• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.743-752
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• 2011

One of main concerns of operators of the Earth observation satellite is taking images as many as possible under the constraints of satellite resources during fixed period. In order to achieve this goal, satellite operators are strongly required to generate the optimized image collection plans, and it is a very time consuming process to achieve an optimized image collection plan when it is done by manual. This paper suggests automation of image collection planning based on the dynamic programming algorithm to reduce the time required for image collection planning. The validity of the proposed method is tested using operating satellite system and the result is given in this paper.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.459-466
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• 2012

Satellite operation is divided as user's request, image collection planning, product generation, distribution. Image collection planning is to make image collection plan of satellite to reflect user's request in proper time based on NTO (New Task Order) and AO (Archive Order) using limited satellite resources. Image collection planning has high computational cost because of considering several variables simultaneously, is to be performed identical process repeatedly. In this paper, optimization research of image collection planning is performed for efficient planning. First, formulation of image collection planning is made to require satellite image as much as possible and then Heuristic algorithm is suggested for solution of formulation.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2831-2833
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• 2000

Since the access to Station Control Computers(DCCs) is restricted to the main control room(MCR). the operating data of power plants can't be easily analyzed and effectively managed. It is possible to reduce waste of time and human energy by means of building the Remote Monitoring Network of DCCs connected to Local Area Network. automatizing collection and analysis of DCC data. gathering the operating state of power plants. and managing systematically. Furthermore. this system help preventing trip by means of analyzing the data promptly and watching main system continuously.

• Journal of Biosystems Engineering
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• v.28 no.1
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• pp.59-64
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• 2003

This study was carried out to develop database system using internet fur greenhouse. The database system consisted of group monitor, client monitor. server monitor and DBMS. The results of the study are summarized as follows. 1. The monitoring module, as data collection system for database. could monitor the state of the control device and the greenhouse environment. 2 The group monitor was connected to the house monitors by RS-485 communication method. Data received by the group monitor were sent to the server monitor and then stored in database server by TCP/IP and MIDAS. 3. The data of database consisted of on growing environment. control devices, operation and cultivation data in greenhouse. It was developed using MS-SQL server. 4. Remote monitoring of greenhouse was realized in a client/server environment. The client module. which was named as the client monitor. made requests to access the measurement data of greenhouse through the remote data module of the server monitor in internet environment.

• Journal of Sensor Science and Technology
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• v.6 no.5
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• pp.362-368
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• 1997

The remote real-time uranium concentration analysis using nitrogen laser, optode, photomultiplier and optical fiber is studied. The optode for the remote collection of uranium fluorescence is designed. The fluorescence intensity at time zero is calculated in order to exclude the quenching effect and the temperature fluctuation and used for more precise estimation. The fluorescence change is very sensitive to the uranium concentration change. The method shows the detection limit of 0.06ppm and the linearity between 0.1ppm and 2ppm of the aqueous uranium concentration.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.40-44
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• 2002

Precision correction is the process of geometrically aligning images to a reference coordinate system using GCPs(Ground Control Points). Many applications of remote sensing data, such as change detection, mapping and environmental monitoring, rely on the accuracy of precision correction. However it is a very time consuming and laborious process. It requires GCP collection, the identification of image points and their corresponding reference coordinates. At typical satellite ground stations, GCP collection requires most of man-powers in processing satellite images. A method of automatic registration of satellite images is demanding. In this paper, we propose a new algorithm for automatic precision correction by GCP chips and RANSAC(Random Sample Consensus). The algorithm is divided into two major steps. The first one is the automated generation of ground control points. An automated stereo matching based on normalized cross correlation will be used. We have improved the accuracy of stereo matching by determining the size and shape of match windows according to incidence angle and scene orientation from ancillary data. The second one is the robust estimation of mapping function from control points. We used the RANSAC algorithm for this step and effectively removed the outliers of matching results. We carried out experiments with SPOT images over three test sites which were taken at different time and look-angle with each other. Left image was used to select UP chipsets and right image to match against GCP chipsets and perform automatic registration. In result, we could show that our approach of automated matching and robust estimation worked well for automated registration.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.153-155
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• 2003

Laser scanning has become a viable technique for the collection of a large amount of accurate 3D point data densely distributed on the scanned object surface. The inherent 3D nature of the sub-randomly distributed point cloud provides abundant spatial information. To explore valuable spatial information from laser scanned data becomes an active research topic, for instance extracting digital elevation model, building models, and vegetation volumes. The sub-randomly distributed point cloud should be segmented and classified before the extraction of spatial information. This paper investigates some exist segmentation methods, and then proposes an octree-based split-and-merge segmentation method to divide lidar data into clusters belonging to 3D planes. Therefore, the classification of lidar data can be performed based on the derived attributes of extracted 3D planes. The test results of both ground and airborne lidar data show the potential of applying this method to extract spatial features from lidar data.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.549-551
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• 2003

Satellite images are utilized for various purposes and many people are concerned about them. But it is necessary to process geometric correction for using of satellite images. However, common user regards geometric correction, which is basic preprocessing for satellite image, as laborious job. Therefore we should provide an automatic geometric correction method for Landsat image using GCP chip database. The GCP chip database is the collection of pieces of images with geoinformation and is provided by XML web service. More specifically, XML web service enables common users to easily use our GCP chip database for their own geometric correcting applications.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.5-11
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• 2003

The number of the enterprises which utilize network technology has been increasing for solving problems such as productivity improvement, market trend analysis, and material collection for making decision. Especially, the management of equipment and the recovery time reduction when machines break down are very important factors in productivity improvement of the enterprise. Currently, most of the remote trouble diagnosis of equipment using the internet have just one function of transmitting the trouble information to the user. Therefore it does not directly reflect the user's recovery experience or the developer's new recovery methods. If the user's experienced recovery methods or the developer's recovery methods as well as the basic recovery methods are reflected online or on the internet, it makes it possible to recover faster than before. In this paper, we develop a Remote Monitoring Server (RMS) for chip mounters, and make it possible to reduce the recovery time by reflecting the user's experience and developer's new methods in addition to presenting the basic recovery methods. For this, trouble recovery concept will be defined. Based on this, many functions(trouble diagnosis, the presentation of the basic recovery methods, user's and developer's recovery method, counting function of the trouble number of each code, and presentation of usage number of each recovery methods) were developed. By utilizing the reports of the actual results of chip mounter and the notice function of the parts change time, the rate of operation of the chip mounter can be improved.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.39-55
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• 2019

In this study, we have proposed an improved method to detect forest fires by correcting the reflected signals of day images using the middle-wavelength infrared (MWIR) channel. The proposed method is allowed to remove the reflected signals only using the image itself without an existing data source such as a land-cover map or atmospheric data. It includes the processing steps for calculating a solar-reflected signal such as 1) a simple correction model of the atmospheric transmittance for the MWIR channel and 2) calculating the image-based reflectance. We tested the performance of the method using the MODIS product. When compared to the conventional MODIS fire detection algorithm (MOD14 collection 6), the total number of detected fires was improved by approximately 17%. Most of all, the detection of fires improved by approximately 30% in the high reflection areas of the images. Moreover, the false alarm caused by artificial objects was clearly reduced and a confidence level analysis of the undetected fires showed that the proposed method had much better performance. The proposed method would be applicable to most satellite sensors with MWIR and thermal infrared channels. Especially for geostationary satellites such as GOES-R, HIMAWARI-8/9 and GeoKompsat-2A, the short acquisition time would greatly improve the performance of the proposed fire detection algorithm because reflected signals in the geostationary satellite images frequently vary according to solar zenith angle.