전자지방정부 구현을 위한 GIS 활용방안 연구(Strategies for implementing GIS-based local E-government)

노트 : 이 연구보고서의 내용은 국토연구원의 자체 연구물로서 정부의 정책이나 견해와는 상관없습니다

국내외 공간빅데이터 정책 및 기술동향

노트 : [특집 | 공간빅데이터와 새로운 국토가치 창출 4

국가GIS 중장기 정책방향 연구(Vision and policy issues for national geographic information system in Korea)

노트 : 이 연구보고서의 내용은 국토연구원의 자체 연구물로서 정부의 정책이나 견해와는 상관없습니다

공간빅데이터체계 구축, 활용 정책방향

노트 : [특집 | 공간빅데이터와 새로운 국토가치 창출 1

기업의 공간빅데이터 활용사례

노트 : [특집 | 공간빅데이터와 새로운 국토가치 창출 3

Quantitative Kinetic Energy Estimated from Disdrometer Signal

The kinetic energy of the rain drops was predicted in a relation between the rain rate and rain quantity, derived directly from the rain drop size distribution (DSD), which had been measured by a disdrometer located in the eastern state of Alagoas-Brazil. The equation in the form of exponential form suppressed the effects of large drops at low rainfall intensity observed at the beginning and end of the rainfall. The kinetic energy of the raindrop was underestimated in almost rain intensity ranges and was considered acceptable by the performance indicators such as coefficient of determination, average absolute error, percent relative error, mean absolute error, root mean square error, Willmott's concordance index and confidence index

