• 농촌계획
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• 제30권1호
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

• 한국멀티미디어학회논문지
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• 제8권6호
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• pp.844-855
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• 2005

This paper proposes a human action recognition scheme for Intelligent Web Browser. Based on the principle that a human action can be defined as a combination of multiple articulation movements, the inference of stochastic grammars is applied to recognize each action. Human actions in 3 dimensional (3D) world coordinate are measured, quantized and made into two sets of 4-chain-code for xy and zy projection planes, consequently they are appropriate for applying the stochastic grammar inference method. We confirm this method by experiments, that various physical actions can be classified correctly against a set of real world 3D temporal data. The result revealed a comparatively successful achievement of $93.8\%$ recognition rate through the experiments of 8 movements of human head and $84.9\%$ recognition rate of 60 movements of human upper body. We expect that this scheme can be used for human-machine interaction commands in a web browser.

• 한국환경복원기술학회지
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• 제18권2호
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• pp.19-32
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• 2015

In Korea, significant riparian areas have been developed due to river maintenance projects. Introduction of new riparian facilities can negatively affect wildlife in the riparian areas. This study focuses on selecting core conservation areas for Eurasian Otter(Lutra lutra) to support decision making process for development of riparian areas. For the study, first of all, field data of study site were collected by field surveys. Secondly, stream naturalness was assessed to understand physical environments of the study sites. Thirdly, habitat suitability was assessed using occurrence data of Eurasian Otter and environmental data. Lastly, core areas for conservation was selected by comparing and synthesizing stream naturalness map and habitat suitability map. The selected core areas showed several characteristics. The number of artificial facilities is low in the core areas. Rocks which are preferred by Eurasian Otter to eat and excrete are plentiful in the core areas. Also, the ratio of adjacent farmland is high. Based on the analyses, it is expected that this study can contribute to decision making process for environmental spatial plans to better conserve habitats of Eurasian Otter.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1527-1530
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• 2002

Video summary is one of the tools which can provide the fast and effective browsing fur a lengthy video. Video summary consists of many key-frames that could be defined differently depending on the video genre it belongs to. Consequently, the video summary constructed by the uniform manner might lead into inadequate result. Therefore, identifying the video genre is the important first step in generating the meaningful video summary. We propose a new method that can classify the genre of the video data in MPEG compressed bit-stream domain. Since the proposed method operates directly on the com- pressed bit-stream without decoding the frame, it has merits such as simple calculation and short processing time. In the proposed method, only the visual information is utilized through the spatial-temporal analysis to classify the video genre. Experiments are done for 6 genres of video: Cartoon, Commercial, Music Video, News, Sports, and Talk Show. Experimental result shows more than 90% of accuracy in genre classification for the well-structured video data such as Talk Show and Sports.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.101-104
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• 2007

Efficient Query processing and optimization are critical for reducing network traffic and decreasing latency of query when accessing and manipulating sensor data of large-scale sensor networks. Currently it has been studied in sensor database projects. These works have mainly focused on in-network query processing for sensor networks and assumes homogeneous sensor networks, where each sensor network has same hardware and software configuration. In this paper, we present a framework for efficient query processing over heterogeneous sensor networks. Our proposed framework introduces query processing paradigm considering two heterogeneous characteristics of sensor networks: (1) data dissemination approach such as push, pull, and hybrid; (2) query processing capability of sensor networks if they may support in-network aggregation, spatial, periodic and conditional operators. Additionally, we propose multi-query optimization strategies supporting cross-translation between data acquisition query and data stream query to minimize total cost of multiple queries. It has been implemented in WSN middleware, COSMOS, developed by ETRI.

• 한국공간정보시스템학회 논문지
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• 제11권1호
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• pp.43-54
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• 2009

최근 인간 중심의 미래 컴퓨터 환경인 유비쿼터스 컴퓨팅 환경 실현을 위한 기술의 연구 개발이 활발히 진행됨에 따라 시공간 데이타를 다루는 GIS 기술이 대두되고 있다. 또한, 다양한 이기종 환경에서 호환성을 제공하기 위해서 생성된 데이타를 가공하여 사용자에게 원만하게 서비스를 제공하기 위한 미들웨어의 필요성이 증가되고 있다. 이와 같은 미들웨어의 핵심 기술로는 위치 측위 시스템으로부터 끊임없이 연속으로 들어오는 데이타 스트림을 실시간으로 처리하는 기술과 다양한 컴퓨팅 디바이스간의 데이타 동기화를 위한 기술이 요구된다. 하지만, 기존의 데이타 스트림 처리 기술은 비시공간 데이타를 대상으로 개발되었기 때문에 시공간 데이타에 대한 질의 처리가 효율적으로 지원되지 않는 문제점이 있다. 따라서, 본 논문에서는 모바일 시공간 DBMS(DataBase Management System)와 서버 시공간MMDBMS (Main Memory DBMS)간의 상호운용성을 제공하기 위한 시공간 미들웨어를 설계 및 구현하였다. 시공간 미들웨어는 끊임없이 연속으로 들어오는 시공간 데이타 스트림을 실시간으로 처리하고 시공간 DBMS간의 양방향 동기화를 지원하여 이기종 장치들간의 호환성을 유지하고 질의 처리를 하는데 있어 데이타의 무결성을 보장한다. 또한, 각 시공간 DBMS와 연결된 세션의 상태를 관리하고, 시공간 미들웨어가 안정적으로 작동될 수 있기 위한 자원 관리 기능을 제공한다. 마지막으로, 본 논문에서는 시공간 미들웨어를 실시간 위치추적 시스템에 적용해 봄으로써 시공간 미들웨어의 효용성을 입증하였다.

