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안호용(Ahn, Ho Yong),박소영(Park, So young),최철웅(Choi, Chul Uong) 대한공간정보학회 2011 한국공간정보학회 학술대회 Vol.2011 No.5
토지이용변화 예측 모델로는 Cellular Automata(CA) 모델이 많이 이용되고 있다. 하지만, 비선형 동적모형은 CA 기법 또한 시계열 자료의 변화양상을 공통적으로 적용시켜 인접격자의 상태를 지속적으로 변화시키기 때문에 실제의 토지이용 정책이나 사회?경제적 요인에 의한 토지피복 변화의 경향을 반영하기 어렵다. 이에 반해, CLUE(Conservation of Land Use Change and its Effects) 모델은 환경변화와 사회ㆍ경제적 변화 등을 반영하여 토지이용 변화를 파악할 수 있는 모델이다. 따라서 본 연구는 부산지역과 서울지역을 대상으로 1985년부터 2005년 까지 환경부에서 작성한 토지피복도를 이용하여 토지피복 변화를 비교분석하고, CLUE 모델을 이용하여 향후 2020년의 토지이용변화를 예측하였다. 이를 위해 도시지역의 변화예측에 활용할 수 있는 회귀식을 도출하고 확률지도를 생성하기 위해 부산지역과 서울지역의 토지이용과 구동요인의 회귀분석을 수행하였다.
최철웅 ( Chul Uong Choi ),김호용 ( Ho Young Kim ),전성우 ( Sung Woo Jun ) 大韓遠隔探査學會 2003 大韓遠隔探査學會誌 Vol.19 No.4
원격탐사는 각종 상업용 위성과 항공사진을 바탕으로 연구된다. 그러나 이러한 자료는 연구자들이 원하는 시기와 장소에서 촬영하는데 기상조건 및 경제적 이유로 많은 어려움을 겪고 있다. 이러한 문제점을 해결하는 작은 방안의 하나로 본 연구에서는 소형비행기 및 초경량 비행기에 탈 부착이 가능한 소형 다중분광 자동 항공촬영시스템을 개발하였다. 본 항공촬영시스템은 연구실 자체에서 보유한 고해상도 다중분광카메라(가시대역, 적외선대역)와 열 적외선 카메라, 자체 제작한 자동카메라 정밀자세조정장치, 촬영관제 소형컴퓨터, gimbal, GPS수신기, 기상센서 등으로 구성되어 있다. 이에 대한 성능평가 및 분석을 경북 칠포지역에서 2회, 낙동강지역에서 3회, 경안천 지역에서 2회 실시하였다. 그 결과, 다양한 항공사진, 기상자료 및 GPS자료를 획득할 수 있었고, 환경감시 등에 유용성이 매우 높음을 알 수 있었다. The cost of deploying Geological and Environmental information gathering systems, especially when such systems obtain remote sensing and photographic data through the use of commercial satellites and aircraft. Besides the high cost equipment required, adverse weather conditions can further restrict a researcher`s ability to collect data anywhere and anytime. To mitigate this problem, we have developed a compact, multi-spectral automatic Aerial photographic system. This system`s Multi-spectral camera is capable of the visible (RGB) and infrared (NIR) bands (3032*2008 pixel). It consists of a thermal infrared camera and automatic balance control, and can be managed by a palm-top computer. Other features includes a camera gimbal system, GPS receiver, weather sensor among others. We have evaluated the efficiency of this system in several field tests at the following locations: Kyongsang-bukdo beach, Nakdong river (at each site of mulkeum-namji and koryung-gumi), and Kyungahn River. Its tested ability in aerial photography, weather data, as well as GPS data acquisition demonstrates its flexibility as a tool for environmental data monitoring.
