• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.434-436
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• 2005

Analysis method using remote sensing data is one of the effective ways to research a spatial and temporal variability of the mesoscale oceanic motions. During past several decades, many researchers have been getting comprehensive results using remote sensing data with application of data fusion methods in many parts of geo-science. For this study, we took the integration and fusion of several remote sensing data, which are different data resolution, timescale and characteristics, for improving accurate analysis of variation of the Kuroshio Extension. Furthermore, we might get advanced ways to understand the variability of the Kuroshio Extension, has close relation to the spatial and temporal variation of the Kuroshio and Oyashio Current.

• Proceedings of the KSRS Conference
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• v.1
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• pp.47-50
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• 2006

Tsunami disaster caused great damages and very large victims especially when occurs in urban area along coastal region. Therefore information of evacuation in a map is very important for disaster preparedness in order to minimize the number of victims in affected area. Here, information generated from remote sensing satellite data (SPOT 5 and DEM) and secondary data (administration boundary and field survey data) are used to simulate evacuation route and to produce a map for Padang City. Vulnerability and evacuation areas are determined based on DEM. Landuse/landcover, accessibility areas, infrastructure and landmark are extracted from SPOT 5 data. All the data obtained from remote sensing and secondary data are integrated using geospatial modelling to determine evacuation routes. Finally the simulation of evacuation route in Padang City for tsunami preparedness is provided based on the parameters derived from remote sensing data such as distances from shelters, save zones, city's landmarks and the local community experiences how they can survive with the disaster.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.530-535
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• 2002

An approach for quickly updating GIS building data using high resolution remotely sensed data is proposed in this paper. High resolution remotely sensed data could be aerial photographs, satellite images and airborne laser scanning data. Data from different types of sensors are integrated in building extraction. Based on the extracted buildings and the outdated GIS database, the change-detection-template can be automatically created. Then, GIS building data can be fast updated by semiautomatically processing the change-detection-temp late. It is demonstrated that this approach is quick, effective and applicable.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1313-1315
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• 2003

This paper is dedicated to studying the quantitative analysis method with remote-sensing data in shallow geological structure reconstruction by the example of TM data in western China. A new method of computing attitude of geological contacts from remote-sensing data is developed and assessed. We generate several geological profiles with remotely derived measurements to constrain the shallow geological structure reconstruction in three dimensions.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.638-643
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• 2002

MODIS (MODerate-resolution Imaging Spectroradiometer) onboard the first Earth Observing System (EOS) satellite, Terra, was launched successfully at the end of 1999. The direct broadcast MODIS data has been received and utilized in Korea Meteorological Administration (KMA) since february 2001. This study introduces utilizations of this data, especially for the derivation of sea surface temperature (SST). To produce the MODIS SST operationally, we used a simple cloud mask algorithm and MCSST algorithm. By using a simple cloud mask algorithm and by assumption of NOAA daily SST as a true SST, a new set of MCSST coefficients was derived. And we tried to analyze the current NASA's PFSST and new MCSST algorithms by using the collocated buoy observation data. Although the number of collocated data was limited, both algorithms are highly correlated with the buoy SST, but somewhat bigger bias and RMS difference than we expected. And PFSST uniformly underestimated the SST. Through more analyzing the archived and future-received data, we plan to derive better MCSST coefficients and apply to MODIS data of Aqua that is the second EOS satellite. To use the MODIS standard cloud mask algorithm to get better SST coefficients is going to be prepared.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1006-1008
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• 2003

In this paper, we describe the development of a Southeast Asia environmental information web portal based on near real time MODIS Level 2 and higher level products generated from the direct broadcast data received at the Centre for Remote Imaging, Sensing and Processing (CRISP). This web portal aims to deliver timely environmental information to interested users in the region. Interpreted data will be provided instead of raw satellite data to reduce operational requirements on our system, and to enable users with limited bandwidths to have access to the system.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.969-969
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• 2003

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.9 no.1
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• pp.97-107
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• 1991

This paper was suggested the detailed methods on the integration of Remote Sensing and GIS for various application of two functions at the one system with making the most use of respective merits rather than make use of independent systems. It developed of algorithm about simultaneous overlay of raster and vector data for remote sensing and GIS for these objects. For test application on integration of remote sensing and GIS, it used of remote sensing data of satellite and used to topographic map of the same area for vector data acquisition of GIS application. For the practical application, it proved of effective value of integration of raster and vector data by present of useful technique with multilateral approach method through data conversion about thematic application for major application fields of remote sensing and GIS and it suggested that new application technique for integrated application of remote sensing GIS through synthetic situation analysis.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.367-372
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• 2006

Cloud detection algorithm is being developed as primary one of the 16 baseline products of CMDPS (COMS Meteorological Data Processing System), which is under development for the real-time application of data will be observed from COMS Meteorological Imager. For cloud detection from satellite data, we studied two different algorithms. One is threshold technique based algorithm, which is traditionally used, and another is artificial neural network model. MPEF scene analysis algorithm is the basic idea of threshold cloud detection algorithm, and some modifications are conducted for COMS. For the neural network, we selected MLP with back-propagation algorithm. Prototype software of each algorithm was completed and evaluated by using the MTSAT-IR and GOES-9 data. Currently the software codes are standardized using Fortran90 language. For the preparation as an operational algorithm, we will setup the validation strategy and tune up the algorithm continuously. This paper shows the outline of the two cloud detection algorithms and preliminary test results of both algorithms.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.564-564
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• 2004