• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1149-1151
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• 2003

We performed a validation study of the MODIS active fire detection algorithm using high resolution SPOT image as the reference data set. Fire with visible smoke plumes are detected in the SPOT scenes, while the hotspots in MODIS data are detected using NASA's new version 4 fire detection algorithm. The detection performance is characterized by the commission error rate (false alarms) and the omission error rate (undetected fires). In the Sumatra and Kalimantan study area, the commission rate and the omission rate are 27% and 34% respectively. False alarms are probably due to recently burnt areas with warm surfaces. False negative detection occur where there are long smoke plumes and where fires occur in densely vegetated areas.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.2
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• pp.95-99
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• 2005

This paper presents an accurate recovery method of the reference clock which is needed for network synchronization in two-way satellite multimedia systems compliant with DVB-RCS specification and which use closed loop method for burst synchronization. In these systems, the remote station transmits TDMA burst via return link. For burst synchronization, it obtains reference clock from program clock reference (PCR) defined by MPEG-2 system specification. The PCR is generated periodically at the hub system by sampling system clock which runs at 27MHz $\pm$ 30ppm. Since the reference clock is recovered by means of digital PLL(DPLL) using imprecise PCR values due to variable random jitter, the recovered clock frequency of remote station doesn't exactly match reference clock of hub station. We propose a robust recovery method of reference clock against random delay jitter The simulation results show that the recovery error is remarkably decreased from 5 clocks to 1 clock of 27MHz relative to the general DPLL recovery method.

• Korean Journal of Remote Sensing
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• v.31 no.1
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• pp.1-9
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• 2015

Mobility and cloud platform have become the dominant paradigm to develop web services dealing with huge and diverse digital contents for scientific solution or engineering application. These two trends are technically combined into mobile cloud computing environment taking beneficial points from each. The intention of this study is to design and implement a mobile cloud application for remotely sensed image fusion for the further practical geo-based mobile services. In this implementation, the system architecture consists of two parts: mobile web client and cloud application server. Mobile web client is for user interface regarding image fusion application processing and image visualization and for mobile web service of data listing and browsing. Cloud application server works on OpenStack, open source cloud platform. In this part, three server instances are generated as web server instance, tiling server instance, and fusion server instance. With metadata browsing of the processing data, image fusion by Bayesian approach is performed using functions within Orfeo Toolbox (OTB), open source remote sensing library. In addition, similarity of fused images with respect to input image set is estimated by histogram distance metrics. This result can be used as the reference criterion for user parameter choice on Bayesian image fusion. It is thought that the implementation strategy for mobile cloud application based on full open sources provides good points for a mobile service supporting specific remote sensing functions, besides image fusion schemes, by user demands to expand remote sensing application fields.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.257-268
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• 2024

Drone-mounted hyperspectral sensors (DHSs) have revolutionized remote sensing in agriculture by offering a cost-effective and flexible platform for high-resolution spectral data acquisition. Their ability to capture data at low altitudes minimizes atmospheric interference, enhancing their utility in agricultural monitoring and management. This study focused on addressing the challenges of radiometric and geometric distortions in preprocessing drone-acquired hyperspectral data. Radiometric correction, using the empirical line method (ELM) and spectral reference panels, effectively removed sensor noise and variations in solar irradiance, resulting in accurate surface reflectance values. Notably, the ELM correction improved reflectance for measured reference panels by 5-55%, resulting in a more uniform spectral profile across wavelengths, further validated by high correlations (0.97-0.99), despite minor deviations observed at specific wavelengths for some reflectors. Geometric correction, utilizing a rubber sheet transformation with ground control points, successfully rectified distortions caused by sensor orientation and flight path variations, ensuring accurate spatial representation within the image. The effectiveness of geometric correction was assessed using root mean square error(RMSE) analysis, revealing minimal errors in both east-west(0.00 to 0.081 m) and north-south directions(0.00 to 0.076 m).The overall position RMSE of 0.031 meters across 100 points demonstrates high geometric accuracy, exceeding industry standards. Additionally, image mosaicking was performed to create a comprehensive representation of the study area. These results demonstrate the effectiveness of the applied preprocessing techniques and highlight the potential of DHSs for precise crop health monitoring and management in smart agriculture. However, further research is needed to address challenges related to data dimensionality, sensor calibration, and reference data availability, as well as exploring alternative correction methods and evaluating their performance in diverse environmental conditions to enhance the robustness and applicability of hyperspectral data processing in agriculture.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.297-305
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• 2001

Ocean satellite altimetry-implied free-air gravity anomalies have had the shortest wavelengths removed during the processing to generate the optimal solution between multiple radar altimeter missions. ERS-1 168day mission altimetry was residualized to a reference geoid surface generated by integrating Anderson & Knudsen’s free-air gravity anomalies for the Barents Sea. The altimetry tracks were reduced and filtered to extract the shortest wavelengths (between 4 and 111 km) from both ascending and descending tracks, respectively. These data were recombined using existing quadrant-swapping techniques in the wavenumber domain to generate a correlated, high frequency gravity field related to the local geologic sources. This added-value surface adjusted the reference free-air gravity anomalies to better reflect features in the gravity field at a wavelength related to the distance between altimetry ground tracks.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.4 no.1
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• pp.1-10
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• 2008

