• 대한원격탐사학회지
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• 제27권6호
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• pp.637-651
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• 2011

This study presents a rule-based urban image classification method for time series analysis of changes in the vicinity of Asan-si and Cheonan-si in Chungcheongnam-do, using Landsat satellite images (1991-2006). The area has been highly developed through the relocation of industrial facilities, land development, construction of a high-speed railroad, and an extension of the subway. To determine the yearly changing pattern of the urban area, eleven classes were made depending on the trend of development. An algorithm was generalized for the rules to be applied as an unsupervised classification, without the need of training area. The analysis results show that the urban zone of the research area has increased by about 1.53 times, and each correlation graph confirmed the distribution of the Built Up Index (BUI) values for each class. To evaluate the rule-based classification, coverage and accuracy were assessed. When Optimal allowable factor=0.36, the coverage of the rule was 98.4%, and for the test using ground data from 1991 to 2006, overall accuracy was 99.49%. It was confirmed that the method suggested to determine the maximum allowable factor correlates to the accuracy test results using ground data. Among the multiple images, available data was used as best as possible and classification accuracy could be improved since optimal classification to suit objectives was possible. The rule-based urban image classification method is expected to be applied to time series image analyses such as thematic mapping for urban development, urban development, and monitoring of environmental changes.

• 정보처리학회논문지C
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• 제14C권2호
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• pp.139-146
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• 2007

최근 Robomote, Robotic Sensor Agents(RSAs)와 같은 이동 센서의 등장으로 인해 이동 센서네트워크(MSN: Mobile Sensor Network)에 대한 연구가 활발히 진행되고 있다. 하지만 기존의 이동 센서네트워크에 대한 연구는 주로 기존의 고정 센서네트워크(SSN: Stationary Sensor Network)에서 발생하는 문제점인 Coverage Hole을 해결하는데 초점을 맞추고 있다. 이러한 연구들에서는 이동 센서들에게 부여된 이동 능력을 최대한 활용하지 못하는 단점을 안고 있다. 이를 해결하기 위해 이동 센서에게 지속적인 이동성을 부여함으로써 고정 센서네트워크에 비해 더 넓은 영역을 센싱하도록 제안한 연구가 있으나, 그 연구가 아직 초기 단계로써 이동 센서의 지속적인 이동으로 인한 싱크 노드로의 통신 경로선정 및 데이터 전송 문제에 대해서는 논하고 있지 않다. 이에 본 논문에서는 지속적인 이동성을 갖는 이동 센서로 구성된 이동 센서네트워크 환경에서 효율적으로 경로 설정 및 데이터 전송을 가능하게 하는 통신 프로토콜을 제안한다. 제안하는 프로토콜에서는 이동 센서와 함께 고정센서를 배치함으로써 고정 센서가 이동 센서를 대신하여 싱크 노드로 센싱 데이터를 전송하도록 한다. 시뮬레이션을 이용한 성능 평가를 통해 제안한 통신 프로토콜이 기존의 고정 센서네트워크에 비해 네트워크 커버리지 면에서 최대 40%, 트래픽 오버헤드 부분에서는 최대 76%의 성능을 향상시킴을 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권8호
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• pp.1894-1912
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• 2012

This paper proposes a system called Wireless Link based on Global Communication Channel (WLGCC) to enhance the spectrum sharing between digital broadcasting (DB) services and the cognitive radio (CR) system in the licensed band of 470-790 MHz. The WLGCC aims to enhance the spectrum sensing and geolocation database (GLD) spectrum sharing methods in the CR system. Spectrum sensing can be enhanced by receiving the status of the used frequencies from the WLGCC, thereby eliminating the need for a low detection threshold (i.e., avoiding the hidden node problem). In addition, the GLD can be enhanced by providing a reliable communication link between the database and the CR device in the form of an unused TV white space that is reserved as the proposed Global Communication Channel (GCC). This paper analyzes the coexistence of the new WLGCC system and the DB service in terms of avoiding additional interference. Specifically, we mathematically determine the WLGCC parameters, such as the in-band and out-of-band power levels, and operation coverage, and verify them using Monte Carlo simulation. The results show that WLGCC does not degrade the existing DB service and reliably transmits information of the vacant (or used) frequency bands to the CR.

