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MMS로부터 취득된 LiDAR 점군데이터의 반사강도 영상과 UAV 영상의 정합을 위한 특징점 기반 매칭 기법 연구
최윤조,무하마드,홍승환,손홍규 한국측량학회 2019 한국측량학회지 Vol.37 No.6
Recently, as the demand for 3D geospatial information increases, the importance of rapid and accurate data construction has increased. Although many studies have been conducted to register UAV (Unmanned Aerial Vehicle) imagery based on LiDAR (Light Detection and Ranging) data, which is capable of precise 3D data construction, studies using LiDAR data embedded in MMS (Mobile Mapping System) are insufficient. Therefore, this study compared and analyzed 9 matching algorithms based on feature points for registering reflectance image converted from LiDAR point cloud intensity data acquired from MMS with image data from UAV. Our results indicated that when the SIFT (Scale Invariant Feature Transform) algorithm was applied, it was able to stable secure a high matching accuracy, and it was confirmed that sufficient conjugate points were extracted even in various road environments. For the registration accuracy analysis, the SIFT algorithm was able to secure the accuracy at about 10 pixels except the case when the overlapping area is low and the same pattern is repeated. This is a reasonable result considering that the distortion of the UAV altitude is included at the time of UAV image capturing. Therefore, the results of this study are expected to be used as a basic research for 3D registration of LiDAR point cloud intensity data and UAV imagery. 최근 3차원 공간정보에 대한 수요가 증가함에 따라 신속하고 정확한 데이터 구축의 중요성이 증대되어 왔다. 정밀한 3차원 데이터 구축이 가능한 LiDAR (Light Detection and Ranging) 데이터를 기준으로 UAV (Unmanned Aerial Vehicle) 영상을 정합하기 위한 연구가 다수 수행되어 왔으나, MMS (Mobile Mapping System)로부터 취득된 LiDAR 점군데이터의 반사강도 영상을 활용한 연구는 미흡한 실정이다. 따라서 본 연구에서는 MMS로부터 취득된 LiDAR 점군데이터를 반사영상으로 변환한 데이터와 UAV 영상 데이터의 정합을 위해 9가지의 특징점 기반 매칭 기법을 비교·분석하였다. 분석 결과 SIFT (Scale Invariant Feature Transform) 기법을 적용하였을 때 안정적으로 높은 매칭 정확도를 확보할 수 있었으며, 다양한 도로 환경에서도 충분한 정합점을 추출할 수 있었다. 정합 정확도 분석 결과 SIFT 알고리즘을 적용한 경우 중복도가 낮으며 동일한 패턴이 반복되는 경우를 제외하고는 약 10픽셀 수준으로 정확도를 확보할 수 있었으며, UAV 영상 촬영 당시 UAV 자세에 따른 왜곡이 포함되어 있음을 감안할 때 합리적인 결과라고 할 수 있다. 따라서 본 연구의 분석 결과는 향후 LiDAR 점군데이터와 UAV 영상의 3차원 정합을 위한 기초연구로 활용될 수 있을 것으로 기대된다.
