• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.156-156
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• 2018

The subbasin spatial scale can affect a hydrological simulation result. The objective of this study was to investigate an appropriate subbasin spatial scale for reproducing the different flow phases with the Soil and Water Assessment Tool (SWAT). Moreover, this study addressed the total hydrologic model uncertainty using the Generalized Likelihood Uncertainty Estimation (GLUE) method. The hydrologic modelling uncertainty analysis revealed that the courser subbasin spatial scale provided a relatively better coverage of most of the observations by the 95PPU. On the other hand, the finer subbasin spatial scale produced the best single simulation output closer to the observation. Moreover, most of the observed high flows were enveloped by the 95PPU while this did not happen for the low flows. The overall average performance improvement through an appropriate subbasin spatial scale for reproducing the different flow phases in the Yongdam and Gilgelabay watersheds were found to be 36% and 53%, respectively. It is, therefore, a worth that to put more effort in reproducing the different flow phases by investigating an appropriate subbasin spatial scale to improve our understanding about the frequency and magnitude of the different flow phases.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.89-99
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• 2018

Spatial downscaling is often applied to coarse scale satellite products with high temporal resolution for environmental monitoring at a finer scale. An area-to-point regression kriging (ATPRK) algorithm is regarded as effective in that it combines regression modeling and residual correction with area-to-point kriging. However, an open source tool or package for ATPRK has not yet been developed. This paper describes the development and code organization of an R-based spatial downscaling tool, named R4ATPRK, for the implementation of ATPRK. R4ATPRK was developed using the R language and several R packages. A look-up table search and batch processing for computation of ATP kriging weights are employed to improve computational efficiency. An experiment on spatial downscaling of coarse scale land surface temperature products demonstrated that this tool could generate downscaling results in which overall variations in input coarse scale data were preserved and local details were also well captured. If computational efficiency can be further improved, and the tool is extended to include certain advanced procedures, R4ATPRK would be an effective tool for spatial downscaling of coarse scale satellite products.

• Atmosphere
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• v.20 no.3
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• pp.343-353
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• 2010

A regional wind network with complex surface conditions must be designed with sufficient space and time resolution to resolve the local circulations. In this study, the spatial variations of the wind field observed in the Seoul and Jeju regional networks were evaluated in terms of annual, seasons, and months to assess the spatial homogeneity of wind fields within the regional networks. The coherency of the wind field as a function of separation distance between stations indicated that significant coherency was sometimes not captured by the network, as inferred by low correlations between adjacent stations. A meso-velocity scale was defined in terms of the spatial variability of the wind within the network. This problem is predictably most significant with weak winds, dull prevailing wind, clear skies and significant topography. The relatively small correlations between stations imply that the wind at a given point cannot be estimated by interpolating winds from the nearest stations. For the Seoul and Jeju regional network, the meso-velocity scale has typically a same order of magnitude as the speed of the network averaged wind, revealing the large spatial variability of the Jeju network station imply topography and weather. Significant scatter in the relationship between spatial variability of the wind field and the wind speed is thought to be related to thermally-generated flows. The magnitude of the mesovelocity scale was significantly different along separation distance between stations, wind speed, intensity of prevailing wind, clear and cloudy conditions, topography. Resultant wind vectors indicate much different flow patterns along condition of contributing factors. As a result, the careful considerations on contributing factors such as prevailing wind in season, weather, and complex surface conditions with topography and land/sea contrast are required to assess the spatial variations of wind field on a regional network. The results in the spatial variation from the mesovelocity scale are useful to represent the characteristics of regional wind speed including lower surface conditions over the grid scale of large scale atmospheric model.

• Journal of the Korean housing association
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• v.25 no.1
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• pp.15-22
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• 2014

In the domestic housing market, uncompleted lot-solid apartments and unoccupied residences are increasing in the medium-large scale area whose rents and transactions have been unstable, as going through the financial crisis and economical recession. Demands for small-scale housings are steadily increasing by practical consumer group who don't need large places, which are often not needed for the current people who are spending most of their time outside of their houses. Therefore, this study proposes the useful methods for spatial planning for small-scale houses for multiple households, including variable form, levels form, multi-level form, and smart-sizing. For efficient spatial planning for that purpose, here, small-scale housings are not limited to places for families with 1-2 members, but considered as one of broader approaches to graft various households and families. In addition, we examined the existed trends of researches about spatial utility of small-scale places, and did the research about the status of small-scale housing developments, and then proposed the direction for future small-scale housings by analyzing the advanced examples.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.445-454
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• 2017

