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Estimation of Carbon Absorption Distribution based on Satellite Image Considering Climate Change Scenarios (기후변화 시나리오를 고려한 위성영상 기반 미래 탄소흡수량 분포 추정)

  • Na, Sang-il;Ahn, Ho-yong;Ryu, Jae-Hyun;So, Kyu-ho;Lee, Kyung-do
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.833-845
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    • 2021
  • Quantification of carbon absorption and understanding the human induced land use changes forms one of the major study with respect to global climatic changes. An attempt study has been made to quantify the carbon absorption by land use changes through remote sensing technology. However, it focused on past carbon absorption changes. So prediction of future carbon absorption changes is insufficient. This study simulated land use change using the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) model and predicted future changes in carbon absorption considering climate change scenarios 4.5 and 8.5 of the Representative Concentration Pathways (RCP). Results of this study, in the RCP 4.5 scenarios there predicted to be loss of 7.92% of carbon absorption, but in the RCP 8.5 scenarios was 13.02%. Therefore, the approach used in this study is expected to enable exploration of future carbon absorption change considering other climate change scenarios.

A Study for Possibility to Detect Missing Sidewalk Blocks using Drone (드론을 이용한 보도블럭 탈락 탐지 가능성 연구)

  • Shin, Jung-il
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.5
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    • pp.34-41
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    • 2021
  • Sidewalks are facilities used for the safe and comfortable passage of pedestrians and are paved with blocks of various materials. Currently, Korea does not have a quantitative survey method for the pavement condition of sidewalks, so it is necessary to develop an efficient survey method. Drones are being used as an efficient survey tool in various fields, but there are limited studies in which sidewalks have been investigated. This study investigates the possibility of detection by limiting the missing sidewalk blocks using a drone. This study is an initial study on the development of a method for detecting damage in sidewalk blocks. For this, sidewalk blocks were artificially removed to simulate a dropout situation, and images were acquired with 0.7-cm resolution using a drone. As a characteristic of the point cloud data acquired through image pre-processing, there was high variance of the elevation of the points in the missing area of the sidewalk block. Using these characteristics, an experiment was conducted to detect the missing parts of the sidewalk block by applying four thresholds to the variance of the elevation of points included in the grid corresponding to the sidewalk area. As a result, the detection accuracy was shown with a positive detection ratio of 70-80%, omission errors of 20-30%, and commission errors lower than 2%. It is judged that the possibility of detecting missing sidewalk blocks is high. This study focused on detecting a simulated missing sidewalk block in a limited environment. Therefore, it is expected that an efficient and quantitative method of detecting damaged sidewalk blocks can be developed in the future through additional research with considerations of the actual environment.

Prediction of Land Surface Temperature by Land Cover Type in Urban Area (도시지역에서 토지피복 유형별 지표면 온도 예측 분석)

  • Kim, Geunhan
    • Korean Journal of Remote Sensing
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    • v.37 no.6_3
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    • pp.1975-1984
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    • 2021
  • Urban expansion results in raising the temperature in the city, which can cause social, economic and physical damage. In order to prevent the urban heat island and reduce the urban land surface temperature, it is important to quantify the cooling effect of the features of the urban space. Therefore, in order to understand the relationship between each object of land cover and the land surface temperature in Seoul, the land cover map was classified into 6 classes. And the correlation and multiple regression analysis between land surface temperature and the area of objects, perimeter/area, and normalized difference vegetation index was analyzed. As a result of the analysis, the normalized difference vegetation index showed a high correlation with the land surface temperature. Also, in multiple regression analysis, the normalized difference vegetation index exerted a higher influence on the land surface temperature prediction than other coefficients. However, the explanatory power of the derived models as a result of multiple regression analysis was low. In the future, if continuous monitoring is performed using high-resolution MIR Image from KOMPSAT-3A, it will be possible to improve the explanatory power of the model. By utilizing the relationship between such various land cover types considering vegetation vitality of green areas with that of land surface temperature within urban spaces for urban planning, it is expected to contribute in reducing the land surface temperature in urban spaces.

