• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.909-912
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• 2006

In this paper a method for remotely-sensed assessment of eutrophication was experimented. The water samples were collected for analysis of COD (chemical oxygen demand) and nutrients concentration, and the remote sensing reflectance data at the sampling points were synchronously measured using above-water method in two cruises, which were conducted in the Pearl River Estuary in January 2003 and January 2004 respectively. Based on the in-situ data the local algorithms for estimation of concentration of nutrients (P and N) and COD were developed by Partial Least Squares (PLS) regression. The algorithms were then applied to atmospheric-corrected SeaWiFS data and the COD and nutrients concentration in Pearl River Estuary were estimated. And then the assessment of eutrophication was carried out by comparison of the estimated nutrients and COD value with the water quality standard. The results show that the whole estuary is seriously in eutrophication.

• Journal of information and communication convergence engineering
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• 제8권5호
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• pp.513-518
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• 2010

This paper proposes a medium access control protocol for integrated voice and data services in slotted CDMA systems. The proposed protocol, which is named as RCSSMA (Reservation Code and Status Sensing Multiple Access), adopts a code reservation and status sensing schemes. RCSSMA protocol gives higher access priority to the voice traffic than data traffic for reducing the packet dropping probability. The voice terminal reserves an available spreading code to transmit voice packets during a talkspurt, whereas the data terminal transmits a packet over one of the available spreading codes that are not reserved by the voice terminals. In this protocol, the voice packets never contend with the data packets. Packet dropping probability and average data packet transmission delay are analyzed using a Markov chain model.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.917-919
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• 2003

This paper demonstrates that RADARSAT ScanSAR data can be an important data source of radar remote sensing for monitoring crop systems and estimation of rice yield for large areas in tropic and sub-tropical regions. Experiments were carried out to show the effectiveness of RADARSAT ScanSAR data for rice yield estimation in whole province of Guangdong, South China. A methodology was developed to deal with a series of issues in extracting rice information from the ScanSAR data, such as topographic influences, levels of agro-management, irregular distribution of paddy fields and different rice cropping systems. A model was provided for rice yield estimation based on the relationship between the backscatter coefficient of multi-temporal SAR data and the biomass of rice.

• 대한원격탐사학회지
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• 제31권6호
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• pp.513-521
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• 2015

해색 원격탐사 자료의 처리과정에서는 일반적으로 관측 영역의 확보를 위해 시공간적 합성을 수행하며, 이 때 Level-2 flag를 참조하여 합성 재료가 되는 영상의 유효성을 판단한다. NASA OBPG의 표준 알고리즘은 stray light에 의한 관측 오차를 최소화하기 위해서 필터링 윈도우를 채택하고 있으나, 이로 인한 관측 영역의 손실이 많다. 이 연구는 유효 관측 영역의 복원/확장을 통한 해색 원격탐사 자료의 품질 향상에 목적을 둔다. 이를 위해서 MODIS/Aqua의 필터링 윈도우의 크기 변화에 따른 관측 영역과 클로로필a 농도 측정값의 변화를 분석하였다. 그 결과 유효 관측 영역에 있어 Level-2 swath 자료, Level-3 일별 합성자료, 8일 합성자료, 월별 합성자료에서 각각 $13.2({\pm}5.2)%$, $30.8({\pm}16.3)%$, $15.8({\pm}9.2)%$, $6.0({\pm}5.6)%$의 복원 효과가 발생하였으며, 표준 자료와의 측정값 차이는 공통 관측 영역에서 평균 0.012% 이하로 매우 유의하였다. 또한 공간 영역 확장으로 인해 시계열 자료에서의 관측 밀도도 상승하였으며 그 이득은 8일 합성자료에서 가장 크게 나타났다. 제안 방법을 통한 유효 영역의 확장은 자료 생산의 효율성뿐만 아니라 자료 분석의 통계적 신뢰성 확보의 측면에서도 해색 원격탐사 자료의 품질 향상에 기여할 수 있다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.231-236
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• 1999