SCS-CN 산정을 위한 수치세부정밀토양도 활용과 괴산군 소수면 소유역의 물 유출량 평가
홍석영(Suk-Young Hong),정강호(Kang-Ho Jung),최철웅(Chol-Uong Choi),장민원(Min-Won Jang),김이현(Yi-Hyun Kim),손연규(Yeon-Kyu Sonn),하상건(Sang-Keun Ha) 한국토양비료학회 2010 한국토양비료학회지 Vol.43 No.3
“Curve number” (CN) indicates the runoff potential of an area. The US Soil Conservation Service (SCS)’s CN method is a simple, widely used, and efficient method for estimating the runoff from a rainfall event in a particular area, especially in ungauged basins. The use of soil maps requested from end-users was dominant up to about 80% of total use for estimating CN based rainfall-runoff. This study introduce the use of soil maps with respect to hydrologic and watershed management focused on hydrologic soil group and a case study resulted in assessing effective rainfall and runoff hydrograph based on SCS-CN method in a small watershed. The ratio of distribution areas for hydrologic soil group based on detailed soil map (1:25,000) of Korea were 42.2% (A), 29.4% (B), 18.5% (C), and 9.9% (D) for HSG 1995, and 35.1% (A), 15.7% (B), 5.5% (C), and 43.7% (D) for HSG 2006, respectively. The ratio of D group in HSG 2006 accounted for 43.7% of the total and 34.1% reclassified from A, B, and C groups of HSG 1995. Similarity between HSG 1995 and 2006 was about 55%. Our study area was located in Sosu-myeon, Goesan-gun including an approx. 44 km²-catchment, Chungchungbuk-do. We used a digital elevation model (DEM) to delineate the catchments. The soils were classified into 4 hydrologic soil groups on the basis of measured infiltration rate and a model of the representative soils of the study area reported by Jung et al. 2006. Digital soil maps (1:5,000) were used for classifying hydrologic soil groups on the basis of soil series unit. Using high resolution satellite images, we delineated the boundary of each field or other parcel on computer screen, then surveyed the land use and cover in each. We calculated CN for each and used those data and a land use and cover map and a hydrologic soil map to estimate runoff. CN values, which are ranged from 0 (no runoff) to 100 (all precipitation runs off), of the catchment were 73 by HSG 1995 and 79 by HSG 2006, respectively. Each runoff response, peak runoff and time-to-peak, was examined using the SCS triangular synthetic unit hydrograph, and the results of HSG 2006 showed better agreement with the field observed data than those with use of HSG 1995.
다목적실용위성 3호 AEISS센서의 방사 특성 교차 검증
신동윤 ( Dong-yoon Shin ),최철웅 ( Chul-uong Choi ),이선구 ( Sun-gu Lee ),안호용 ( Ho-yong Ahn ) 대한원격탐사학회 2016 大韓遠隔探査學會誌 Vol.32 No.5
This study, multispectral and hyperspectral sensors were utilized to use radiometric cross validation for the purpose of radiometric quality evaluation of a ‘KOMPSAT-3`. Images of EO-1 Hyperion and Landsat-8 OLI sensors taken in PICS site were used. 2 sections that have 2 different types of ground coverage respectively were selected as the site of cross validation based on aerial hyperspectral sensor and TOA Reflectance. As a result of comparison between the TOA reflectance figures of KOMPSAT-3, EO-1 Hyperion and CASI-1500, the difference was roughly 4%. It is considered that it satisfies the radiological quality standard when the difference of figure of reflectance in a comparison to the other satellites is found within 5%. The difference in Blue, Green, Red band was approximately 3% as a comparison result of TOA reflectance. However the figure was relatively low in NIR band in a comparison to Landsat-8. It is thought that the relatively low reflectance is because there is a difference of band passes in NIR band of 2 sensors and in a case of KOMPSAT-3 sensor, a section of 940nm, which shows the strong absorption through water vapor, is included in band pass resulting in comparatively low reflectance. To overcome these conditions, more detailed analysis with the application of rescale method as Spectral Bandwidth Adjustment Factor (SBAF) is required.