• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.13-21
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• 2011

In mobile environment supporting mobility technologies, user requirements have been increased with respect to utilization of location information. In particular, moving object DBMS has consistently posed in order to efficiently maintain traffic information related to location of vehicle which tents to tremendously change over time. Despite the fact that these sorts of researches must be taken into consideration, empirical studies on moving object in terms of map database for lbs service, spatial attribute of which is continuously changed over time, have rarely performed. Therefore, aim of this paper is to suggest efficient spatial index scheme, which is capable of supporting query processing algorithm and location of moving object over time, by developing new empirical model. As a result, we can come to the conclusion that moving object model based on multi-fixed grid index makes it possible to cut down on the number of entity for retrieving. What's more, this model enables hierarchical data to be accessed through efficient spatial filtering on large-scale lbs data and constraints in accordance with level in order to display map.

• Korean Journal of Human Ecology
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• v.21 no.2
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• pp.389-405
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• 2012

The purposes of this study were to investigate students' perception on importance and performance of service quality of university foodservice, and to examine Importance-Performance Analysis(IPA) of foodservice quality for male and female students. A total of 500 university students in Daejeon were surveyed and 432 responses were returned. Excluding responses with significant missing data, 412 responses were used for data analysis. In terms of importance of service quality attributes, 'sanitation(4.74)' category received the highest score, followed by 'food(4.36)', 'service(4.22)', 'convenience(4.01)', 'menu(3.90)' and 'atmosphere(3.73)'. In terms of performance, the highest service quality attribute was associated with 'convenience(3.30)', followed by 'service(3.06)', 'sanitation(2.95)', 'food(2.88)', 'atmosphere(2.79)' and 'menu(2.68)'. As the results of IPA, 'staff's kindness', 'overall quality of service', 'taste of the food', 'freshness of the food', 'overall quality of the food', and 'cleanliness of the facility' fell into the Quadrant IV(Focus here) for female students. On the other hand, male students' IPA grid illustrated that 'taste of the food', 'freshness of the food', 'nutrition of the food', 'sanitation of the food', and 'sanitation of the utensils' fell into Quadrant IV(Focus here).

• Spatial Information Research
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• v.19 no.4
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• pp.81-89
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• 2011

This paper presents a multivariate kriging algorithm that integrates categorical data as secondary data for spatial interpolation of sparsely sampled ground survey data. Instead of using constant mean values in each attribute of categorical data, disaggregated local mean values at target grid points are first estimated by area-to-point kriging and then are used as local mean values in simple kriging with local means. This algorithm is illustrated through a case study of spatial interpolation of a geochemical copper element with geological map data. Cross validation results indicates that the presented algorithm leads to significant respective improvement of 15% and 25% in prediction capability, compared with univariate ordinary kriging and conventional simple kriging with constant mean values. It is expected that the multivariate kriging algorithm applied in this study would be effectively applied for spatial interpolation with categorical data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.431-436
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• 2008

Recently, the rapid development of GIS technology has made it possible to handle a various data associated with spatially hydrological parameters with their attribute information. Therefore, there has been a shift in focus from lumped runoff models to distributed runoff models, as the latter can consider temporal and spatial variations of discharge. In this research, a distributed rainfall-runoff model based on physical kinematic wave for analysis of surface and river flow was used to simulate temporal and spatial distribution of long-term discharge. The snowfall and melting process model based on Hydro-BEAM was developed, and various hydrological parameters for input data of the model was extracted from basic GIS data such as DEM, land cover and soil map. The developed model was applied for the Shonai River basin(532) in Japan, which has sufficient meteorological and hydrological data, and displayed precise runoff results to be compared to the hydrograph.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.145-151
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• 2009