Accurate ocean surface fluxes with high resolution are critical for understanding a mechanism of global climate. However, it is difficult to derive those fluxes by using ocean observation data because the number of ocean observation data is extremely small and the distribution is inhomogeneous. On the other hand. satellite data are characterized by the high density, the high resolution and the homogeneity. Therefore, it can be considered that we obtain accurate ocean surface by using satellite data. Recently we constructed ocean surface data sets mainly using satellite data. The data set is named by Japanese Ocean Flux data sets with Use of Remote sensing Observations (J-OFURO). Here, we introduce J-OFURO. The data set includes shortwave radiation, longwave radiation, latent heat flux, sensible heat flux, and momentum flux etc. Moreover, sea surface dynamic topography data are included in the data set. Radiation data sets covers western Pacific and eastern Indian Ocean because we use a Japanese geostationally satellite (GMS) to estimate radiation fluxes. On the other hand, turbulent heat fluxes are globally estimated. The constructed data sets are used and shows the effectiveness for many scientific studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권2호
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• pp.209-218
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• 2009

In a wireless sensor network(WSN) each sensor node deals with numerous sensing data elements. For the sake of energy efficiency and network lifetime, sensing data must be handled effectively. A technique used for this is data aggregation. Sending/receiving data involves numerous steps such as MAC layer control packet handshakes and route path setup, and these steps consume energy. Because these steps are involved in all data communication, the total cost increases are related to the counts of data sent/received. Therefore, many studies have proposed sending combined data, which is known as data aggregation. Very effective methods to aggregate sensing data have been suggested, but there is no means of deciding how long the sensor node should wait for aggregation. This is a very important issue, because the wait time affects the total communication cost and data reliability. There are two types of data aggregation; the data counting method and the time waiting method. However, each has weaknesses in terms of the delay. A hybrid method can be adopted to alleviate these problems. But, it cannot provide an optimal point of aggregation. In this paper, we suggest a stochastic-based data aggregation scheme, which provides the cost(in terms of communication and delay) optimal aggregation point. We present numerical analysis and results.

• Journal of Ecology and Environment
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• 제34권2호
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• pp.149-156
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• 2011

Phenological variables derived from remote sensing are useful in determining the seasonal cycles of ecosystems in a changing climate. Satellite remote sensing imagery is useful for the spatial continuous monitoring of vegetation phenology across broad regions; however, its applications are substantially constrained by atmospheric disturbances such as clouds, dusts, and aerosols. By way of contrast, a tower-based ground remote sensing approach at the canopy level can provide continuous information on canopy phenology at finer spatial and temporal scales, regardless of atmospheric conditions. In this study, a tower-based ground remote sensing system, called the "Phenological Eyes Network (PEN)", which was installed at the Gwangneung Deciduous KoFlux (GDK) flux tower site in Korea was introduced, and daily phenological progressions at the canopy level were assessed using ratios of red, green, and blue (RGB) spectral reflectances obtained by the PEN system. The PEN system at the GDK site consists of an automatic-capturing digital fisheye camera and a hemi-spherical spectroradiometer, and monitors stand canopy phenology on an hourly basis. RGB data analyses conducted between late March and early December in 2009 revealed that the 2G_RB (i.e., 2G - R - B) index was lower than the G/R (i.e., G divided by R) index during the off-growing season, owing to the effects of surface reflectance, including soil and snow effects. The results of comparisons between the daily PEN-obtained RGB ratios and daily moderate-resolution imaging spectroradiometer (MODIS)-driven vegetation indices demonstrate that ground remote sensing data, including the PEN data, can help to improve cloud-contaminated satellite remote sensing imagery.

