• Journal of the Economic Geographical Society of Korea
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• v.16 no.3
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• pp.458-471
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• 2013

This paper addresses the limitation of a map comparison metric entitled Figure of Merit through employing a simple land change model. The metric was originally designed to overcome limitations of other existing statistics, such as Kappa, when assessing predictive accuracy of land change models. A series of comparisons between null and predicted outcomes at multiple resolutions as well as a multi-resolution Figure of Merit analysis techniques of validation are compared for spatially segregated calibration and validation datasets. The Figure of Merit at the null resolution in this paper was 57%, although future research must be done to determine if this was simply a coincidence. A Figure of Merit greater than 50% would seem to represent a "Resolution of Merit" in that the Figure of Merit at that resolution becomes greater than the error. Thus, these two metrics should be used in tandem to assess predictive accuracy of a land change model.

• Journal of Environmental Science International
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• v.19 no.7
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• pp.829-841
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• 2010

The estimation of a biogenic volatile organic compound (BVOC, especially isoprene) and the influence of isoprene emissions on ozone concentrations in the Greater Busan Area (GBA) were carried out based on a numerical modeling approach during a high ozone episode. The BVOC emissions were estimated using a biogenic emission information system (BEIS v3.14) with vegetation data provided by the forest geographical information system (FGIS), land use data provided by the environmental geographical information system (EGIS), and meteorological data simulated by the MM5. Ozone simulation was performed by two sets of simulation scenarios: (1) without (CASE1) and (2) with isoprene emissions (CASE2). The isoprene emission (82 ton $day^{-1}$) in the GBA was estimated to be the most dominant BVOC followed by methanol (56) and carbon monoxide (28). Largest impacts of isoprene emissions on the ozone concentrations (CASE2-CASE1) were predicted to be about 4 ppb in inland locations where a high isoprene was emitted and to be about 2 ppb in the downwind and/or convergence regions of wind due to both the photochemical reaction of ozone precursors (e.g., high isoprene emissions) and meteorological conditions (e.g., local transport).

• Journal of the Korean Geographical Society
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• v.46 no.3
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• pp.291-303
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• 2011

It has actively advanced to study the impact of climate change on ecosystem. This study addresses ABMS (Agent Based Modeling and Simulation) as a methodology of ecosystem research. ABMS would suggest the possibility of practical use in this sector. This study would investigate how the melting speed of glacier in the arctic influences the extinction period of polar bears. The Polar Bears and Glacier Model in this study is expected to contribute to accurate prediction of the polar bear's extinction period. The suggested ABMS could also be applied to the study of various factors of ecosystem in general.

• Journal of the Korean Geographical Society
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• v.46 no.3
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• pp.331-350
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• 2011

Advances in computer technology enabled us to simulate the integrated effects of various geomorphic processes on landscape evolution. This review introduces a theoretical framework for 2-dimensional numerical landscape evolution models (NLEMs) which have recently been used for various research purposes. In particular much attention is paid to the approaches deployed to model major geomorphic processes on a geological time scale in previous research. NLEMs can simulate landscape evolution by numerically solving the partial differential equation which represents the relationship among the geomorphic system components (GSCs). Simple process specifications of the relationships among GSCs on a long-term time scale in terms of quantification and attempts to combine processes represent the initial research on NLEMs. Later researchers have taken these simple NLEMs and elaborated on them. Introducing the theories of NLEMs in this review is expected to help researchers trying to utilize or develop NLEMs.

• Journal of the Korean Geographical Society
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• v.44 no.3
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• pp.395-409
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• 2009

The objective of this paper is to illustrate that kriging can provide an effective framework both for integrating remote sensing data and for uncertainty modeling through a case study of sediment grain size mapping with remote sensing data. Landsat TM data which show reasonable relationships with grain size values are used as secondary information for sediment grain size mapping near the eastern part of Anmyeondo and Cheonsuman bay. The case study results showed that uncertainty attached to prediction at unsampled locations was significantly reduced by integrating remote sensing data through the analysis of conditional variance from conditional cumulative distribution functions. It is expected that the kriging-based approach presented in this paper would be efficient integration and analysis methodologies for any environmental thematic mapping using secondary information as well as sediment grain size mapping.

