• Spatial Information Research
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• v.22 no.5
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• pp.1-8
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• 2014

Globally, mobile, cloud computing or big data are the recent marketable key terms. These trend technologies or paradigm in the ICT (Information Communication Technology) fields exert large influence on the most application fields including geo-spatial applications. Among them, cloud computing, though the early stage in Korea now, plays a important role as a platform for other trend technologies uses. Especially, mobile cloud, an integrated platform with mobile device and cloud computing can be considered as a good solution to overcome well known limitations of mobile applications and to provide more information processing functionalities to mobile users. This work is a case study to design and implement the mobile application system for geo-spatial image filtering processing operated on mobile cloud platform built using OpenStack and various open sources. Filtering processing is carried out using R environment, recently being recognized as one of big data analysis technologies. This approach is expected to be an element linking geo-spatial information for new service model development and the geo-spatial analysis service development using R.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.161-167
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• 2021

This paper presents the method to quantitatively evaluate the uncertainty of the semi-empirical Bidirectional Reflectance Distribution Function (BRDF) model for Himawari-8/AHI. The uncertainty of BRDF modeling was affected by various issues such as assumption of model and number of observations, thus, it is difficult that evaluating the performance of BRDF modeling using simple uncertainty equations. Therefore, in this paper, Monte-Carlo method, which is most dependable method to analyze dynamic complex systems through iterative simulation, was used. The 1,000 input datasets for analyzing the uncertainty of BRDF modeling were generated using the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) Radiative Transfer Model (RTM) simulation with MODerate Resolution Imaging Spectroradiometer (MODIS) BRDF product. Then, we randomly selected data according to the number of observations from 4 to 35 in the input dataset and performed BRDF modeling using them. Finally, the uncertainty was calculated by comparing reproduced surface reflectance through the BRDF model and simulated surface reflectance using 6S RTM and expressed as bias and root-mean-square-error (RMSE). The bias was negative for all observations and channels, but was very small within 0.01. RMSE showed a tendency to decrease as the number of observations increased, and showed a stable value within 0.05 in all channels. In addition, our results show that when the viewing zenith angle is 40° or more, the RMSE tends to increase slightly. This information can be utilized in the uncertainty analysis of subsequently retrieved geophysical variables.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.589-593
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• 2013

Sea Surface Temperature (SST) is the temperature close to the ocean's surface and affects the Earth's atmosphere as an important parameter for the climate circulation and change. The SST from satellite still has biases from the error in specifying retrieval coefficients from either forward modeling or instrumental biases. So in this paper, we performed sensitivity analysis using input parameter of the SST to notice that the SST is most affected among the input parameter. We used Infrared (IR) data from the Communication, Ocean, and Meteorological Satellite (COMS)/Meteorological Imager (MI) from April 2011 to March 2012. We also used the Global Space-based Inter-Calibration System (GSICS) correction to quality of the IR data from COMS. SST was calculated by substituting the input parameters; IR data with or without the GSICS correction. The results of this sensitivity analysis, the SST was sensitive from -0.0403 to 0.2743 K when the IR data were changed by the GSICS corrections.

• Journal of the Korean Society for information Management
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• v.30 no.2
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• pp.143-167
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• 2013

There are increasing needs for complex information services for user of cultural heritage institution recently. And the concept of "Larchiveum", merging of functions of libraries, archives and museums, is suggested in United States and researches associated with this concept are progressed on Korean information science. At present, however, the larchiveum has not been materialized, and hence researches focus on theoretical frameworks. Therefore, this study establishes plans for an analysis with planning of institutions that libraries, archives and museums are remodeled into larchiveum. Methodologically, the research processes of existing larchiveum spatial planning are specified. More realistic implementing measures for larchiveum spatial planning are suggested through utilization of related law & guidelines as analysis tools.

• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.387-397
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• 2008

Recently many researches on data analysis using spatial statistics have been studied in various field and the studies on small area estimations using spatial statistics are in actively progress. In analysis of lattice data, defining the neighborhood information system is the most crucial procedure because it also determines the result of the analysis. However the used neighborhood informal ion system is generally defined by sharing the common border lines of small areas. In this paper the other neighborhood information systems are introduced and those systems are compared with Moran's I statistic and for the comparisons, Economic Active Population Survey (2001) is used.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.225-230
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• 2016

Dam is built to supply water necessary for life stably and reduce the damage caused by heavy rains. Recently there has been required the analysis and utilization of spatial information on the area around the dam because construction of the dam gives a great impact on the environment of the surrounding area. In this study, we build spatial information about the submerged district due to dam construction using drone and propose the effective method for analysis of the spatial information. As a result, orthoimage and DSM of study area were constructed effectively. Change of submerged district of this area was calculated according to the analysis of spatial information. Building and analyzing spatial information carried out in this study are expected to be utilized as the basis in related fields.

• Spatial Information Research
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• v.8 no.2
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• pp.243-255
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• 2000

The spatial distribution characteristics and patterns of geographic features in space can be understood through a variety of analysis techniques. The scale is one of most important factors in spatial analysis techniques. This study is aimed at identifying the characteristics of spatial data with a coarser spatial resolution and finding procedures for spatial resolution in operational scale. To achieve these objectives, this study selected LANSAT TM imagery for Sunchon Bay, a coastal wetland for a study site, applied the indices for representing scale characteristics with resolution, and compared those indices. Local variance and fractal dimension developed by previous studies were applied to measure the textual characteristics. In this study, Moran s I was applied to measure spatial pattern change of variance data which were generated from the process of coarser resolution. Drawing upon the Moran s I of variancedata was optimum technique for analysing spatial structure than those of previous studies (local variance and fractal dimension). When the variance data represents maximum Moran´s I at certainly resolution, spatial data reveals maximum change at that resolution. The optimum resolution for spatial data can be explored by applying these results.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1193-1202
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• 2018

It is important to quantitatively analyze the energy budget for understanding of long-term climate change in Arctic. High-quality and long-term radiative parameters are needed to understand the energy budget. Since most of radiative flux components based on satellite are provide for a short period, several data must be used together. It is important to acquaint differences between data to link for conjunction with several data. In this study, we investigated the comparative analysis of Arctic radiative flux product such as CERES and GEWEX to provide basic information for data linkage and analysis of changes in Arctic climate. As a result, GEWEX was underestimated the radiative variables, and it difference between the two data was about $3{\sim}25W/m^2$. In addition, the difference in high-latitude and sea ice regions have increased. In case of comparing with monthly means, the other variables except for longwave downward flux represent high difference of $9.26{\sim}26.71W/m^2$ in spring-summer season. The results of this study can be used standard data for blending and selecting GEWEX and CERES radiative flux data due to recognition of characteristics according to ice-ocean area, season, and regions.

• Spatial Information Research
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• v.23 no.3
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• pp.45-54
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• 2015

Since the V-World, the Spatial Information Open Platform service, has started in 2012, a lot of people have increased explosively every year with their interest. It is necessary to know the specific service status in order to serve as indicators of the improvement of user's environment and the service to be added in the future based on the user's increasing need. However, there is difficulty to figure out more specific service status, such as the usage of hardware resources for 2D / 3D / Portal services and the actual user usage patterns, because the current system does not have the real-time monitoring system. Therefore, in this paper, through the analysis of the usage of system resources for 2D / 3D / Portal services based on web server log and the usage of hardware resources such as CPU, Memory based on system log, we analyze the usage of service in 2015 and compare with the results of the 2014, to present problems of the current system and the solutions about the problems.

• Spatial Information Research
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• v.23 no.4
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• pp.1-11
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• 2015

Since the Spatial Information Open Platform service started in January 2012, the number of service users and the size of the system has increased significantly. However, we could not know the analysis result about how much the hardware resources of the Open Platform system can handle user services. Thereafter, whenever the number of service users are rapidly increased, we simply have solved the service delays using the hardware extension. So, this study presents the obvious solution to avoid the same problem in the future, by pinpointing the system performance of the Open Platform. In this study, through the performance analysis of hardware using NMON and the load test of web service using nGrinder, we intend to get an accurate performance of the Open Platform system. Then we intend to present the resource reallocation method in order to provide better performance of the system.