대형 폐기물량 산정을 위한 UAS와 TLS 기반 공간정보 구축기법 연구

학위논문(박사)--서울대학교 대학원 :환경대학원 협동과정 조경학,2019. 8. 이동근.대형재난 발생에 대한 사전예방부터 대응단계까지 전과정의 체계적이고 효율적인 대처를 통해 인명, 재산, 환경 등의 피해를 최소화하여야 한다. 본 연구는 대형재난 발생 시 대응 과정 중 폐기물량 산정에 집중하여 연구를 수행하였다. 대형폐기물량 산정에 대한 연구는 과거부터 수행되고 있지만 실질적인 측정이 어렵기 때문에 발생 이전의 정보를 이용하여 모델링, 원격탐사 등의 기술을 이용하여 폐기물량을 예측하는 연구가 다수 수행되고 있다. 본 연구에서는 최근 활발하게 이용되고 있는 UAS (Unmanned Aerial System)를 기반으로 폐기물량을 산정하고 정확도를 평가하며 기존 기술과의 비교와 분석을 수행하고자 하였다. UAS는 UAV (Unmanned Aerial Vehicle)를 이용하여 영상을 취득하고 분석하는 전반적인 과정이라고 볼 수 있다. UAS를 이용하여 3차원 공간정보를 구축하고 정확도를 평가하는 연구가 과거부터 주로 수행되고 있으며 다양한 분야에 적용되고 있다. 이와 유사하게 TLS (Terrestrial Laser Scanning)를 이용하여 3차원 공간정보를 구축할 수 있는데 측량 분야에서 주로 이용되고 있으며 그 정확성 또한 우수하여 식생, 건축, 토목, 문화재, 지형측량 등 다양한 분야에서 널리 이용되고 있다. 대형폐기물량 또한 TLS를 이용하여 3차원 공간정보 구축 후 산정할 수 있지만 비용, 시간 등의 제약사항으로 인해 활용이 불가능하다고 볼 수 있다. 본 연구는 크게 3가지 부분으로 구분할 수 있다. 첫 번째는 UAS를 이용한 3차원 공간정보 구축과 폐기물량 산정 가능성 모색이다. UAS를 이용하여 3차원 공간정보 구축까지의 과정을 정밀 분석하여 최적의 비행변수와 기타 변수를 도출하여 폐기물량 산정의 가능성을 보고자 하였다. 두 번째는 TLS 기술과 UAS 기술 기반의 3차원 공간정보의 비교와 분석이다. 각각의 3차원 공간정보를 M3C2알고리즘을 이용하여 비교하고 분석하여 최적의 폐기물량 산정 기법을 도출하고자 하였다. 마지막으로 세 번째는 3차원 공간정보의 융합과 효율성 분석이다. 두 가지 기술을 융합하여 3차원 공간정보를 구축하고 효율성을 분석하여 UAS, TLS, 융합기법 세가지 방법론간의 차이와 최적의 폐기물량 산정 기법을 도출하고자 하였다. 주요 비행변수는 비행고도와 영상의 중복도이며 이외 변수는 지상기준점 개수이다. 이 외에도 카메라 내부표정, 짐벌의 흔들림 정도를 분석하였다. 본 연구를 통해 56개의 케이스 중 최적의 변수를 도출하였으며 과거 연구와는 다르게 고도차이가 많이 나는 폐기물 지역에서는 DW (Distance covered on the ground by on image in Width direction)에 의해 결과가 도출되었다. 일반적으로 고도가 낮을수록 높은 정확도를 가지는 3차원 공간정보를 구축하지만 본 연구에서는 고도가 낮을수록 정확도가 낮아지는 것을 확인하였다. 56개의 케이스 모두 정확도 분석을 실시하였으며 정확도와 폐기물량간의 상관성이 있음을 도출하였다. 3차원 공간정보의 정확도가 높을수록 산정한 폐기물량이 유사했으며 이와 반대로 정확도가 낮은 3차원 공간정보들에서는 폐기물량이 제각각으로 나타나는 것을 확인할 수 있었다. 이러한 일련의 과정을 통해 폐기물량 산정을 위한 UAS 최적 변수를 도출하였으며 3차원 공간정보 기반의 폐기물량 산정 가능성을 확인할 수 있었다. M3C2알고리즘을 이용하여 UAS와 TLS 기반의 3차원 공간정보를 비교하였으며 이를 통해, 각각의 공간정보가 가지고 있는 장단점을 확인할 수 있었다. 정확도의 경우, UAS기반 3차원 공간정보의 RMSE는 0.032m, TLS의 RMSE는 0.202m로 UAS의 정확도가 더 높은 것으로 나타났다. 두 가지 기술을 융합한 3차원 공간정보의 RMSE는 0.030m로써 세 가지 방법론 중에서 가장 높은 정확도를 보였다. 하지만 효율성 관점에서 분석한 결과, UAS 기반의 3차원 공간정보가 단시간에 높은 정확도를 보이는 결과로 도출됨으로써 대형폐기물량 산정에 최적화된 기술과 방법론을 가지고 있는 것으로 확인할 수 있었다. 이 외에도 비용을 분석한 결과, UAS 기반의 3차원 모형 구축까지 소비된 비용이 TLS에 비해 적은 비용이 소비된 것을 확인할 수 있었다. 대형재난 시 비교적 단시간에 대응하여 피해를 최소화 하고 다양한 의사결정을 진행해야 하는데, 본 연구를 통해 도출한 UAS 기반의 3차원 공간정보 구축 기법은 대형 폐기물량산정과 공간적 의사결정에 활용할 수 있을 기대한다.Damage to people, property, and the environment must be minimized through systematic and efficient handling of large-scale disasters throughout the entire process from prevention to the response stage. This study focused on the waste quantity calculations that are part of the response process during large-scale disasters. Studies on large-scale waste quantity calculations have been performed in the past, but actual measurements are difficult. Therefore, many studies are being performed on using information from previous instances to perform modeling and using technologies such as remote sensing to estimate waste quantities. This study calculated waste quantities based on UAS (unmanned aerial system), which is a technology that is often used these days. It evaluated the accuracy of this technology, and it analyzed and compared the technology with existing technologies. UAS can be seen as an overall process of using UAVs (Unmanned Aerial Vehicle) to capture images and analyzing them. Studies have been conducted in the past on using UAS to build 3D spatial information and evaluate accuracy, and they are being used integrally in a variety of fields. Similarly, 3D spatial information can be built using TLS (Terrestrial Laser Scanning), and these are chiefly used in the surveying field. This methods accuracy is excellent, and it is widely used in a variety of fields such as vegetation, construction, civil engineering, cultural assets, and topographical surveys. Large-scale waste can also be calculated by using TLS to build a 3D spatial information, but it is seen as unfeasible to use due to cost and time limitations. This study is broadly divided into 3 parts. The first part is examining the feasibility of using UAS to build a 3D spatial information and calculate waste quantity. The process up to the point of using UAS to build a 3D spatial information was analyzed in detail, and optimal flight variables and other variables were found in order to examine the feasibility of calculating waste quantity. The second part is comparing and analyzing 3D spatial information based on TLS and UAS technology. The 3D spatial information were compared and analyzed using the M3C2 algorithm, and the optimal waste quantity calculation methods were found. Finally, the third part is analyzing a combination of the 3D spatial information and the 3D spatial information efficiency. The two technologies were combined to build a 3D spatial information, and their efficiency was analyzed to find the differences between the three methodologies (UAS, TLS, and the combined method), as well as find the optimal waste quantity calculation method. The major flight variables are the flight altitude and image overlap. Another variable is the number of ground control points. In addition to this, the camera interior orientation and degree of gimbal shaking were analyzed. Through this study, the optimal variables among 56 cases were found. Unlike past studies, it was discovered that the results were contrary to previous studies due to the DW (Distance covered on the ground by on image in Width direction) in waste regions with a lot of altitude differences. Normally, as the altitude becomes lower, the accuracy of the 3D spatial information becomes higher, but in this study it was found that the accuracy became lower as the altitude became lower. The accuracy of all 56 cases was analyzed, and it was found that there is a correlation between accuracy and the amount of waste. As the accuracy of the 3D spatial information increased, the calculated waste amounts became similar. Conversely, in 3D spatial information with low accuracy, it was found that the waste amounts were different. Through this sequential process, the optimal UAS variables for calculating waste amounts were found, and it was possible to confirm the feasibility of calculating waste amounts based on 3D spatial iformation. The M3C2 algorithm was used to compare the UAS and TLS-based 3D spatial information, and by doing so, it was possible to confirm the advantages and disadvantages of each model. As for accuracy, the RMSE of the UAS-based 3D spatial information was 0.032 m, and the RMSE of the TLS model was 0.202, making the UAS models accuracy higher. The RMSE of the 3D spatial information which combined the two technologies was 0.030 m, and it showed the highest accuracy of the three methodologies. However, in terms of efficiency, the analyzed results were able to confirm that the UAS-based 3D spatial information had the optimal technology and methodology for large-scale waste amount calculations by creating a model which shows high accuracy in a short time. In addition, cost analysis results were able to confirm that the cost of building the UAS-based 3D spatial information was lower than that of TLS. During large-scale disasters, it is necessary to respond in a relatively short time to minimize damage and perform a variety of decision-making. The UAS-based 3D spatial information building method found in this study can be used for large-scale waste amount calculations and spatial decision-making.I. Introduction 1 II. Literature Review 7 1. Studies on Applying the UAS to Disaster Management 7 2. Accuracy of UAS-based 3D Model Construction 14 3. Disaster Waste Quantity 26 III. Materials and Methods 34 1. Optimal Flight Parameters for UAV Generating 3D Spatial Information 36 1.1. Design of UAV Flight 36 1.2. Photogrammetric Processing for the Acquisition of 3D Spatial Information 41 1.3. Assessment of the 3D Spatial Information Accuracy 43 1.4. Computation of the Amount of Waste 45 2. Comparison and Analysis of TLS and UAS Methodology for Optimal Volume Computation 47 2.1. TLS and UAS-based 3D Spatial Information Generation and Volume Computation 49 2.2. Comparison and Analysis of 3D Spatial Information 55 3. Multispace Fusion Methodology-based 3D Spatial Information Generating and Efficiency Analysis 57 3.1. Multispace Fusion Methodology-based 3D Spatial Information 57 3.2. Efficiency Analysis of 3D Spatial Information for Responding to Large-scale Disasters 58 III. Result and Discussion 59 1. Optimal Flight Parameters for UAV Generating 3D Spatial Information and Investigation of Feasibility 59 1.1. Generation of 3D Spatial Information using UAS 59 1.2. Assessment of the 3D Spatial Information Accuracy 64 1.3. Computation of the Amount of Waste and Optimal flights parameters 76 2. Comparison and Analysis of TLS and UAS-based 3D Spatial Information 84 2.1. Generation of 3D Spatial Information and Volume Computation using UAS 84 2.2. Spatial Comparison and Analysis 88 3. Multispace Fusion Methodology-based 3D Spatial Information Generating and Efficiency Analysis 93 3.1. Multispace Fusion Methodology-based 3D Spatial Information 93 3.2. 3D Spatial information Efficiency Analysis for Responding to Large-scale Disasters 96 IV. Conclusion 100 V. Bibliography 103Docto

