• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.287-299
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• 2017

The Southern Volcanic Zone (SVZ) of Chile consists of many volcanoes, including the Mt.Villarrica and Mt.Llaima, and the two volcanoes are covered with snow at the top of Mountain. The purpose of this study is to analyze the relationship between the ice caps and the volcanic activity of the two volcanoes for 25 years by using the satellite image data are available in a time series. A total of 60 Landsat-5 TM and Landsat-7 ETM + data were used for the study from September 1986 to February 2011. Using NDSI (Normalized Difference Snow Index) algorithm and SRTM DEM, snow cover and snowline were extracted. Finally, the snow cover area, lower-snowline, and upper-snowline, which are quantitative indicators of snow cover change, were directly or indirectly affected by volcanic activity, were extracted from the satellite images. The results show that the volcanic activity of Villarrica volcano is more than 55% when the snow cover is less than 20 and the lower-snowline is 1,880 m in Llaima volcano. In addition, when the upper-snowline of the two volcanoes is below -170m, it can be confirmed that the volcano is differentiated with a probability of about 90%. Therefore, the changes in volcanic snowfall are closely correlated with volcanic activity, and it is possible to indirectly deduce volcanic activity by monitoring the snow.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.621-629
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• 2008

This study was carried out in part of Tamil Nadu, India. Also, Landsat ETM+ image and field sampling data were acquired. The field data were basal area, number of trees and number of species. Using the data set, this study performed a three steps processing, (1) Image classification (2) extracting the vegetation indices(NDVI, Tasseled cap brightness, greenness and wetness) (3) mapping the prediction of biodiversity distribution using basal area and NDVI image value. Basal area was significantly correlated with NDVI. The result of classification showed 69% overall accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.3
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• pp.289-297
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• 2006

The Land Cover/Land Use Map have been constructed from 1998, which has hierarchical structure according to land cover/land use system. Level 1 classification Map have done using Landsat satellite image over whole Korean peninsula. Level II classification Map have been digitized using IRS-1C, 1D, KOMPSAT and SPOT5 satellite images resolution-merged with low resolution color images. Level II Land Cover/Land Use Map construction by digitizing method, however, is consuming enormous expense for satellite image acquisition, image process and Land Cover/Land Use Map construction. In this paper, the possibility of constructing Level II Land Cover/Land Use Map using hyperspectral satellite image of EO-1 Hyperion, which is studied a lot recently, is studied. The comparison of classifications using Hyperion satellite image offering more spectral information and Landsat-7 ETM+ image is performed to evaluate the availability of Hyperion satellite image. Also, the algorithm of the optimal band selection is presented for effective application of hyperspectral satellite image.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.23-32
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• 2011

This research uses a distributed model, Vflo which can devide subwater shed into square grids and interpret diverse topographic elements which are obtained through GIS processing. To use the distributed model, soil wetness information was extracted through Tasseled Cap transformation from LANDSAT 7 $ETM^+$ satellite data and then they were applied to each cell of the test area, unlike previous studies in which have applied average soil condition of river basin uniformly regardless of space-difference in subwater shed. As a resut of the research, it was ascertained the spatial change of soil wetness is suited to the distributed model in a subwater shed. In addition, we derived out a relation between soil wetness of image collection time and 10 days-preceded rainfall and improved the feasibility of weights obtained by the relation equation.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.1 s.19
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• pp.101-108
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• 2002

The studies using satellite data have been progressed in many area. Especially, Landsat data have been widely used due to its wide coverage. To establish a plan for preserving fishing and environment preservation, measurement of sea temperature is important. The measurement of the sea temperature was made on the ship. However, the measurement on the ship could not provide sufficient information due to the poor timing with relatively longer measurement, and point-based data acquisition. Thus remote sensing technique is required because satellite image data offer more wide coverage in sea temperature monitoring. The purpose of this paper was to study on the sea temperature monitoring with thermal band information of Landsat ETM+. From this study, sea temperature map of Cheju island has been made efficiently.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.113-118
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• 2008

본 연구는 Landsat 7 ETM+를 이용한 지열자원 평가 가능성 연구로써, 위성영상의 열적외 밴드에서 추출된 지표온도와 지열자료의 비교를 통해 위성영상이 초기 지열 탐사에 적용 가능한지를 평가하기 위하여 실시하였다. 지열자원 부존 가능성 평가를 위해 경상도지역(114-35)의 여름시기영상(2001년8월24일)과 겨울시기영상(2000년3월14일)사이의 DN(Digital Number) 값을 이용하였으며, 두 시기영상은 시추공 온도자료 및 지형자료와 함께 비교 분석을 실시하였다. 영상에서 지표온도 추출을 위해 1) NASA에서 제공하는 지표온도 산출 경험식 ( T = K $_2$ / ln ( K $_1$ / L $_{\lambda}$ + 1 ) )을 이용한 방법과 2) 기상청에서 제공하는 실제 지표면온도 관측자료(n=7)를 이용해 영상의 화소(Pixel) 값을 계산하여 실측값과 비교하였다. 3월과 8월 모두 Ground Truth 방법에 따라 추정한 지표면 온도값이 실측값과 더 가깝게 나타났고, 특히 3월은 NASA의 경험식을 이용했을 때 보다 실측 지표면 온도에 훨씬 더 가까운 것으로 나타났다. 지표온도의 일변화(Diurnal ${\triangle}$T)는 지표 열물성과 밀접한 관련이 있으므로, 일변화(Diurnal ${\triangle}$T) 보다는 지열의 영향이 더 클 것으로 기대되는 계절변화(Seasonal ${\triangle}$T)를 이용하여 지열 자료와 비교해 보았다. 그 결과, 계절변화(Seasonal ${\triangle}$T)는 고도에 영향을 받으며, 일사량에 의한 차이는 거의 일정하게 나타났다. 위성영상에서 계절변화(Seasonal ${\triangle}$T)와 심도 20m 온도를 비교해 본 결과결정계수(R$^2$)는 0.46으로 낮지만 심도 20m 온도가 높을수록 계절변화(Seasonal ${\triangle}$T)는 작아지는 경향을 보여 지열자원 탐사에 있어 위성영상 적용 가능성을 볼 수 있었다. 이번 연구는 기초단계로서 두 시기 위성영상을 이용하여 초기 지열자원탐사에 가능성만을 연구했지만, 지형과 특히 토지피복(함수량 등)에 의한 영향에 대해 좀 더 심도 있는 연구가 요구된다.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.521-528
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• 2007