The performance of spatial downscaling models depends on the quality of input coarse scale products. Thus, the impact of intrinsic errors contained in coarse scale satellite products on predictive performance should be properly assessed in parallel with the development of advanced downscaling models. Such an assessment is the main objective of this paper. Based on a synthetic satellite precipitation product at a coarse scale generated from rain gauge data, two synthetic precipitation products with different amounts of error were generated and used as inputs for spatial downscaling. Geographically weighted regression, which typically has very high explanatory power, was selected as the trend component estimation model, and area-to-point kriging was applied for residual correction in the spatial downscaling experiment. When errors in the coarse scale product were greater, the trend component estimates were much more susceptible to errors. But residual correction could reduce the impact of the erroneous trend component estimates, which improved the predictive performance. However, residual correction could not improve predictive performance significantly when substantial errors were contained in the input coarse scale data. Therefore, the development of advanced spatial downscaling models should be focused on correction of intrinsic errors in the coarse scale satellite product if a priori error information could be available, rather than on the application of advanced regression models with high explanatory power.

• Korean Institute of Interior Design Journal
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• v.23 no.3
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• pp.212-221
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• 2014

This study aims to analyze and explore phenomenological elements that appear in small-scall art museums with spatial concepts, such as top and bottom, depth, movement, and experienced space on the basis of Merleau-Ponty $Ph\acute{e}nom\acute{e}nologie$ de la perception.' Therefore, small-scale art museums may be regarded as an ideal space that can be analyzed with Merleau-Ponty's phenomenological theory since they should provide viewers with various spatial experiences in a limited space, breaking away from spatial limitations beyond appreciation of artworks. As research subjects, the range of art museums was limited to ones whose designs architectures or interior designers participated in out of all the small-scale art museums constructed after the 1990s, when the concepts and directing methods of spatial experience elements started being applied to art museums. Small-scale art museums chosen as cases were analyzed with Merleau-Ponty's spatial concepts explained earlier, and this study drew conclusions for each one. The significance of this study is that the results of this study can be used as efficient materials to reflect phenomenological elements on planning future small-scale art museums through further studies on various small-scale art museums.

• Journal of the Korean Institute of Educational Facilities
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• v.23 no.4
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• pp.3-10
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• 2016

This paper presents the investigation results on the classification of the university campuses. For the classification, we selected the spatial index as the evaluation indicator since the environmental factors and maintenance methods vary from university campus to university campus. For the study, we used eight spatial indices of the 30 national universities. This paper provides the spatial characteristics of different campus types, presents campus classification analysis as a future research approach to campus maintenance, and provides the data for the future study of comparison among universities. The results are as follows. 1) The classification investigation categorized the university campuses into three groups. Type 1 is a large-scale type, located near downtown. Type 2 is a medium-scale type, located at a remote site from downtown. Type 3 is a small-scale type, which is located comparatively near downtown. 2) Type 1 is a large-scale mixed area type, and 13 universities belong to this group. Type 2 is a medium-scale suburban area type, and six universities are in this group. Finally, Type 3 is a small-scale downtown area type, and 11 universities belong to this group.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.569-584
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• 2016

In this paper, we present a spatial knowledge extractor implemented in Hadoop MapReduce parallel, distributed computing environment. From a large spatial dataset, this knowledge extractor automatically derives a qualitative spatial knowledge base, which consists of both topological and directional relations on pairs of two spatial objects. By using R-tree index and range queries over a distributed spatial data file on HDFS, the MapReduce-enabled spatial knowledge extractor, MRSPAKE, can produce a web-scale spatial knowledge base in highly efficient way. In experiments with the well-known open spatial dataset, Open Street Map (OSM), the proposed web-scale spatial knowledge extractor, MRSPAKE, showed high performance and scalability.

• 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 System Dynamics Review
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• v.16 no.2
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• pp.75-100
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• 2015

The purpose of this study is to analyze causation of Ecosystem service's trade-off(ES trade-off) and to establish baseline data for wise spatial planning and management. In order to understand why and how ES trade-off occurs, systems thinking and causal loops were employed. The causal loop of ecosystem service creation cycle includes profits quantification process, decision making process, spatial planning and management process, and ecosystem services creation process. The profits quantification process has a limitation that all ecosystem service categories were not included in profits quantification, because quantification method for cultural services is insufficient. These problems led to unequal discussion opportunity in decision making process. ES trade-off occurs through transition of ecosystem function in spatial scale and temporal scale. In spatial scale, land-use variation and resource-use variation contribute to change an ecosystem function for different ES category by spatial planning and management. In temporal scale, a change of an ecosystem function for different ES category is influenced by ecological succession, seasonal change and land cover variation, which are parameter from environmental features. This study presented that spatial planning and management should ecosystem service assessment in order to enhance balanced ecosystem services.