A magnetotelluric survey and geological survey have been performed to delineate deeply extended fracture systems at the geothermal field in Seokmo Island, Inchon, Korea. One borehole(BH-1) succeed to meet a large fracture system at the depth of 750 m where approximately $72^{\circ}C$ geothermal water is overflowing, while the other borehole(BH-2), which is about 200 m eastward from BH-1, failed to develop enough geothermal water even at the depth of 1,200m. Though there have been so many electric noise sources around the survey region, good quality of MT data above 1 Hz could be obtained with careful installation, remote reference processing. Inversion of MT data for two lines roughly perpendicular to the two major lineaments respectively show that the two lineaments are related to the fracture systems that are extended at least down to 1.5 km depth and inclined eastwards. From the interpretation, additional drilling for BH-2 is recommended and finally meet the fracture systems at the depth of 1,280 m and resulted in overflow of large amount of geothermal water of temperature $69.4^{\circ}C$ from BH-2.

• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.345-352
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• 2007

Two-dimensional (2D) MT surveys near the Century mine in Australia have been performed with very far remote reference in Esashi, Japan (RR_ESS) as well as Gregory Downs (RR_GREG), which are roughly 6,400 km and 80 km apart from the survey area, respectively. Good quality of MT data could be obtained by remote reference processing with RR_GREG, while the coherency of magnetic fields between field sites and RR_ESS was not sufficient to be used as remote data. Both 2D and 3D inversion of 2D profile data represented the general geological structure beneath the survey area. The main target of the survey, Termite Range Fault, appeared as a boundary between a conductive block to the north and a resistive block to the south in the reconstructed resistivity section, and is inclined slightly to the north-east direction.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.349-354
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• 1998

The grid reference system (GRS) has been useful for identifying the geographical location of satellite images. In this study we derive a GRS for the KOMPSAT Electro-Optical Camera (EOC) images. The derivation substantially follows the way that SPOT defines for its GRS, but incorporates the KOMPSAT orbital characteristics. The KOMPSAT EOC GRS (KEGRS) is designed to be a (K,J) coordinate system. The K coordinate parallel to the KOMPSAT ground track denotes the relative longitudinal position and the J coordinate represents the relative latitudinal position. The numbering of K begins with the prime meridian of K=1 with K increasing eastward, and the numbering of J uses a fixed value of J=500 at all center points on the equator with J increasing northward. The lateral and vertical intervals of grids are determined to be 12.5 km about at the 38$^{\circ}$ latitude to allow some margins for the value-added processing. The above design factors are being implemented in a satellite programming module of the KOMPSAT Receiving and Processing System (KRPS) to facilitate the EOC data collection planning over the Korean peninsula.

• Korean Journal of Remote Sensing
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• v.28 no.3
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• pp.319-327
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• 2012

In this paper, we introduce a newly developed photogrammetric software for automatic generation of high quality geo-products and its performance assessment carried out using various satellite images. Our newly developed software provides the latest techniques of an optimized sensor modelling, ortho-image generation and automated Digital Elevation Model (DEM) generation for diverse remote sensing images. In particular, images from dual- and multi-sensor images can be integrated for 3D mapping. This can be a novel innovation toward a wider applicability of remote sensing data, since 3D mapping has been limited within only single-sensor so far. We used Kompsat-2, Ikonos, QuickBird, Spot-5 high resolution satellite images to test an accuracy of 3D points and ortho-image generated by the software. Outputs were assessed by comparing reliable reference data. From various sensor combinations 3D mapping were implemented and their accuracy was evaluated using independent check points. Model accuracy of 1~2 pixels or better was achieved regardless of sensor combination type. The high resolution ortho-image results are consistent with the reference map on a scale of 1:5,000 after being rectified by the software and an accuracy of 1~2 pixels could be achieved through quantitative assessment. The developed software offers efficient critical geo-processing modules of various remote sensing images and it is expected that the software can be widely used to meet the demand on the high-quality geo products.

• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.37-48
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• 1994

In spatial information processing, particularly in non-renewable resource exploration, the spatial data sets, including remote sensing, geophysical and geochemical data, have to be geocoded onto a reference map and integrated for the final analysis and interpretation. Application of a computer based GIS(Geographical Information System of Geological Information System) at some point of the spatial data integration/fusion processing is now a logical and essential step. It should, however, be pointed out that the basic concepts of the GIS based spatial data fusion were developed with insufficient mathematical understanding of spatial characteristics or quantitative modeling framwork of the data. Furthermore many remote sensing and geological data sets, available for many exploration projects, are spatially incomplete in coverage and interduce spatially uneven information distribution. In addition, spectral information of many spatial data sets is often imprecise due to digital rescaling. Direct applications of GIS systems to spatial data fusion can therefore result in seriously erroneous final results. To resolve this problem, some of the important mathematical information representation techniques are briefly reviewed and discussed in this paper with condideration of spatial and spectral characteristics of the common remote sensing and exploration data. They include the basic probabilistic approach, the evidential belief function approach (Dempster-Shafer method) and the fuzzy logic approach. Even though the basic concepts of these three approaches are different, proper application of the techniques and careful interpretation of the final results are expected to yield acceptable conclusions in cach case. Actual tests with real data (Moon, 1990a; An etal., 1991, 1992, 1993) have shown that implementation and application of the methods discussed in this paper consistently provide more accurate final results than most direct applications of GIS techniques.