• ETRI Journal
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• 제31권4호
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• pp.365-375
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• 2009

In this paper, a terrestrial digital multimedia broadcasting (T-DMB) multichannel audio broadcasting system based on spatial audio coding is presented. The proposed system provides realistic multichannel audio service via T-DMB with a small increase of data rate as well as backward compatibility with the conventional stereo-based T-DMB player. To reduce the data rate for additional multichannel audio signals, we compress the multichannel audio signals using the sound source location cue coding algorithm, which is an efficient parametric multichannel audio compression technique. For compatibility, we use the dependent property of an elementary stream descriptor, and this property should be ignored in a conventional T-DMB player. To verify the feasibility of the proposed system, we implement the T-DMB multichannel audio encoder and a prototype player. We perform a compatibility test using the T-DMB multichannel audio encoder and conventional T-DMB players. The test demonstrates that the proposed system is compatible with a conventional T-DMB player and that it can provide a promisingly rich audio service.

• Spatial Information Research
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• 제13권1호
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• pp.43-53
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• 2005

본 연구에서는 폐쇄성 수역에 있어서 비점 오염원의 모델링 및 적정 수환경 관리방안에 대하여 고찰하였다 공간적으로 분포하는 각종 환경정보를 효과적으로 얻기 위하여 GIS데이터(contour data)를 이용하였다. 등고선 데이터로부터 소유역 및 하도망을 자동적으로 도출하였으며, 준 수치고도모델(Quasi Digital Elevation Model)을 모형화함으로써 유역으로부터의 질소 오염물질 유출량을 해석하였다. 본 모형은 실측자료를 토대로 유효화하였다. GIS와 연계한 본 모형은 수역의 오염현황을 고려한 유역의 비점 오염원유출 분석에 효과적이며, 향후 수 환경 관리에 적절하게 이용될 것으로 기대한다.

• 대한공간정보학회지
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• 제6권1호
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• pp.75-90
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• 1998

본 연구에서는 하천수질관리 방안의 일환으로 수질 및 오염원등의 환경정보에 대한 데이터베이스를 구축하고, 특히 하천의 유기오염 상태를 나타내는 지표인 BOD를 중심으로 GSIS환경하에서 시간과 지점에 따라 변화되는 사항을 수치적으로는 물론 시각적으로 Simulation하였다. 또한 각종 환경관련정보의 테이터베이스 구축과 동시에 검색, 통계, 분석등에 목적을 두고 있다. 본 연구의 결과를 이용하면 일반인에게 하천의 오염상태를 쉽게 보고 이해 할 수 있게 하여 환경에 대한 관심도를 높이는 데 도움을 줄 수 있으며 돌발적인 수결오염의 발생시 대상지역 및 영향의 정도를 신속하게 파악할 수 있다. 그리고 각 지역간의 오염원현황 및 발생오염부하량의 원활한 비교와 파악이 가능하고 각 오염인자에 의한 하천의 오염의 정도를 파악할 수 있어 이에 대한 적절한 오염량 저감대책 수립의 한 기준으로 사용될 수 있을 것으로 기대된다.

• 한국물환경학회지
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• 제25권2호
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• pp.311-321
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• 2009

Long-Term Hydrologic Impact Assessment (L-THIA) was modified to improve runoff and pollutant load prediction for Korean watersheds with changes in land use classification and event mean concentration produced from observed data in Korea. The L-THIA model was linked with SCE-UA, which is one of the global optimization techniques, to automatically calibrate direct runoff. Modified L-THIA model was applied to Gumho River Basins to analyze spatial distribution of nonpoint source pollution. The results of model calibration during 1991~2000 and validation during 1981~1990 for direct runoff represented high model efficiency of 0.76 for calibration and 0.86 for validation. As a results of spatial analysis of nonpoint source pollution, the BOD was mainly loaded from urban area but SS, TN, and TP from agricultural area which is mainly located along the stream. Modified L-THIA model improve its accuracy with minimum imput data and application efforts. From this study, we can find out the L-THIA model is very useful tool to predict direct runoff and pollutant loads from the watershed and spatial analysis of nonpoint source pollution.