• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.1
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• pp.57-66
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• 2001

This study used four theoretical models, such as two-point linear model, linear regression model, quadratic regression model and cubic regression model which are presented from The Ministry of Science and Technology, for extraction of urban surface temperature from Landsat TM band 6 image. Through correlation and regression analysis between result of four models and AWS(automatic weather station) observation data, this study could verify spatial distribution characteristic of urban surface temperature using GIS spatial analysis method. The result of analysis for surface temperature by landcover showed that the urban and the barren land belonged to the highest surface temperature class. And there was also -0.85 correlation in the result of correlation analysis between surface temperature and NDVI. In this result, the meteorological environmental characteristics wuld be regarded as one of the important factor in urban planning.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.47-55
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• 2006

This paper investigates the performance of sensor models based on satellite position and rotation angles and sensor models based on satellite orbit and attitude angles. We analyze the performance with respect to the accuracy of bundle adjustment and the accuracy of exterior orientation estimation. In particular, as one way to analyze the latter, we establish sensor models with respect to one image and apply the models to other scenes that have been acquired from the same orbit. Experiment results indicated that fer the sole purpose of bundle adjustment accuracy one could use both position-rotation models and orbit-attitude models. The accuracy of estimating exterior orientation parameters appeared similar for both models when analysis was performed based on single scene. However, when multiple scenes within the same orbital segment were used for analysis, the orbit-attitude model with attitude biases as unknowns showed the most accurate results.

• The Journal of Engineering Geology
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• v.26 no.1
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• pp.23-32
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• 2016

This study evaluates landslide susceptibility using statistical analysis by SVM (support vector machine) and the illite index of clay minerals extracted from ASTER(advanced spaceborne thermal emission and reflection radiometer) imagery which can be use to create mineralogical mapping. Landslide locations in the study area were identified from aerial photographs and field surveys. A GIS spatial database was compiled containing topographic maps (slope, aspect, curvature, distance to stream, and distance to road), maps of soil properties (thickness, material, topography, and drainage), maps of timber properties (diameter, age, and density), and an ASTER satellite imagery (illite index). The landslide susceptibility map was constructed through factor correlation using SVM to analyze the spatial database. Comparison of area under the curve values showed that using the illite index model provided landslide susceptibility maps that were 76.46% accurate, which compared favorably with 74.09% accuracy achieved without them.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.3
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• pp.186-194
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• 2017

In this paper, we analyze the main performance of satellite's Synthetic Aperture Radar system for high resolution and wide swath. We have used the radiation pattern of reflector antenna with array feed and comparison between the conventional ScanSAR mode and SweepSAR mode has been carried out. The SweepSAR mode is a high-resolution wide-swath mode that transmits beams over a wide range and receives echo signals through sequential beamforming based on SCORE(SCan On REceive). In this paper, we analyzed the operating principle and characteristics of satellite's SweepSAR mode and simulate system performances. In addition, in order to increase the utilization of image, performances analysis for multiple frequency bands(C-band, X-band) has been considered.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.63-71
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• 2013

This study calculated vegetation indexes such as SR, NDVI, SAVI, and LAI to figure out correlations regarding vegetation by using high resolution KOMPSAT-2 images and LANDSAT images based on the forest biomass distribution map that utilized field survey data, satellite images and LiDAR data and then analyzed correlations between their values and forest biomass. The analysis results reveal that the vegetation indexes of high resolution KOMPSAT-2 images had higher correlations than those of LANDSAT images and that NDVI recorded high correlations among the vegetation indexes. In addition, the study analyzed the characteristics of hyperspectral images by using the COMIS of STSAT-3 and Hyperion images of a similar sensor, EO-1, and further the usability of biomass estimation in hyperspectral images by comparing vegetation index, which had relatively high correlations with biomass, with the vegetation indexes of LANDSAT with the same GSD conditions.

• Korean Journal of Agricultural Science
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• v.41 no.3
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• pp.205-211
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• 2014

Focused on Mt. Bogdkhan nature reserve in Mongolia, this study was conducted as a fundamental research to discover a tendency and characteristics of forest damage and to draw up measures for proper plans of forest restoration through an analysis of year-to year change using satellite images. In specific, land cover mapping was conducted by using Landsat images from 1994 to 2011, and then year-to year change was analyzed to investigate the features of forest damage in Mt. Bogdkhan. The results showed that the whole area of a reservation in Mongolia in 2011 was about $416.89km^2$; among them, forest area was $167,87km^2$, accounting for about 40.3%, followed by bare patch and grassland area (58.6%) and urban dry area (1.1%). In particular, compared in 1994, the area of forest in 2011 has increased by $6.12km^2$; while bare patch and grassland area has decreased by $10.81km^2$. Primary causes of forest degradation occurred in Mt. Bogdkhan nature reserve included illegal logging for fuel, forest and grassland degradation caused by domestic animals grazing, man-made forest fire, and disaster caused by insect pest.

