• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.229-229
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• 2015

Downscaling is a fundamental procedure in the assessment of the future climate change impact at regional and watershed scales. Hence, it is important to investigate the spatial variability of the climate conditions that are constructed by various downscaling methods in order to assess whether each method can model the climate conditions at various spatial scales properly. This study introduces a fundamental research from Jang and Kavvas(2015) that precipitation variability from a popular statistical downscaling method (BCSD) and a dynamical downscaling method (MM5) that is based on the NCAR/NCEP reanalysis data for a historical period and on the CCSM3 GCM A1B emission scenario simulations for a projection period, is investigated by means of some spatial characteristics: a) the normalized standard deviation (NSD), and b) the precipitation change over Northern California region. From the results of this study it is found that the BCSD method has limitations in projecting future precipitation values since the BCSD-projected precipitation, being based on the interpolated change factors from GCM projected precipitation, does not consider the interactions between GCM outputs and local geomorphological characteristics such as orographic effects and land use/cover patterns. As such, it is not clear whether the popular BCSD method is suitable for the assessment of the impact of future climate change at regional, watershed and local scales as the future climate will evolve in time and space as a nonlinear system with land-atmosphere feedbacks. However, it is noted that in this study only the BCSD procedure for the statistical downscaling method has been investigated, and the results by other statistical downscaling methods might be different.

• Journal of Biosystems Engineering
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• v.39 no.4
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• pp.377-388
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• 2014

Purpose: Determining the spatial structure of data is important in understanding within-field variability for site-specific crop management. An understanding of the spatial structures present in the data may help illuminate interrelationships that are important in subsequent explanatory analyses, especially when site variables are correlated or are a combined response to multiple causative factors. Methods: In this study, correlation, principal component analysis, and single and nested variogram models were applied to soil electrical conductivity and chemical property data of two fields in central Missouri, USA. Results: Some variables that were highly correlated, or were strongly expressed in the same principal component, exhibited similar spatial ranges when fitted with a single variogram model. However, single variogram results were dependent on the active lag distance used, with short distances (30 m) required to fit short-range variability. Longer active lag distances only revealed long-range spatial components. Nested models generally yielded a better fit than single models for sensor-based conductivity data, where multiple scales of spatial structure were apparent. Gaussian-spherical nested models fit well to the data at both short (30 m) and long (300 m) active lag distances, generally capturing both short-range and long-range spatial components. As soil conductivity relates strongly to profile texture, we hypothesize that the short-range components may relate to the scale of erosion processes, while the long-range components are indicative of the scale of landscape morphology. Conclusion: In this study, we investigated the effect of changing active lag distance on the calculation of the range parameter. Future work investigating scale effects on other variogram parameters, including nugget and sill variances, may lead to better model selection and interpretation. Once this is achieved, separation of nested spatial components by factorial kriging may help to better define the correlations existing between spatial datasets.

• The Korean Journal of Ecology
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• v.27 no.2
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• pp.79-86
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• 2004

An extensive study of the vegetation characteristics of the Hamersley Ranges, a mountainous desert area of north-west Australia, facilitated the comparison of plant species diversity measures with mountainous deserts of other parts of the world. Alpha diversity was defined as the number of species co-existing at local scales and was found to average 18 species per 0.1 ha for the Hamersley Ranges. This was found to be similar to seven other mountainous deserts in North and South America, and southern Africa. Variation in alpha diversity between these deserts was found to considerably lower than within deserts, suggesting that local processes control species richness at local scales. Beta diversity, defined here as turnover in species composition at various spatial scales, can be measured in many ways. For the Hamersley Ranges, Wilson's β ranged from 1.2 to 1.6 for five sites along a topographic gradient, whereas Whittaker's β between different plant communities was found to average 0.93. Comparable data was not found for other desert areas, but comparisons to non-desert areas suggest beta diversity within landscapes is relatively high and is likely to reflect the considerable landform heterogeneity of the Hamersley Ranges. 55∼70% of species were shared between different landscapes of the Hamersley Ranges; comparisons to other regions suggest beta diversity at this scale is relatively low. Gamma diversity, the number of species over large spatial extents, was successfully compared using regression analysis of the log-log species - area relationship. This revealed that the northern Sonoran desert has significantly less species than the Nama (inland) Karoo and Hamersley Ranges over medium spatial extents, but species numbers were similar at a regional scale. Several constraints to the valid comparison of species diversity were identified, including lack of standardisation of sampling techniques, the wide range of measures employed, general lack of published data, and the influence of the various components of spatial scale on most diversity measures. Recommendations on how to improve future comparative work are provided.

• Journal of The Korea Institute of Healthcare Architecture
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• v.20 no.3
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• pp.49-55
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• 2014

Purpose: AIn recent years, the rapid progress of aging and the increase in the elderly people with dementia is becoming a big social issue. Therefore, this paper studies the development of therapeutic environmental rating scales for the elderly people with dementia in korean nursing homes. Methods: We identify the development process and structure of TESS-NH and understand the details of its nature and features. Then, based on the detailed items, we provide major scale factors which do influence on therapeutic environmental rating scales using PCA. Results: In the results, TESS, in the case of the initial stage of TESS-NH, has an advantage to evaluate on physical environments for a short period of time. TESS-2 + sets a large rage of activities of the elderly people with dementia, and tries to evaluate ongoing cares. TESS-NH has a complete set of well-thought-out assessment features for improving quality of care (Quality of Care) On the other hand, the main factors affecting the therapeutic environmental rating scales in nursing homes are "a consideration for facility management (Care for facilities' maintenance)", "a consideration for spatial cognition (Care for spatial cognition) ", and "a consideration for the safety (Care for safety)". Implications: In the future, to develop the therapeutic environmental rating scales on Korea's dementia nursing home, we should actively consider cares of spaces and facility utilization which the residents (the elderly people with dementia) are more secure and comfortable.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.1
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• pp.4-14
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• 2005

