• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3D
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• pp.419-431
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• 2009

The core of this study is finding out the efficient band selection or extraction method discovering the optimal spectral bands when applying canonical correlation classifier (CCC) to hyperspectral data. The optimal efficient bands grounded on each separability decision technique are selected using Multispec$^{(C)}$ software developed by Purdue university of USA. Total 6 separability decision techniques are used, which are Divergence, Transformed Divergence, Bhattacharyya, Mean Bhattacharyya, Covariance Bhattacharyya, Noncovariance Bhattacharyya. For feature extraction, PCA transformation and MNF transformation are accomplished by ERDAS Imagine and ENVI software. For the comparison and assessment on the effect of feature selection and feature extraction, land cover classification is performed by CCC. The overall accuracy of CCC using the firstly selected 60 bands is 71.8%, the highest classification accuracy acquired by CCC is 79.0% as the case that executes CCC after appling Noncovariance Bhattacharyya. In conclusion, as a matter of fact, only Noncovariance Bhattacharyya separability decision method was valuable as feature selection algorithm for hyperspectral image classification depended on CCC. The lassification accuracy using other feature selection and extraction algorithms except Divergence rather declined in CCC.

• Spatial Information Research
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• v.2 no.1
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• pp.75-83
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• 1994

Many application using GIS has been carried out by governments and public office, and Cungbuk province has produced very effective results on agricultural income crops cultivation suit-land, since executed local autonomy system imported GIS for cope with variation of local administration environment, science of administration. The result on the selection of agricultural cultivation suit-land, in fact, offered us very useful information of the policy establishment concern with agriculture. In this study, we had analysed suit elements of cultivation : soil texture, soil drain, soil slope, soil depth and pH. ARC/INFO and ERDAS systems were used for this study.

• Proceedings of the KSRS Conference
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• v.2
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• pp.555-558
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• 2006

In recent years, urban development has expanded rapidly in Nawabshah City of Pakistan. A major effect associated with this population trend is transformation of the landscape from natural cover types to increasingly impervious urban land. The core objective of this study are to provide time-series information to define and measure the urban land cover changes of Nawabshah, Pakistan between the years 1992 and 2002, and to examine related urbanization impacts on air quality of the study area. Two multi-temporal Landsat images acquired in 1992 and 2002 together with standard topographical maps to measure land cover changes were used in this study. The image processing and data manipulation were conducted using algorithms supplied with the ERDAS Imagine software. An unsupervised classification approach, which uses a minimum spectral distance to assign pixels to clusters, was used with the overall accuracy ranging from 84 percent to 92 percent. Land cover statistics demonstrate that during the study period (1992-2002) extensive transformation of barren and vegetated lands into urban land have taken place in Nawabshah City. Results revealed that land cover changes due to urbanization has not only contaminated the air quality of the study area but also raised the health concerns for the local residents.

• ETRI Journal
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• v.21 no.4
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• pp.41-51
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• 1999

This research is an attempt to obtain more accurate land cover information from LANDSAT images. Canonical correlation analysis, which has not been widely used in the image classification community, was applied to the classification of a LANDSAT images. It was found that it is easy to select training areas on the classification using canonical correlation analysis in comparison with the maximum likelihood classifier of $ERDAS^{(R)}$ software. In other words, the selected positions of training areas hardly affect the classification results using canonical correlation analysis. when the same training areas are used, the mapping accuracy of the canonical correlation classification results compared with the ground truth data is not lower than that of the maximum likelihood classifier. The kappa analysis for the canonical correlation classifier and the maximum likelihood classifier showed that the two methods are alike in classification accuracy. However, the canonical correlation classifier has better points than the maximum likelihood classifier in classification characteristics. Therefore, the classification using canonical correlation analysis applied in this research is effective for the extraction of land cover information from LANDSAT images and will be able to be put to practical use.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.199-204
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• 2023