Detection Algorithm of Road Damage and Obstacle Based on Joint Deep Learning for Driving Safety (주행 안전을 위한 joint deep learning 기반의 도로 노면 파손 및 장애물 탐지 알고리즘)

  • Shim, Seungbo;Jeong, Jae-Jin
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.2
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    • pp.95-111
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    • 2021
  • As the population decreases in an aging society, the average age of drivers increases. Accordingly, the elderly at high risk of being in an accident need autonomous-driving vehicles. In order to secure driving safety on the road, several technologies to respond to various obstacles are required in those vehicles. Among them, technology is required to recognize static obstacles, such as poor road conditions, as well as dynamic obstacles, such as vehicles, bicycles, and people, that may be encountered while driving. In this study, we propose a deep neural network algorithm capable of simultaneously detecting these two types of obstacle. For this algorithm, we used 1,418 road images and produced annotation data that marks seven categories of dynamic obstacles and labels images to indicate road damage. As a result of training, dynamic obstacles were detected with an average accuracy of 46.22%, and road surface damage was detected with a mean intersection over union of 74.71%. In addition, the average elapsed time required to process a single image is 89ms, and this algorithm is suitable for personal mobility vehicles that are slower than ordinary vehicles. In the future, it is expected that driving safety with personal mobility vehicles will be improved by utilizing technology that detects road obstacles.

Consideration Points for application of KOMPSAT Data to Open Data Cube (다목적실용위성 자료의 오픈 데이터 큐브 적용을 위한 기본 고려사항)

  • LEE, Ki-Won;KIM, Kwang-Seob;LEE, Sun-Gu;KIM, Yong-Seung
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.1
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    • pp.62-77
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    • 2019
  • Open Data Cube(ODC) has been emerging and developing as the open source platform in the Committee on Earth Observation Satellites(CEOS) for the Global Earth Observation System of Systems(GEOSS) deployed by the Group on Earth Observations (GEO), ODC can be applied to the deployment of scalable and large amounts of free and open satellite images in a cloud computing environment, and ODC-based country or regional application services have been provided for public users on the high performance. This study first summarizes the status of ODC, and then presents concepts and some considering points for linking this platform with Korea Multi-Purpose Satellite (KOMPSAT) images. For the reference, the main contents of ODC with the Google Earth Engine(GEE) were compared. Application procedures of KOMPSAT satellite image to implement ODC service were explained, and an intermediate process related to data ingestion using actual data was demonstrated. As well, it suggested some practical schemes to utilize KOMPSAT satellite images for the ODC application service from the perspective of open data licensing. Policy and technical products for KOMPSAT images to ODC are expected to provide important references for GEOSS in GEO to apply new satellite images of other countries and organizations in the future.

Realization Method for Landscape Architecture Design Using Virtual Reality Technology - Focused on the Residential Garden Design - (가상현실(VR)기법을 이용한 조경설계 구현방법 - 주택정원 설계 중심으로 -)

  • Deng, Bei-Jia;Kim, Young-Hun;Cao, Lin-Sen;Heo, Sang-Hyun
    • Journal of the Korean Institute of Landscape Architecture
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    • v.47 no.3
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    • pp.71-80
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    • 2019
  • The Fourth Industrial Revolution, centered on intelligence and information, began to take hold in 2016. This study uses virtual reality technology, which is the most popular technology of the Fourth Industrial Revolution. The purpose of this study is to explore a Virtual Walk-through method, which can be easily applied to landscape architecture. At present, virtual reality technology is widely used in the fields of games, emergency training, and architectural design. However, in the field of landscape architecture, it is still in the development stage. In addition, most of the traditional ways to display virtual reality use 2D images, but such methods have some limitations. Therefore, this research addresses the three stages of "design-exhibition-experience" and puts forward a new simple method called 'Virtual Walk-through' that breaks from traditional landscape design exhibitions. The results show that compared with traditional methods, virtual reality has many advantages, such as the freedom of experience, a diversity of viewing angles, information supply, interaction, etc. It can show high quality images and effects, which are suitable for landscape design. It provides an evaluation method for garden design that can be utilized in the future. It is simple and has value as it can reflect the method and the expected effects. Virtual reality technology can bring an infinite number of prospects to the development of landscape architecture.

A Study on Pipe Model Registration for Augmented Reality Based O&M Environment Improving (증강현실 기반의 O&M 환경 개선을 위한 배관 모델 정합에 관한 연구)

  • Lee, Won-Hyuk;Lee, Kyung-Ho;Lee, Jae-Joon;Nam, Byeong-Wook
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.32 no.3
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    • pp.191-197
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    • 2019
  • As the shipbuilding and offshore plant industries grow larger and more complex, their maintenance and inspection systems become more important. Recently, maintenance and inspection systems based on augmented reality have been attracting much attention for improving worker's understanding of work and efficiency, but it is often difficult to work with because accurate matching between the augmented model and reality information is not. To solve this problem, marker based AR technology is used to attach a specific image to the model. However, the markers get damaged due to the characteristic of the shipbuilding and offshore plant industry, and the camera needs to be able to detect the entire marker clearly, and thus requires sufficient space to exist between the operator. In order to overcome the limitations of the existing AR system, in this study, a markerless AR was adopted to accurately recognize the actual model of the pipe system that occupies the most processes in the shipbuilding and offshore plant industries. The matching methodology. Through this system, it is expected that the twist phenomenon of the augmented model according to the attitude of the real worker and the limited environment can be improved.