The overall objective of this research was to investigate various combination of segmentation parameters and to improve classification accuracy of object-oriented classification. This research presents a method for evaluation of segmentation parameters by calculating Moran's I and Intrasegment Variance. This research used Landsat-7/ETM image of $11{\times}14$ Km developed area in Ansung, Korea. Segmented images are generated by 75 combinations of parameter. Selecting 7 combinations of high, middle and low grade expected classification accuracy was based on calculated Moran's I and Intrasegment Variance. Selected segmentation images are classified 4 classes and analyzed classification accuracy according to method of objected-oriented classification. The research result proved that classification accuracy is related to segmentation parameters. The case of high grade of expected classification accuracy showed more than 85% overall accuracy. On the other hand, low ado showed around 50% overall accuracy.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.393-407
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• 2012

This study focuses on the correction of topographic effects caused by a combination of solar elevation and azimuth, and topographic relief in single optical remote sensing imagery, and by a combination of changes in position of the sun and topographic relief in comparative analysis of multi-temporal imageries. For the Jeju Island, Republic of Korea, where Mt. Halla and various cinder cones are located, a Landsat 7 ETM+ imagery and ASTER GDEM data were used to normalize the topographic effects on the imagery, using two topographic normalization methods: cosine correction assuming a Lambertian condition and assuming a non-Lambertian c-correction, with kernel sizes of $3{\times}3$, $5{\times}5$, $7{\times}7$, and $9{\times}9$ pixels. The effects of each correction method and kernel size were then evaluated. The c-correction with a kernel size of $7{\times}7$ produced the best result in the case of a land area with various land-cover types. For a land-cover type of forest extracted from an unsupervised classification result using the ISODATA method, the c-correction with a kernel size of $9{\times}9$ produced the best result, and this topographic normalization for a single land cover type yielded better compensation for topographic effects than in the case of an area with various land-cover types. In applying the relative radiometric normalization to topographically normalized three multi-temporal imageries, more invariant spectral reflectance was obtained for infrared bands and the spectral reflectance patterns were preserved in visible bands, compared with un-normalized imageries. The results show that c-correction considering the remaining reflectance energy from adjacent topography or imperfect atmospheric correction yielded superior normalization results than cosine correction. The normalization results were also improved by increasing the kernel size to compensate for vertical and horizontal errors, and for displacement between satellite imagery and ASTER GDEM.

• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.87-99
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• 2006

The Median Resolution Sensors (MRSs) for land observation such as Landsat-ETM+ and SPOT-HRV are more effective than Ocean Color Sensors (OCSs) for studying of detailed ecological and biogeochemical components of the coastal waters. In this study, we developed suspended sediment algorithm for Landsat TM/ETM+ by considering the spectral response curve of each band. To estimate suspended sediment concentration (SS) from satellite image data, there are two difference types of algorithms, that are derived for enhancing the accuracy of SS from Landsat imagery. Both empirical and remote sensing reflectance model (hereafter referred to as $R_{rs}$ model) are used here. This study tried to compare two algorithm, and verified using in situ SS data. It was found that the empirical SS algorithm using band 2 produced the best result. $R_{rs}$ model-based SS algorithm estimated higher values than empirical SS algorithm. In this study we used $R_{rs}$ model developed by Ahn (2000) focused on the Mediterranean coastal area. That's owing to the difference of oceanic characteristics between Mediterranean and Korean coastal area. In the future we will improve that $R_{rs}$ model for the Korean coastal area, then the result will be advanced.

• Korean Journal of Environment and Ecology
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• v.18 no.2
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• pp.231-235
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• 2004

Landsat satellite images were analyzed to study vegetation change patterns of warm-temperate forests from 1991 to 2002 in Wando. For this purpose, Landsat TM satellite image of 1991 and Landsat ETM image of 2002 were used for vegetation classification using ENVI image processing software. Four different forest types were set as a classification criteria; evergreen broadleaf, evergreen conifer, deciduous broadleaf, and others. Unsupervised classification method was applied to classily forest types. Although it was impossible to draw exact forest types in rocky areas because of differences in data detection time and rough resolution of image, 2002 data revealed that total 2,027ha of evergreen broadleaf forests were growing in Wando. Evergreen broadleaves and evergreen conifers increased in total areas compared to 11 years ago, but there was sharp decrease in deciduous broadleaves. GIS-based management system for warm-temperate forest was done using Arc/Info. Geographic and attribute database of Wando such as vegetation, soils, topography, land owners were built with Arc/Info and ArcView. Graphic user interface which manages and queries necessary data was developed using Avenue.