• 인터넷정보학회논문지
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• 제12권4호
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• pp.1-14
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• 2011

본 논문은 전송 전력과 전송 범위가 서로 다른 이기종 무선 통신망이 경쟁 기반의 채널 접속 프로토콜을 사용하여 공존하는 경우 채널 공유의 형평성과 효율에 관해 분석한다. 먼저, 기존에 널리 사용되는 경쟁 기반의 채널 접속 메커니즘인 CSMA(Carrier Sensing Multiple Access) 프로토콜을 사용하여 채널을 공유하는 경우, 이기종 시스템간의 반송파 감지의 비대칭성과 간섭으로 인한 전송실패를 인지하지 못하는 이진 지수 백오프 메커니즘과 링크 적응 메커니즘에 의해 채널이 불공평하게 공유됨을 밝힌다. 다음으로, 공간 재사용성과 공평한 채널 공유를 동시에 보장할 수 있는 반송파 감지 문턱값의 조건을 유도하고, 통신망의 처리율에 관한 수학적인 모형을 수립하여 경쟁 윈도우와 전송 속도가 채널 공유의 형평성과 효율에 끼치는 영향을 분석한다. 마지막으로, 다양한 환경에서의 모의 실험을 수행하여 공평한 채널 공유를 위한 여러 가지 접근 방법의 채널 공유 성능을 비교한다.

• 대한원격탐사학회지
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• 제27권3호
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• pp.339-351
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• 2011

This study investigates the potentials of satellite, ground measurement data, and geo-spatial information within an urban area for the mapping of the Urban Environmental Quality (UEQ) parameters. The UEQ indicates a complex and various parameters resulting from both human and natural factors, which are greenness, climate, air pollution, the urban infrastructure, and etc. Multi-spectral remote sensing data from the Landsat ETM and TM sensors for the mapping of air pollution by the Haze Optimized Transform (HOT) technique, Urban Heat Island (UHO using the emissivity-fusion method in Seoul from 2000 to 2006 in fine resolution (30m) were analyzed for the estimation of UEQ index. Although the UHI values are similar ($8.4^{\circ}C{\sim}9.1^{\circ}C$) during these years, the spatial coverage of "hot" surface temperature (> $24^{\circ}C$) significantly increased from 2000 to 2006 due to the rapid urban development. Furthermore, high correlations between vegetation index and land surface temperature were achieved with a correlation coefficients of 0.85 (2000), 0.81 (2001), 0.84 (2002), and 0.89 (2006), respectively. It was found that the proposed method was successfully analyzed spatial structure of the UEQ and the scenarios of the best and worst areas within the city were also identified. Based on the quantifiable fine resolution satellite image parameters, UEQ can promote the understanding of the complex and dynamic factors controlling urban environment.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.159-159
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• 2023

The Amazon River basin is one of the largest basins in the world, and its ecosystem is vital for biodiversity, hydrology, and climate regulation. Thus, understanding the hydrometeorological process is essential to the maintenance of the Amazon River basin. However, it is still tricky to monitor the Amazon River basin because of its size and the low density of the monitoring gauge network. To solve those issues, remote sensing products have been largely used. Yet, those products have some limitations. Therefore, this study aims to do bias corrections to improve the accuracy of Satellite Precipitation Products (SPPs) in the Amazon River basin. We use 331 rainfall stations for the observed data and two daily satellite precipitation gridded datasets (CHIRPS, TRMM). Due to the limitation of the observed data, the period of analysis was set from 1st January 1990 to 31st December 2010. The observed data were interpolated to have the same resolution as the SPPs data using the IDW method. For bias correction, we use convolution neural networks (CNN) combined with an autoencoder architecture (ConvAE). To evaluate the bias correction performance, we used some statistical indicators such as NSE, RMSE, and MAD. Hence, those results can increase the quality of precipitation data in the Amazon River basin, improving its monitoring and management.

• 한국통신학회논문지
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• 제33권10B호
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• pp.894-903
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• 2008

일반적으로 센서들의 위치는 감시 정찰 센서 네트워크의 적용 범위, 데이터 전송 비용, 그리고 자원 관리에 영향을 미치기 때문에, 최적의 위치에 센서를 배치해야 한다. 그러나 산악 지대나 도심 지역과 같은 실 환경에 센서 노드를 배치할 경우, 센서에 영향을 미치는 다양한 지형 및 기후 요소들을 고려하기 어렵다. 따라서 이러한 다양한 환경에 센서를 배치할 경우 감시 영역 측면에서 목표 대상을 효율적으로 탐지할 수 있는 센서 배치 방법이 필요하다. 이를 위해 본 논문에서는 센서 배치와 관련된 다양한 기후와 지형 등의 환경 요소들을 분석하고, 이들 영향 요소들이 센서 노드 배치 시 활용될 수 있도록 정량화한다. 이를 바탕으로 센서 탐지 영역 측면에서 정량화된 영향 요소들을 고려함으로써 보다 실효적인 센서 배치 방법론을 제안한다. 또한 본 논문에서 제안한 센서 배치 방법론을 따르는 센서 배치 관리 시스템을 구현함으로써 제안된 방법론의 타당성을 입증한다.