A Study on the Improvement of Reliability of Line Conversion Monitoring System using CCTV Camera (CCTV카메라를 활용한 선로전환감시시스템의 신뢰성 향상에 관한 연구)

  • Moon, Chae-young;Kim, Se-min;Ryoo, Kwang-ki
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2019.05a
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    • pp.400-402
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    • 2019
  • The electric point machine, which is used for the control of the turnout used to change the track of the train, is very important in the railway system. Various wired and wireless real-time monitoring systems are used to check the status of the point machine, but there is a possibility of malfunction due to sensor or network error. In this paper, a redundant monitoring system was designed that incorporates the point machine monitoring system and the CCTV camera control system to double check the operation of the point machine. In the point machine monitoring system, the operating state of the railway converter is monitored, alarmed and transmitted over the network. The CCTV camera control system, which received this information, was required to record the status of the turnout and the point machine in question and send it to the administrator. The manager of the railway line can check the conversion status of the railway through the monitoring screen for the railway line switcher first, and then confirm the switching status directly through the CCTV camera image, thereby improving the reliability of the point machine operation. It will also enable the safe and efficient operation of personnel for management. It is expected to contribute to preventing a derailment caused by a malfunction of the point machine.

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Classification of Forest Vertical Structure Using Machine Learning Analysis (머신러닝 기법을 이용한 산림의 층위구조 분류)

  • Kwon, Soo-Kyung;Lee, Yong-Suk;Kim, Dae-Seong;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.35 no.2
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    • pp.229-239
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    • 2019
  • All vegetation colonies have layered structure. This layer is called 'forest vertical structure.' Nowadays it is considered as an important indicator to estimate forest's vital condition, diversity and environmental effect of forest. So forest vertical structure should be surveyed. However, vertical structure is a kind of inner structure, so forest surveys are generally conducted through field surveys, a traditional forest inventory method which costs plenty of time and budget. Therefore, in this study, we propose a useful method to classify the vertical structure of forests using remote sensing aerial photographs and machine learning capable of mass data mining in order to reduce time and budget for forest vertical structure investigation. We classified it as SVM (Support Vector Machine) using RGB airborne photos and LiDAR (Light Detection and Ranging) DSM (Digital Surface Model) DTM (Digital Terrain Model). Accuracy based on pixel count is 66.22% when compared to field survey results. It is concluded that classification accuracy of layer classification is relatively high for single-layer and multi-layer classification, but it was concluded that it is difficult in multi-layer classification. The results of this study are expected to further develop the field of machine learning research on vegetation structure by collecting various vegetation data and image data in the future.

Development of Web Service for Liver Cirrhosis Diagnosis Based on Machine Learning (머신러닝기반 간 경화증 진단을 위한 웹 서비스 개발)

  • Noh, Si-Hyeong;Kim, Ji-Eon;Lee, Chungsub;Kim, Tae-Hoon;Kim, KyungWon;Yoon, Kwon-Ha;Jeong, Chang-Won
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.10
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    • pp.285-290
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    • 2021
  • In the medical field, disease diagnosis and prediction research using artificial intelligence technology is being actively conducted. It is being released as a variety of products for disease diagnosis and prediction, which are most widely used in the application of artificial intelligence technology based on medical images. Artificial intelligence is being applied to diagnose diseases, to classify diseases into benign and malignant, and to separate disease regions for use in identification or reading according to the risk of disease. Recently, in connection with cloud technology, its utility as a service product is increasing. Among the diseases dealt with in this paper, liver disease is a disease with very high risk because it is difficult to diagnose early due to the lack of pain. Artificial intelligence technology was introduced based on medical images as a non-invasive diagnostic method for diagnosing these diseases. We describe the development of a web service to help the most meaningful clinical reading of liver cirrhosis patients. Then, it shows the web service process and shows the operation screen of each process and the final result screen. It is expected that the proposed service will be able to diagnose liver cirrhosis at an early stage and help patients recover through rapid treatment.