• Economic and Environmental Geology
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• v.38 no.2 s.171
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• pp.143-153
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• 2005

Euiseong subbasin, included in the Kyungsang Basin, was created by the result of volcanic activity in the late Cretaceous, and contacts with Milyang and Youngyang subbasins by Palgongsan and Andong faults, respectively. In this study, geophysical survey is implemented fur investigating surface and subsurface geologic structure in Euiseong subbasin which composed with the complex of volcanic and plutonic rocks. To understand surface geologic feature, IRS satellite image and DEM(Digital Terrain Map) are used for analyzing lineament and its density. The numbers of lineaments show major trend in $N55^{\circ}\~65^{\circ}W$, and aspects of lineament lengths show major trend in $N55^{\circ}\~65^{\circ}W$ and N-S directions. 13 delineate subsurface density discontinuity; Power spectrum analysis was implemented for gravity anomaly data, resulting $4-5{\cal}km$ depth of basin basement and $0.5-0.6{\cal}km$ depth of shallow discontinuity. From the result of power spectrum analysis, 2.5-D modelings were implemented along two profiles of A-A' and B-B', and they show subsurface geology in detail. Analytic signal method for detecting boundaries of magnetic basements show 0.001-130 nT/m values, and high energy area show good correspondency with the boundaries of Palgongsan granite and caldera areas in Euiseong subbasin.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.277-292
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• 2020

The purpose of this study is to propose the possibility of precise surface sedimentary facies classification and a more accurate classification method by generating the large-scale map of surface sedimentary facies based on UAV data and object-based image analysis (OBIA) for Hwang-do tidal flat in Cheonsu bay. The very high resolution UAV data extracted factors that affect the classification of surface sedimentary facies, such as RGB ortho imagery, Digital elevation model (DEM), and tidal channel density, and analyzed the principal components of surface sedimentary facies through statistical analysis methods. Based on principal components, input data to be used for classification of surface sedimentary facies were divided into three cases such as (1) visible band spectrum, (2) topographical elevation and tidal channel density, (3) visible band spectrum and topographical elevation, tidal channel density. The object-based image analysis classification method was applied to map the classification of surface sedimentary facies according to conditions of input data. The surface sedimentary facies could be classified into a total of six sedimentary facies following the folk classification criteria. In addition, the use of visible band spectrum, topographical elevation, and tidal channel density enabled the most effective classification of surface sedimentary facies with a total accuracy of 63.04% and the Kappa coefficient of 0.54.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.225-230
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• 2007

Currently, looking at the field of producing national coastlines, the lengths of coastlines are inaccurate due to the vague definition of dividing coastline boundaries and insufficient observation data. The level of accuracy and reliability of previous data are also in the very low. This paper used aerial photographs with certain intervals to monitor the change in coastal areas of Songjeong, Haeundae, Kwanganri, Songdo and Dadaepo. The local area subjected for this research was limited to areas near Busan. Launching quantitative/time series analyses on the change of coastal areas using aortal photographs, satellite image data and RTK-GPS surveys. And developing an automatic edge detection program to extract coastlines, suggesting the performance of the program and analyzing the efficiency of the program.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.249-253
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• 2005

인공위성 데이터를 이용한 원격탐사 기술과 지형공간정보시스템의 통합에 의한 도시에의 활용은 도시 계획뿐 만 아니라, 환경정비와 유지 관리 측면 등에서 중요한 역할을 하고 있다. 본 연구는 대상지역의 Landsat TM 영상자료를 이용하여 보정과정을 수행하고, GSIS 시스템의 NDVI(Normalized Difference Vegetation Index)식을 이용하여 식생지수를 추출하였다. 산출된 식생지수를 5개 등급으로 분류하여 비 식생지역과 식생이 활발한 지역을 구분하여 분석하였고, 인공위성 데이터의 밴드간 비연산 처리를 실시하여 식물의 건강상태를 나타내는 NDVI를 위성 데이터를 이용하여 추출함으로써, 시가지내의 녹지분포에 대한 시계열적 변화를 분석하였다. 이 결과 도심주변지역에 분포하는 낯은 구릉지에서 점차적으로 도시화가 이루어짐을 알 수 있었고, 전체 면적별 녹지분포가 높은 구릉지 및 산악지역의 3, 4, 5등급지역 면적 비율이 68.9%에서 37.2%로 감소한 것으로 나타났다.