Geolocation Error Analysis of KOMPSAT-5 SAR Imagery Using Monte-Carlo Simulation Method
최윤조,홍승환,손홍규 한국측량학회 2019 한국측량학회지 Vol.37 No.2
Geolocation accuracy is one of the important factors in utilizing all weather available SAR satellite imagery. In this study, an error budget analysis was performed on key variables affecting on geolocation accuracy by generating KOMPSAT-5 simulation data. To perform the analysis, a Range-Doppler model was applied as a geometric model of the SAR imagery. The results show that the geolocation errors in satellite position and velocity are linearly related to the biases in the azimuth and range direction. With 0.03cm/s satellite velocity biases, the simulated errors were up to 0.054 pixels and 0.0047 pixels in the azimuth and range direction, and it implies that the geolocation accuracy is sensitive in the azimuth direction. Moreover, while the clock drift causes a geolocation error in the azimuth direction, a signal delay causes in the range direction. Monte-Carlo simulation analysis was performed to analyze the influence of multiple geometric error sources, and the simulated error was up to 3.02 pixels in the azimuth direction
센다이프레임워크 전환에 따른 재해위험경감 관련 국내 정책동향변화 및 과학기술의 역할
최윤조,홍승환,이수진,손홍규 대한토목학회 2017 대한토목학회논문집 Vol.37 No.4
With the end of the HFA (Hyogo Framework Action) in 2015, SFDRR (Sendai Framework for Disaster Risk Reduction) was adoptedas a new agenda for disaster risk reduction at the 3th WCDRR (World Conference on Disaster Risk Reduction), held in March 2015. Continued understanding of the international agenda for reducing disaster risk is critical to disaster risk reduction at the national levelas well as international level. Therefore, in this study, we analyzed major changes in the international agenda for disaster risk reduction as the transition from HFA to SFDRR, and analyzed South Korea’s major achievements in the HFA and the implementation status of SFDRR in South Korea. In addition, SFDRR emphasizes the role of science and technology in policy making, and examined research trends in science and technology. 49.9% of the efforts were made to prevent the disasters during the disaster management stage,and plans related to priority 1 (40.4%) and 4 (35.8%) were mainly promoted. Science and technology research and development fordisaster management were analyzed as active, but 79.7% of the tasks were related to priority 4, and it is necessary to develop all four priorities. Recently, disaster management using next-generation disaster prevention technologies such as satellite technology and big data is required, and it is expected that it will contribute effectively to mitigate disaster risk through establishment of education and policy to support it. 2015년 효고행동강령이 종료됨에 따라 2015년 3월 개최된 제3차 세계재난위기경감회의에서 센다이프레임워크가 재해위험경감을 위한 새로운 글로벌 아젠다로 채택되었다. 재해위험경감을 위한 글로벌 아젠다에 대한 지속적인 파악은 글로벌 수준뿐만 아니라 국가 수준에서의 재해위험 경감에 있어서도 매우 중요하다. 이에 따라 본 연구에서는 재해위험경감을 위한 글로벌 아젠다가 효고행동강령에서 센다이프레임워크로 전환됨에 따라 아젠다의 주요 변화 내용을 살펴보았으며, 효고행동강령 이행에 대한 국내 주요 성과와 센다이프레임워크 채택에 따른 현재까지의 국내현황을 분석하였다. 또한 센다이프레임워크는 정책결정에 있어서 과학 및 기술의 역할을 강조하고 있으며, 국내에서 과학기술 분야의 연구 동향을 살펴보았다. 재난관리 단계 중 예방을 위한 노력이 49.9%로 가장 많이 이루어지고 있었으며, 행동우선순위 1 (40.4%)과 4 (35.8%) 관련 계획들이 주로 추진되고 있었다. 재난관리를 위한 과학기술 연구 개발 또한 활발하게 진행되고 있는 것으로 분석되었으나, 행동우선순위 4와 관련 된 과제가 79.7%로 대부분을 차지하고 있었으며, 4가지 행동우선순위를 모두 고려한 개발이 필요하다고 할 수 있다. 최근 위성기술, 빅데이터 등의 차세대 방재기술을 활용한 재해관리가 요구되고 있으며, 이를 지원할 수 있는 교육 및 정책 수립을 통해 재해위험경감에 효과적으로 기여할 수 있을 것으로 기대된다.
최윤조,조한진,홍승환,이수진,손홍규 대한공간정보학회 2016 대한공간정보학회지 Vol.24 No.4
Sixty four percent of Korean territory consists of forest which is fragile for forest fire. However, it is difficult to detect the disaster-induced damages due to topographic complexity in mountainous areas and harsh weather conditions. For this reason, satellite imaging systems have been widely utilized to detect the damage caused by forest fire. In particular, ground vegetation condition can be estimated from multi-spectral satellite images and change detection technique has been used to detect forest fire damages. However, since Korea has clear four seasons, simple change detection technique has limitation. In this regard, this study applied the NDVI(normalized difference vegetation index) annual cycle modeling technique on time-series of Landsat images from 1991 to 2007 to analyze influence of forest fire of Yangyang-gun, Gangwon-do in 2005 on vegetation condition. The encouraging result was obtained when comparing the areas where forest fire occurs with non-damaged areas. The mean value of NDVI was decreased by 0.07 before and after the forest fire. On the other hand, annual variability of NDVI had been increasing and peak value of NDVI was stationary after the forest fire. It is interpreted that understory vegetation was seriously damaged from the forest fire occurred in 2005.