Recently, the rapid development of GIS technology has made it possible to handle a various data associated with spatially hydrological parameters with their attribute information. Therefore, there has been a shift in focus from lumped runoff models to distributed runoff models, as the latter can consider temporal and spatial variations of discharge. This research is to evaluate the feasibility of GIS based distributed model using radar rainfall which can express temporal and spatial distribution in actual dam watershed during flood runoff period. K-DRUM (K-water hydrologic & hydaulic Distributed flood RUnoff Model) which was developed to calculate flood discharge connected to radar rainfall based on long-term runoff model developed by Kyoto- University DPRI (Disaster Prevention Research Institute), and Yondam-Dam watershed ($930km^2$) was applied as study site. Distributed rainfall according to grid resolution was generated by using preprocess program of radar rainfall, from JIN radar. Also, GIS hydrological parameters were extracted from basic GIS data such as DEM, land cover and soil map, and used as input data of distributed model (K-DRUM). Results of this research can provide a base for building of real-time short-term rainfall runoff forecast system according to flash flood in near future.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.1
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• pp.22-31
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• 2001

The purpose of this study is to compare calculated pollutant loadings using pollutant load unit factors and vector type coverage, and expected mean concentration(EMC) and raster type of digital elevation model(DEM). This study is also focusing on comparison of the advantages and the disadvantages of the two methods, and seeking for a method of calculation of pollutant loadings using DEM. Estimation of pollutant inputs using pollutant load unit factors has limitations in identifying seasonal variations of pollutant loadings. Seasonal changes of runoffs should be considered in the calculation of pollutant loadings from catchments into reservoirs. Evaluation of pollutant inputs using runoff-coefficient and EMC can overcome these drawbacks. Proper EMC and runoff-coefficient values for the Koeup stream catchments of the Koheung estuarine lake were drawn from review of related papers. Arc/Info was employed to establish database of spatial and attribute data of point and non-point pollutant sources and characteristics of the catchments. ArcView was used to calculate point and non-point pollutant loadings. Pollutant loads estimated with either unit factors-coverages, i.e., pollutant load unit factors and vector coverages f point sources and land use, or EMC and digital elevation mode(DEM) were compared with stream monitoring loads. We have found that some differences were shown between monitoring results and estimated loads by Unit Factors-Coverage and EMC-DEM. Monthly variations of pollutant loads evaluated with EMC-DEM were similar to those with monitoring result. The method using EMC-DEM can calculate accumulated flows and pollutant loads and can be utilized to identify stream networks. A future research on correcting the difference between vector type stream using flow direction grid and digitalizing vector type should be conducted in order to obtain more exact calculation of pollutant loadings.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.381-392
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• 2011

Pollutant loads calculated with unit factor method can not identity seasonal variations of pollutant inputs. Estimation of pollutant loads considering rainfall runoff can overcome these limits. SCS curve number method was applied to estimate runoff of each event of Koeup watershed of Koheung estuary lake. SCS curve numbers were calculated based upon land use, soil types of the catchment using GIS. Point and nonpoint source pollutant loads were summed up for total loads estimation. Those from nonpoint source were estimated by multiplying the calculated runoff and expected mean concentrations (EMC) presented by the Minister of Environment of Korea. DEM can present three dimensional views of a terrain, identity stream networks and flow accumulation. Furthermore, it can examine accumulated pollutant loads of specific point of a catchment. Therefore, cell based pollutant load estimation was attempted using DEM. ArcView was utilized to collect, store and manipulate spatial and attribute data of pollutant sources and features of the catchment. Cell-based DEM which was established by the GRID module of ARC/INFO was employed to estimate flows and pollutant loads.

• Journal of the Korean Geosynthetics Society
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• v.22 no.2
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• pp.1-12
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• 2023

Research on the causes of landslides and prediction of vulnerable areas is being conducted globally. This study aims to predict the effective soil depth, a critical element in analyzing and forecasting landslide disasters, using topographic information. Topographic data from various institutions were collected and assigned as attribute information to a 100 m × 100 m grid, which was then reduced through data grading. The study predicted effective soil depth for two cases: three depths (shallow, normal, deep) and five depths (very shallow, shallow, normal, deep, very deep). Three classification models, including K-Nearest Neighbor, Random Forest, and Deep Artificial Neural Network, were used, and their performance was evaluated by calculating accuracy, precision, recall, and F1-score. Results showed that the performance was in the high 50% to early 70% range, with the accuracy of the three classification criteria being about 5% higher than the five criteria. Although the grading criteria and classification model's performance presented in this study are still insufficient, the application of the classification model is possible in predicting the effective soil depth. This study suggests the possibility of predicting more reliable values than the current effective soil depth, which assumes a large area uniformly.