• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.11-14
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• 2006

We present an overview on the observation and research for the China seas using both field experiments and multi-sensor satellite data at ORSI/OUC, covering two topics: (1) Spatial and temporal distribution of internal waves in the China Seas and retrieval of internal wave parameters; (2) Retrieval, validation, and cross-comparison of multi-sensor ocean color data as well as ocean optics in situ experiments in the East China Sea. We also present an incoherent Doppler wind lidar, developed by ORSI, and its observation for marine-atmospheric boundary layer.

• 대한임베디드공학회논문지
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• 제7권6호
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• pp.323-330
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• 2012

Wireless sensor networks need middleware system for efficiently managing the constrained resource and sensing data because they need different sensing data type and protocol to communicate with heterogeneous sensor networks. Thus this paper proposes data-centric sensor middleware for heterogeneous sensor networks. The proposed middleware have to support various query processing of user applications, high-level request of users, manage heterogeneous sensor systems and universal sensing data type for node and user application.

• 한국인터넷방송통신학회논문지
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• 제8권5호
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• pp.57-63
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• 2008

최근 센서 네트워크에서 수집된 다양한 상황 정보를 웹을 통해 지도상에 도시하는 SWE(Sensor Web Enablement) 연구가 OGC(Open Geospatial Consortium)를 중심으로 진행되고 있다. OGC SWE WG(Working Group)에서는 실시간으로 시공간에서 발생하는 영상 및 센싱 데이터 등에 대한 인코딩과 웹 서비스를 지원하는 표준을 정의하고 있다. 본 논문에서는 이동 물체에서 획득한 실시간 센싱 데이터를 도시하기 위해 지도 상의 이동 노느에 GPS 데이터와 센싱 데이터를 맵핑하여 2 차원 지도에서 위치 기반의 센성 데이터 가시화 방안을 제안한다. 이를 위해 먼저 2 차원 지도에서 위치 기반의 센싱 데이터 가시화하기 위해 위치 정보를 지도의 좌표로 변환하는 알고리즘과 처리 절차를 제시한다. 그리고 이를 검증하기 위해 이동 노드의 GPS 데이터와 센싱 데이터를 수집하여 2 차원 지도 상에서 도시하는 프로그램을 설계하고 구현한다. 이를 통하여 센서 네트워크로부터 수집된 실시간 동영상이나 센싱 데이터 정보를 웹 기반의 지도 상에서 효과적으로 가시화하는 것을 확인하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1002-1004
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• 2003

A ground-based, C-band full polarimetric mobile Scatterometer system has been developed in Malaysia with collaboration between Malaysian Centre for Remote Sensing (MACRES) and Multimedia University (MMU). The main purpose of this system is to measure and monitor backscattering coefficient, ${\sigma }^0$, for earth terrain such as paddy fields, forest and soil surfaces. This paper describes the preliminary results on radar backscatter measurement from paddy field using the mobile C-band Scatterometer system. The measurement campaign was conducted at Sungai Burung area in April 2003. Real time data were collected using four polarization modes (HH, HV, VV and VH), at various incidence angles ranging from 0$^0$ to 60$^0$. The measurement data show consistent results as compared to other reports, which verify the capability of this Scatterometer system as a useful tool for remote sensing.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1337-1339
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• 2003

In this article, a new remote sensing image fusion model based on modified Kohonen networks is given. And a new fusion rule based on modified voting rule was established. Select Shaoxing City as the study site, located at Zhejiang Province, P.R.China. The fusion experiment between Landsat TM data (30m) and IRS-C Pan data (5.8m) was performed using the given fusion method. The fusion results show that the new method can gain better result in apply ing to the lower hill area, and the whole classification accuracy was 10% higher than the basic Kohonen method. The confusion between the woodlands and the waterbodies was also diminished.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.736-739
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• 2006

While hyperspectral data are very rich in information, their processing poses several challenges such as computational requirements, noise removal and relevant information extraction. In this paper, the application of advanced scale-space filtering to selected hyperspectral bands was investigated. In particular, a pre-processing tool, consisting of anisotropic diffusion and morphological leveling filtering, has been developed, aiming to an edge-preserving smoothing and simplification of hyperspectral data, procedures which are of fundamental importance during feature extraction and object detection. Two scale space parameters define the extent of image smoothing (anisotropic diffusion iterations) and image simplification (scale of morphological levelings). Experimental results demonstrated the effectiveness of the developed scale space filtering for the enhancement and smoothing of hyperspectral remote sensing data and their advantage against watershed over-segmentation problems and edge detection.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.49-57
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• 1998

CO2 transfer velocity is one of the key parameters for CO2 flux estimation at air - sea interface. However, current studies show that significant inconsistency still exists in its estimation when using different models and remotely sensed data sets, which acts as one of the main uncertainties involved in the computation of CO2 exchange coefficient between air - sea interface. In this study, wind data collected from SSM/I and scatterometer onboard ERS-1, in conjunction with operational NOAA/AVHRR, are applied to different models for calculating CO2 exchange coefficient in the world ocean. Their interrelationship and discrepancies inherent with different models and satellite data are analyzed. Finally, the seasonal and inter-annual variation of CO2 exchanges coefficient for different ocean basins are presented and discussed.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.222-224
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• 2003

Many users want to add some their own information to data which was on the web and computer without actually needing to touch data. In remote sensing, the result data for image classification consist of image and text file in general. To overcome these inconvenience problems, we suggest the annotation method using XML language. We give the efficient annotation method which can be applied to web and viewing of image classification. We can apply the annotation for web and image classification with image and text file. The need for thesaurus construction is the lack of information for remote sensing and GIS on search engine like Empas, Naver and Google. In search engine, we can’t search the information for word which has many different names simultaneously. We select the remote sensing data from different sources and make the relation between many terms. For this process, we analyze the meaning for different terms which has similar meaning.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.331-333
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• 2003

KMA successfully began to receive and utilize the GOES-9 GVAR data since May 22nd 2003 when GOES-9 replaced the long-lived GMS-5 for Western Pacific and East Asian region until operation of MTSAT-1R in 2004. To take advantage of improvements of the GOES-9 data over the GMS-5 data, such as the increase of the temporal and spat ial resolution and addition of 3.9${\mu}$m channel, we have improved several algorithms to derive the meteorological products. Here we show two examples of algorithms, sea surface temperature and atmospheric motion vector, and preliminary results of validation of the improved algorithm.

• 대한원격탐사학회지
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• 제26권6호
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• pp.693-703
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• 2010

High spectral resolution of hyperspectral data enables analysis of complex natural phenomena that is reflected on the data nonlinearly. Although many manifold learning methods have been developed for such problems, most methods do not consider the spatial correlation between samples that is inherent and useful in remote sensing data. We propose a manifold learning method which directly combines the spatial proximity and the spectral similarity through kernel PCA framework. A gain factor caused by spatial proximity is first modelled with a heat kernel, and is added to the original similarity computed from the spectral values of a pair of samples. Parameters are tuned with intelligent grid search (IGS) method for the derived manifold coordinates to achieve optimal classification accuracies. Of particular interest is its performance with small training size, because labelled samples are usually scarce due to its high acquisition cost. The proposed spatial kernel PCA (KPCA) is compared with PCA in terms of classification accuracy with the nearest-neighbourhood classification method.