CarboKorea and HydroKorea are the domestic projects aiming to improve our understanding of carbon and water cycles in a typical Korean forest located in a complex terrain with a watershed connected to large rivers. The ultimate goal is to provide a nowcasting of these cycles for the whole Peninsula. The basic strategy to achieve such goal is through the inter- and multi-disciplinary studies that synthesize the in-situ field observation, modeling and remote sensing technology. The challenge is the fact that natural ecosystems are nonlinear and heterogeneous with a wide range of spatio-temporal scales causing the variations of mass and energy exchanges from a leaf to landscape scales. Our paradigm now shifts from temporal variation at a point to spatial patterns and from spatial homogeneity to complexity of water and carbon at multiple scales. Yet, a large portion of our knowledge about land-atmosphere interactions has been established based on tower observations, indicating that the development of scaling logics holds the key to the success of CarboKorea and HydroKorea. Here, we review the pioneering work of FIFE (First ISLSCP Field Experiment) on scaling issues in a temperate grassland and discuss the lessons from it for the application to Gwangneung forest site.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.589-607
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• 2019

This paper presents a comprehensive overview of recent model developments and practical issues in spatial downscaling of coarse resolution satellite-derived products. First, theoretical aspects of spatial downscaling models that have been applied when auxiliary variables are available at a finer spatial resolution are outlined and discussed. Based on a thorough literature survey, the spatial downscaling models are classified into two categories, including regression-based and component decomposition-based approaches, and their characteristics and limitations are then discussed. Second, open issues that have not been fully taken into account and future research directions, including quantification of uncertainty, trend component estimation across spatial scales, and an extension to a spatiotemporal downscaling framework, are discussed. If methodological developments pertaining to these issues are done in the near future, spatial downscaling is expected to play an important role in providing rich thematic information at the target spatial resolution.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.214-216
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• 2005

• Journal of architectural history
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• v.20 no.4
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• pp.7-28
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• 2011

This study intends to investigate the measuring scales, locations and scales through arrangement plans for a research on construction plans. Through an analysis of the artifacts-measuring scales, the relation of two scales found, which further helped suppose the measuring scales applied during the foundation period. Southern dynasties-scale was still used even after the capital was transferred to Sabi till Tang-scale was introduced. Tang-scale was used for Buddhist temples mostly founded in the 7th century. On the other hand, Goguryo-scale seemed to be used almost at the same period as Southern dynasties-scale used, but it seemed that Goguryo-scale disappeared earlier than Southern dynasties-scale. The locations of Buddhist temples could be classified into mountains, flatlands and mountain valley. Buddhist temples founded in mountains were mostly small-sized, but ones located on flatlands could secure flat fields through mounding operations. In addition, through location conditions of Neungsa and Wangheungsa, it was possible to find out the district setting of Sabi Capital Castle. Finally, the expansion range of Buddhist temples were found to be towards the east and the west. As for the scales of temples according to such conditions of location, it was found a similarity in Temple sites. In general, it was possible to assume that the scales of Buddhist temples tended to be expanded along with spatial expansion and there were regular systems in Buddhist temples related to the Royal family. Through the analysis of arrangement plans between individual buildings, it was found that the basic arrangement of Gate-Pagoda-Main Hall-Lecture Hall was preserved, but the proportion of distances between individual buildings varied depending on cases. As a result, there were differences between scales of entire building sites, construction subjective influences and master plan for each location of a Buddhist temple.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1209-1219
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• 2019

For consistent vegetation monitoring, it is necessary to generate time-series vegetation index datasets at fine temporal and spatial scales by fusing the complementary characteristics between temporal and spatial scales of multiple satellite data. In this study, we quantitatively and qualitatively analyzed the prediction accuracy of time-series change information extracted from spatio-temporal fusion models of multiple satellite data for vegetation monitoring. As for the spatio-temporal fusion models, we applied two models that have been widely employed to vegetation monitoring, including a Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and an Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM). To quantitatively evaluate the prediction accuracy, we first generated simulated data sets from MODIS data with fine temporal scales and then used them as inputs for the spatio-temporal fusion models. We observed from the comparative experiment that ESTARFM showed better prediction performance than STARFM, but the prediction performance for the two models became degraded as the difference between the prediction date and the simultaneous acquisition date of the input data increased. This result indicates that multiple data acquired close to the prediction date should be used to improve the prediction accuracy. When considering the limited availability of optical images, it is necessary to develop an advanced spatio-temporal model that can reflect the suggestions of this study for vegetation monitoring.

• Journal of the Korean association of regional geographers
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• v.18 no.4
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• pp.414-432
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• 2012

Land price is a kind of text to read urban spatial structure. The purpose of this paper is to inquire into the characteristics of Daegu's urban structure and its change in time through exploring spatio-temporal variations of land price with a detailed spatial and temporal resolution. To achieve this, land value surfaces were represented using the officially assessed land price every other year from 1995 to 2011. Through mapping and exploring spatio-temporal patterns and fluctuation rates of land price for this period, changes in urban structure, the effects of local decision makings such as Greenbelt adjustment, housing site development, and gentrification, and the effects of business fluctuations or policies at global or national scales could be caught. In addition, the trends for suburbanization and multi-centric urban form could be examined from the results of a negative exponential model explaining the effect of distance from an urban center on spatial variation of land price. These results demonstrate that urban analysis using land price mirroring spatial decision making at various scales could deepen understanding for internal structure and change of a city and provide useful information for establishing regional and urban development policies and evaluating their effects.