Hyperspectral Irradiance Data for a Comparison and an Analysis of Optical Satellite Spectral Observation: Based on Seogwipo Forest Flux Tower

Comparison with ground-truth data is essential for developing and applying remote sensing algorithm towards the Earth surface. Unfortunately, major sources of domestic ground-truth data are depending on field-campaign with limited period because of insufficient all-time observation facilities within a domestic region. Korea Aerospace Research Institute, KARI, is planning to construct and operate surface observation tower to provide remote sensing infrastructure. This study was conducted as a pilot program of the observation tower construction and targeted to observe surface reflectance. The observation was made for about 21 months from May 2017. Two hyper-spectroradiometers were installed on top of a forest flux tower at Mt. Halla to measure hyperspectral up/down-welling irradiance, and surface reflectance was derived simply from their ratio. The derived surface reflectance was compared to surface reflectance values estimated from LANDSAT8 VNIR images, and the two surface reflectances coincided while showing effectiveness of the derived surface reflectance. The data acquired from this study would be able to provide background information for the expected surface observation tower, as well as actual ground-truth data for remote sensing application upon Mt. Halla area

Chlorophyll and Total Suspended Materials Concentrations and Remote Sensing Reflectance Data measured at the Red Tide Area of Jinhae, Geoje, and East Sea during August from 1998 to 2003 and August 2013

The chlorophyll and total suspended materials concentrations and remote sensing reflectance data were observed for red tides occurring every summer in waters around the Korean Peninsula. In observation area and date, the field survey were performed (1) in the Jinhae and Geoje coasts during August 1998, August 1999, August 2001, and August 2003, (2) in East Sea coast during August 2013. The remote sensing reflectance data were obtained from portable spectroradiometer. The chlorophyll concentration data were obtained from spectrophotometric method and the total suspended materials concentration data were obtained from filter-weight difference method. The remote sensing reflectance data were validated using Moon et al.(2012). The chlorophyll concentration data were validated using baseline correction and subtraction of 750 nm value, and the total suspended materials concentration data were validated using variation of humidity