• Journal of Communications and Networks
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• 제16권3호
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• pp.335-343
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• 2014

This paper considers the crucial problem of deploying wireless relays for achieving a connected wireless sensor network in indoor environments, an important aspect related to the management of the sensor network. Several algorithms have been proposed for ensuring full sensing coverage and network connectivity. These algorithms are not applicable to indoor environments because of the complexity of indoor environments, in which a radio signal can be dramatically degraded by obstacles such as walls. We first prove theoretically that the indoor relay placement problem is NP-hard. We then predict the radio coverage of a given relay deployment in indoor environments. We consider two practical scenarios; wire-connected relays and radio-connected relays. For the network with wire-connected relays, we propose an efficient greedy algorithm to compute the deployment locations of relays for achieving the required coverage percentage. This algorithm is proved to provide a $H_n$ factor approximation to the theoretical optimum, where $H_n=1+{\frac{1}{2}}+{\cdots}+{\frac{1}{n}}={\ln}(n)+1$, and n is the number of all grid points. In the network with radio-connected relays, relays have to be connected in an ad hoc mode. We then propose an algorithm based on the previous algorithm for ensuring the connectivity of relays. Experimental results demonstrate that the proposed algorithms achieve better performance than baseline algorithms.

• Ocean and Polar Research
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• 제35권4호
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• pp.395-405
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• 2013

The aim of this study is to suggest an optimal survey method for coastal habitat monitoring around Weno Island in Chuuk Atoll, Federated States of Micronesia (FSM). This study was carried out to compare and analyze differences between in situ survey (PHOTS) and high spatial satellite imagery (Worldview-2) with regard to the coastal habitat distribution patterns of Weno Island. The in situ field data showed the following coverage of habitat types: sand 42.4%, seagrass 26.1%, algae 14.9%, rubble 8.9%, hard coral 3.5%, soft coral 2.6%, dead coral 1.5%, others 0.1%. The satellite imagery showed the following coverage of habitat types: sand 26.5%, seagrass 23.3%, sand + seagrass 12.3%, coral 18.1%, rubble 19.0%, rock 0.8% (Accuracy 65.2%). According to the visual interpretation of the habitat map by in situ survey, seagrass, sand, coral and rubble distribution were misaligned compared with the satellite imagery. While, the satellite imagery appear to be a plausible results to identify habitat types, it could not classify habitat types under one pixel in images, which in turn overestimated coral and rubble coverage, underestimated algae and sand. The differences appear to arise primarily because of habitat classification scheme, sampling scale and remote sensing reflectance. The implication of these results is that satellite imagery analysis needs to incorporate in situ survey data to accurately identify habitat. We suggest that satellite imagery must correspond with in situ survey in habitat classification and sampling scale. Subsequently habitat sub-segmentation based on the in situ survey data should be applied to satellite imagery.

• Ocean and Polar Research
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• 제24권3호
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• pp.255-261
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• 2002

We investigated the distribution of sea ice using Topex/Poseidon (T/P) and ERS-1 .ada. altimeter data in the northwest Weddell Sea, Antarctica, between the area $45-75^{\circ}W\;and\;55-66^{\circ}S$. Using the Geo_Bad_1 flag of the Merged GDR of the T/P, we classified the surface into ocean, land, and sea. Total 257 cycles of altimeter measurements between Oct. 1992 and Sep. 1999 (for nearly 2570 days) were used to analyze the distribution of the Antarctic sea ice. We then calculated the surface area of ice coverage using SUTM20 map projection to monitor the periodic variations. Each year, the maximum and minimum coverage of the sea ice were found in late August and February in the study area, respectively. We also studied the sea ice distribution using ERS-1 altimeter data between $45-75^{\circ}W\;and\;55-81.5^{\circ}S$ to compare with the T/P Using the Valid/Invalid flag of the Ocean Product, we analyzed the sea ice distribution between March and August of 1995, which showed very good coherence with the T/P measurements. Our preliminary results showed that the altimeter measurements can be effectively used to monitor the distribution of the sea ice in the polar region. However, the size of radar footprint, typically 2-6km depending on the roughness of the sea surface, may be too big to monitor the sharp boundary between ice and water/land. If more other altimeter mission data with dense coverage such as Geosat GM are analyzed together, this limitation can be significantly improved. If we also combine other microwave remote sensing data such as radiometer, and SSM/I, the result will be significantly enhanced.