• Smart Structures and Systems
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• 제7권2호
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• pp.83-102
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• 2011

As a testbed for various structural health monitoring (SHM) technologies, a super-tall structure - the 610 m-tall Guangzhou Television and Sightseeing Tower (GTST) in southern China - is currently under construction. This study aims to explore state-of-the-art wireless sensing technologies for monitoring the ambient vibration of such a super-tall structure during construction. The very nature of wireless sensing frees the system from the need for extensive cabling and renders the system suitable for use on construction sites where conditions continuously change. On the other hand, unique technical hurdles exist when deploying wireless sensors in real-life structural monitoring applications. For example, the low-frequency and low-amplitude ambient vibration of the GTST poses significant challenges to sensor signal conditioning and digitization. Reliable wireless transmission over long distances is another technical challenge when utilized in such a super-tall structure. In this study, wireless sensing measurements are conducted at multiple heights of the GTST tower. Data transmission between a wireless sensing device installed at the upper levels of the tower and a base station located at the ground level (a distance that exceeds 443 m) is implemented. To verify the quality of the wireless measurements, the wireless data is compared with data collected by a conventional cable-based monitoring system. This preliminary study demonstrates that wireless sensing technologies have the capability of monitoring the low-amplitude and low-frequency ambient vibration of a super-tall and slender structure like the GTST.

• 한국화재소방학회논문지
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• 제23권6호
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• pp.75-81
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• 2009

화재감지 데이터 전송에 있어서 기존의 유선기반의 전송선로보다 설치에 용이하고 다양한 정보수집에 효율성이 높은 무선기반의 USN망이 대안으로 제시되고 있다. 그러나 USN망 구축에 사용되는 센서노드의 무선전송거리 및 정보의 신뢰성에 대해서는 문제점이 대두되고 있다. 본 연구에서는 국제적 표준규격 지그비 프로토콜을 사용하여 센서노드를 구현하였다. 제안한 센서노드 사이에 전송거리 및 수신된 정보의 신뢰성을 검증하고자 테스트 전압 3V와 5V를 센서노드 입력단자에 인가하고, 실내에서 10m씩 거리를 증가시켜 실험한 결과 최대 유효전송거리가 90m 내외임을 확인하였다. 또한, Mesh Routing 중계센서노드를 사용했을 때 전송거리에는 제한이 없었다. 제안한 센서노드로 USN망을 구축하고 실제 화재감지센서를 센서노드 입력단자에 연결하여 전송하였을 때 센서에서 직접측정 한 데이터와 USN망으로 전송하여 수집된 화재감지데이터가 잘 일치하였다. 따라서 제안한 센서노드의 화재감지정보 전송용 USN망 구축에 있어서 전송거리 및 정보의 신뢰성이 확인 되었다.

• 전기전자학회논문지
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• 제26권3호
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• pp.341-348
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• 2022

Wi-Fi가 거의 모든 곳에서 사용이 가능한 환경이 도래하면서 Wi-Fi 기반의 센싱 시스템의 활용가능성에 대한 학계의 주목과 함께 활발한 연구가 진행되고 있다. 최근에는 채널 상태 정보(CSI)를 활용한 딥러닝 기술의 비약적 발달로 높은 감지 성능을 달성하고 있다. 하지만, 새로운 대상 도메인에 적용하기 위해서는 명시적인 데이터 수집 및 모델 재학습 과정의 값비싼 적응 노력 없이는 여전히 실질적으로는 사용하기가 어렵다. 본 연구에서는 딥러닝 기반의 Wi-Fi 센싱 시스템을 위한 훈련데이터 수집 및 레이블링을 자동으로 진행하는 CSI 자동 레이블링 시스템(CALS)를 제안한다. 제안 시스템은 CSI 데이터 수집 과정에서 컴퓨터 비전 기술을 함께 활용하여, 지도학습용으로 수집된 CSI 데이터에 대한 레이블링을 자동으로 수행토록 하였다. CALS의 효율성을 보이기 위해 라즈베리파이를 이용하여 프로토타입 시스템을 구현하고, 실내 환경에서의 사람 존재 감지를 수행하는 3가지 모델에 대해 학습과 평가를 진행하였다. 자동 수집된 데이터를 진행하여 학습을 활용하는 방식으로 실시간 데이터에 대해 평가를 진행했을 때 90% 이상의 높은 정확도를 달성하였다.