Periodic assessment of reservoir capacity is essential for better water resources management and planning for the future water use. Reservoirs and water storage structures raised on the rivers are subjected to sedimentation and he sedimentation is caused by deposition of eroded sediment particles carried by the streams. Knowledge of reservoir sedimentation is important to estimate avaliable storage capacity for optimum reservoir operation and scheduling water release. In recent years, remote sensing and GIS techniques have emerged as an important tool in carrying out reservoir capacity analysis and water management. The reduction in storage capacity as compared to the original capacity at the time of reservoir impounding is indicative of sediment deposition. In this study, the application of GIS and remote sensing techniques were applied to assess the sediment deposition, losses in the reservoir storage and the revised cumulative capacity. Satellite images covering Pyodongdong reservoir were analyzed using Erdas Imagine and ArcGIS softwares.Cumulative capacities at different levels were also calculated and we estimated that the revised live storage was 84.2Mft3 in 2021 and 64.3Mft3 in 2022 while the original capacity was 22.8 and 53.6Mft3 in 2021 and 2022.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.34-43
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• 2005

We will catch the spatio-temporal changes that analyse the unknown topography of Go-Gunsan Islands using Landsat TM satellite images into an unsupervised ISODATA classification and a supervised nearest likelihood classification. Each sedimental topography has the different characteristics according to building the Saemangeum embarkment. We will deal with the distribution of sedimental shapes using ERDAS Imagine 8. 6. The result that classifies specifically topographic properties of our research area be considered to get use of establishing the reclaiming program and predicating the reclaimed sedimental topography. The research area can be classified into tidal flats and sea level using band 4 among 7 bands of Landsat TM. Also band 5 can be used to classify the special unknown shapes of tidal flats. We will clarify the efficiency that spatio-temporal sedimental changes can be extracted through processing satellite images. Therefore, the spatio-temporal unknown topography change monitoring using satellite images is expected to be very useful to clarify whether the tidal flat is generated or not in the Go-Gunsan Islands at the outer side of the embarkment after constructing completely the Saemangeum tidal embarkment.

• Journal of the Korean Geographical Society
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• v.37 no.5
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• pp.511-521
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• 2002

Coastal sand dunes in West coast of Korea are under stress. Due to the newly constructed Seohaean(West Coast) Highways, the number of visitors and the anthropogenic pressures will keep rising in near future. Sea level rise due to the global warming may cause a lot of damage to the natural resources and residents of coastal area. Therefore, many countries including United States are doing nationwide coastline survey using highly sophisticated methodology. In this study, high resolution IKONOS satellite images along with aerial photographs taken since 1960's have been sequentially analyzed using GIS software (Erdas Imagine 8.3). Onsite monitoring has been performed at the 31 measuring points in 10 beaches since the May of 2001 in order to measure the sand budget. Post-construction monitoring after installation of sand fences is also being done on sites regularly. Restoration works seem to be effective at this moment.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1940-1944
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• 2006