• Journal of the Korean Geographical Society
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• v.48 no.3
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• pp.387-401
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• 2013

Redistricting of National Assembly Election has a significant effect on the results of election because it has a strong tendency to be performed with political intentions rather than the equivalent representativeness of population and region. This paper focuses on proposing an alternative for restricting of National Assembly Election in terms of implementation, that is, an procedural and systematic approach, not allowing for political or arbitrary intervention. A spatial optimization model conforming with criteria for political redistricting such as population equality, contiguity, and spatial compactness is developed and applied to Yongin City where are some controversy over the redistricting of the 19th National Assembly. Modeling results show that it is possible to derive National Assembly Election districts based on the information of basic spatial units without political consideration or arbitrary intervention. In addition, The districts derived from the model improved population equality compared with the existing districts.

• Journal of the Korean Geographical Society
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• v.46 no.2
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• pp.197-211
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• 2011

Due to the complexity of spatial interaction and the necessity of spatial representation and modeling, aggregation of spatial interaction data is indispensible. Given this, the purpose of this paper is to evaluate the effects of modifiable areal unit problem (MAUP) on a spatial interaction model. Four aggregation schemes are utilized at eight different scales: 1) randomly select seeds of district and then allocate basic spatial units to them, 2) minimize the sum of population weighted distance within a district, 3) maximize the proportion of flow within a district, and 4) minimize the proportion of flow within a district. A simple Poisson regression model with origin and destination constraints is utilized. Analysis results demonstrate that spatial characteristics of residuals, parameter values, and goodness-of-fit of the model were influenced by aggregation scale and schemes. Overall, the model responded more sensitively to aggregation scale than aggregation schemes and the scale effect on the model was varied according to aggregation schemes.

• Journal of the Korean Geographical Society
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• v.45 no.4
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• pp.521-539
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• 2010

Recently many local governments have carried out dong merger and abolition process to cope with rapidly changing administrative demand and environment. This administrative effort impacts substantially the locational characteristics of the existing dong offices which directly involve in the quality of local community life. In this paper, we attempt to analyze the location pattern of current dong community service centers (formerly, 'dong office') and suggest the optimal locations maximizing spatial accessibility. As an application, we examine the location pattern of the existing dong community service centers in Mapo-gu, Seoul. Moreover, we compare current spatial configurations with the optimally selected locations such as, a Median maximizing spatial efficiency, a Center maximizing spatial equity, and a Centdian exploring compromising solutions regarding the tradeoff between efficiency and equity. The analytical results present that each of dong community service centers was systematically evaluated in terms of spatial efficiency and equity and in general the community service center locations are not spatially optimized with respect to efficiency and equity, compared with the optimal locations.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.183-201
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• 2022

Estimating the implicit value of housing assets is a very important task for participants in the housing market. Until now, such estimations were usually carried out using multiple regression analysis based on the inherent characteristics of the estate. However, in this paper, we examine the estimation capabilities of the Artificial Neural Network(ANN) and its 'Deep Learning' faculty. To make use of the strength of the neural network model, which allows the recognition of patterns in data by modeling non-linear and complex relationships between variables, this study utilizes geographic coordinates (i.e. longitudinal/latitudinal points) as the locational factor of housing prices. Specifically, we built a dataset including structural and spatiotemporal factors based on the hedonic price model and compared the estimation performance of the models with and without geographic coordinate variables. The results show that high estimation performance can be achieved in ANN by explaining the spatial effect on housing prices through the geographic location.

• Journal of the Korean Geographical Society
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• v.44 no.2
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• pp.122-145
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• 2009

Terrain parameters calculated from digital elevation models (DEM) have become increasingly important in current spatially distributed models of earth surface processes. This paper investigated how the ability of upslope area for predicting the spatial distribution of soil properties varies depending on the selection of spatial resolutions of DEM and algorithms. Four soil attributes from eight soil-terrain data sets collected from different environments were used. Five different methods of calculating upslope area were first compared for their dependency on different grid sizes of DEM. Multiple flow algorithms produced the highest correlation coefficients for most soil attributes and the lowest variations amongst different DEM resolutions and soil attributes. The high correlation coefficient remained unchanged at resolutions from 15 m to 50 m. Considering decreasing topographical details with increasing grid size, we suggest that the size of 15-30 m may be most suitable for soil-landscape analysis purposes in our study areas.