수와 침엽수의 구분을 할 수 있었고, 각 임상별의 특징도 얻을 수 있었다. 특히 침엽수의 경우 그림자의 효과가 높다는 특성도 파악 할 수 있었다. 분광혼합분석법은 기존의 전통 분류방법과는 달리 다양한 산림의 정보를 추출해 낼 수 있다.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.29-33
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• 2002

In order to utilize remote sensed images widely, it is necessary to correct geometrically. Traditional approaches to geometric correction require substantial human operations. Such substantial human operations make geometric correction a laborious and tedious process. In this paper, We introduce concept of GCP(Ground Control Point) Chip and generate a GCP Chip for automatic geometric correction. GCP Chip is small image patch which has a GCP in reference coordinate image. GCP Chip will be used to match new images in geometric correction. We generated GCP chip using Landsat-7 ETM+ panchromatic band image in this study. Henceforth this result will support automatic process in geometric correction.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.207-209
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• 2003

Quantifying crop production is one of the most important applications of remote sensing in which the temporal and up-to-date data can play very important role in avoiding any immediate insufficiency in agricultural production. A combination of climatic data and biophysical parameters derived from Landsat7 ETM+ was used to develop a mathematical model for wheat yield forecast in different geographically wide Wheat growing districts in Egypt. Leaf Area Index (LAI) and fraction of Absorbed Photosynthetically Active Radiation (fAPAR) with temperature were used in the modeling. The model includes three sub-models representing the correlation between the reported yield and each individual variable. Simulation results using district statistics showed high accuracy of the derived correlations to estimate wheat production with a percentage standard error (%S.E.) of 1.5% in El- Qualyobia district and average (%S.E.) of 7% for the whole wheat areas.

• Economic and Environmental Geology
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• v.43 no.5
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• pp.467-475
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• 2010

The Landsat and ASTER data have been used in mineralogical and lithological studies, and they have also proved to be useful tool in the initial steps for mineral exploration throughout Nevada mining district, US. Huge pyrophyllite quarry mines, including Jungang, Samsung, Kyeongju, and Naenam located in the southeastern part of Gyeongsang Basin. The geology of study area consists mainly of Cretaceous volcanic rocks, which belong into Cretaceous Hayang and Jindong Group. They were intruded by Bulgugsa granites, so called Sannae-Eonyang granites. To extraction of Ratio model for pyrophyllite deposits, tuffaceous rock and pyrophyllite ores from the Jungang mine used in reflectance spectral analysis and these results were re-sampled to Landsat and ASTER bandpass. As a result of these processes, the pyrophyllite ores spectral features show strong reflectance at band 5, whereas strong absorption at band 7 in Landsat data. In the ASTER data, the pyrophyllite ores spectral features show strong absorption at band 5 and 8, whereas strong reflectance at band 4 and 7. Based on these spectral features, as a result of application of $Py_{Landsat}$ model to hydrothermal alteration zone and other exposed sites, the DN values of two different areas are 1.94 and 1.19 to 1.49, respectively. The differences values between pyrophyllite deposits and concrete-barren area are 0.472 and 0.399 for $Py_{ASTER}$ model, 0.452 and 0.371 for OHIb model, 0.365 and 0.311 for PAK model, respectively. Thus, $Py_{ASTER}$ and $Py_{Landsat}$ model proposed from this study proved to be more useful tool for the extraction of pyrophyllite deposits relative to previous models.

• 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.

• Journal of Environmental Impact Assessment
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• v.11 no.4
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• pp.231-238
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• 2002

In this study we classified sediment types of tidal flat using Landsat-5 images. This is for groping the method which can analyze correctly various kinds of sediment faces through satellite images. This work was performed by referencing ground truth of sediment faces which was investigated in the field. With this data we classified Landsat-5 image of 1997's to grope a most suitable classification method. As a result, in case of south Kanghwa island area, it was the optimum way to compound band 4, 5, 7 of Landsat-5 TM imagery. And, this work classified 3 kinds of sediment faces - M(mud), sM(sandy mud) and (g)M(slightly gravelly mud) - in land and mixed water area. It is anticipated that if this method is applied to a image of extremely lower sea level time, it can classify the sediment types of a broad tidal flat area. This is expected to be a beginning of estimating the effect of sediment faces to the change of the tidal flat ecosystem.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.583-590
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• 2008

This study presents a correlation between timber Age, image bands and vegetation indices for timber age estimation. Basically, this study used Landsat TM images of three difference years (1994, 1994, 1998) and difference between Shuttle Radar Topography Mission (SRTM) and National Elevation Dataset (NED). Bands of 4, 5 and 7, Normalized Difference Vegetation Index (NDVI), Infrared Index (II), Vegetation Condition Index (VCI) and Soil Adjusted Vegetation Index (SA VI) were obtained from Landsat TM images. Tasseled cap - greenness and wetness images were also made by Tasseled cap transformation. Finally, analysis of correlation between timber age, difference between Shuttle Radar Topography Mission (SRTM) and National Elevation Dataset (NED), individual TM bands (4, 5, 7), Normalized Difference Vegetation Index (NDVI), Tasseled cap-Greenness, Wetness, Infrared Index (II), Vegetation Condition Index (VCI) and Soil Adjusted Vegetation Index (SAVI) using regression model. In this study about 1,992 datasets were analyzed. The Tasseled cap - Wetness, Infrared Index (II) and Vegetation Condition Index (VCI) showed close correlation for timber age estimation.