현지관측을 통한 지속적이고 광범위한 지역에 대해 정확하고 정밀하게 조사하여 종합적인 분석과 예측, 결정과정에 있어서, 복잡한 해양의 특성, 여러가지 조사 작업상의 난점, 경제적, 시간적으로 많은 어려움이 따르게 된다. 하지만, 위성원격탐사와 GIS를 이용한 해양환경파악기법은 현지관측에서 얻을 수 있는 제한적인 자료이외의 다량의 자료를 정성 및 정량적으로 데이터베이스화하여 분석함과 동시에 가시화함으로써 해양개발로 인해 불가피하게 초래될 수밖에 없는 환경을 보다 정확하게, 객관적으로 분석하여 장기적으로 예측할 수 있는 고도화된 환경조사 및 평가 기술이라고 할 수 있다. 본 연구에서는 고해상도 위성자료인 Landsat TM 영상과 NOAA AVHRR 자료를 이용하여 수온 및 클로로필을 추출하였으며, GIS를 이용하여 현지관측자료 및 수치해도를 기초로 공간분포도를 작성함으로서 그 외의 수질환경요소를 산출하였다. 위성영상분석은 현장조사와 같은 시점의 Landsat TM 위성영상을 획득하여, 위성 영상은 지구의 곡률과 자전, 위성체의 자세와 고도 및 속도, 그리고 센서의 기하 특성으로 인하여 실제의 지형에 대하여 기하학적 왜곡을 가지고 있으므로 지형도에서 지상기준점(Ground Control Point, GCP)를 추출하여 ERDAS Imagine으로 UTM좌표체계에 따른 기하보정(Geometric Correction)을 실시하였으며, 동일한 시기의 NOAA AVHRR영상을 데이터로 처리하여 수온자료를 추출하였다. 표층수온과 현장관측에 의한 클로로필을 수치 지도화하기 위하여 열적외선영역인 TM band 6의 분광특성값(Digital Number)과 동일한 위치의 수온자료를 기초로 회귀분석을 실시함으로써 수온추출 알고리즘을 도출하여, 분석데이터의 신뢰도를 검증하였으며, 수온, 클로로필, 투명도 등을 위성원격탐사 자료와 GIS를 이용하여 공간분석을 실시하고, 공간분포도를 작성함으로써 대상해역의 해양환경을 파악하였다. 본 연구결과, 분석된 위성자료가 현장조사에 의한 검증이 이루어지지 않을 경우, 영상자료분석을 통한 표층수온 추출은 대기 중의 수증기와 에어로졸에 의한 계산치의 오차가 반영되기 때문에 실측치 보다 낮게 평가 될 수 있으므로, 반드시 이에 대한 검증이 필요함을 알 수 있었다. 현지관측에 비해 막대한 비용과 시간을 절약할 수 있는 위성영상해석방법을 이용한 방법은 해양수질파악이 가능할 것으로 판단되며, GIS를 이용하여 다양하고 복잡한 자료를 데이터베이스화함으로써 가시화하고, 이를 기초로 공간분석을 실시함으로써 환경요소별 공간분포에 대한 파악을 통해 수치모형실험을 이용한 각종 환경영향의 평가 및 예측을 위한 기초자료로 이용이 가능할 것으로 사료된다.

• Spatial Information Research
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• v.2 no.2
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• pp.135-145
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• 1994

The primary purpose of this study is, using Landsat remote sensing data and a image processing software, ERDAS, to generate real data and image photographs on physical land use of the Seoul metropolitan region. The remote sensing data used in this study are Landsat MSS data (August 28, 1979) and TM data (May 31, 1991) which cover the Seoul metropolitan region of Korea. The spatial resolutions of MSS data and TM data are 57m X 79m and 30m X 30m respectively. In addition, this study aims at contrasting urbanization phases of the Seoul metropolitan region in 1979 with those in 1991, by making image photographs and statistics on physical land use. Summing up the major results, built-up area ratio within the Seoul city had been expanded from 41.9% in 1979 to 64.5% in 1991 and that within the radius of 40km of Seoul city hall had been expanded from 10.5% In 1979 to 19.8% in 1991. The data and technique developed in this study could serve as a useful tool in making various kinds of spatial plannings, that is, urban and regional planning, selection of optimal new town location, evaluation of public facilities location alternatives, etc..

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.4 s.34
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• pp.67-73
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• 2005

The urbanization of Korea has been rapidly progressed since 1960, but satellite imagery have provided the information only after 1975. Recently released CORONA imagery is one of the few source of satellite image which can provide 1960's topographic information of the Korean Peninsular. It can be applied to change detection in various fields such as urban, forest, and environmental planning. In this research mosaic image of past Korean Peninsular using CORONA imagery in the 1960s were generated. A polynomial equation and a modified collinearity equation were applied for geo-referencing and a comparative analysis was conducted. In this research the 2nd polynomial equations were used for geo-referencing of CORONA imagery. After carrying out geo-referencing, mosaic image was generated using Erdas Imagine. It is assumed that this result image is very useful for various fields such as generation of thematic maps, urban planning, and change detection.