Kyehyun Kim

Ontology based personalized route planning system using a multi-criteria decision making approach

This study presents a generic ontology-based architecture using a multi-criteria decision making technique to design a personalized route planning system. The real world has become too complex to implement entirely within an information system such as geographic information system (GIS). A route planning technique is an essential geo-related decision support tool, especially in intelligent transportation systems (ITS). In ubiquitous GIS environments, personalization can be accomplished through a users preferences stored on mobile appliances. In this manner, personalized and user-centric route planning services using semantic technologies and ontologies perceive user and context models to satisfy user demands and predict their requirements. In the past few years, several studies have been carried out regarding personalized services. However, the existing route finding algorithms suffer from a number of major difficulties, mainly owing to insufficient criteria modeling for a personalized system. Thus, the present study investigates how a user-centric route planning system can be implemented. In order to address this research issue, an ontology-based knowledge modelling technique using an analytic hierarchical process (AHP) is proposed. This technique can facilitate determination of the choice of criteria used for applying an impedance function in the route finding algorithm. From another perspective, AHP explicitly deals with a hierarchy structure and is essentially a theory of measurement and decision making methodology used for combining or synthesizing quantitative as well as qualitative criteria. User-centric results on real data illustrate the strengths of the present approach. It is anticipated that this new technique can be applied to develop new graph algorithms based on semantic web technology and can be used with new semantic graph structures.

Development of a water quality loading index based on water quality modeling.

Water quality modeling is an ideal tool for simulating physical, chemical, and biological changes in aquatic systems. It has been utilized in a number of GIS-based water quality management and analysis applications. However, there is considerable need for a decision-making process to translate the modeling result into an understandable form and thereby help users to make relevant judgments and decisions. This paper introduces a water quality index termed QUAL2E water quality loading index (QWQLI). This new WQI is based on water quality modeling by QUAL2E, which is a popular steady-state model for the water quality of rivers and streams. An experiment applying the index to the Sapgyo River in Korea was implemented. Unlike other WQIs, the proposed index is specifically used for simulated water quality using QUAL2E to mainly reflect pollutant loading levels. Based on the index, an iterative modeling-judgment process was designed to make decisions to decrease input pollutants from pollutant sources. Furthermore, an indexing and decision analysis can be performed in a GIS framework, which can provide various spatial analyses. This can facilitate the decision-making process under various scenarios considering spatial variability. The result shows that the index can evaluate and classify the simulation results using QUAL2E and that it can effectively identify the elements that should be improved in the decision-making process. In addition, the results imply that further study should be carried out to automate algorithms and subsidiary programs supporting the decision-making process.

Design of GIS based Korean Reach File Supporting Water Quality Modeling

Various input data required for water quality modeling have considerable impacts on modeling results and relevant analysis due to the absence of data standardization and lack of data accuracy. With this in mind, this study mainly focused on the designing Korean Reach File for more effective water quality modeling through the supply of database composed with accurate hydraulic and hydrologic data. The Korean Reach File is the hydraulic database with the locational information of individual reaches, and each reach represents the stream reach of homogeneous hydraulic characteristics. In detail, it has reach code designating each stream reach, and topological information including catalog unit, segment, marker and index. It was also designed considering linkage of existing codes such as stream name and stream code. The devised reach code was implemented to Kyungan River at the City of Gwangju of Kyunggi Province and the results showed that the reach code could effectively support the input database integrating basic numerous data required for water quality modeling based on a criterion as well as easier linkage and utilization with existing database. In addition, more systematic water quality management was enabled through the linkage of existing data such as treatment facilities, pollutant data, and management institutes using the reach codes defined for each stream section. In the future, more efforts need to be made to adopt the reach code as the national standard data thereby enabling utilization of numerous relevant database through the assigning of reach code to individual stream reaches nationwide.

A Study on the Development of GIS Based Mitigation Scenario Support System Using QUAL2E Model for TMDL

Abstract : This study was mainly focused on the development of GIS based decision support system to easily make mitigation scenarios and to conveniently simulate water quality for TMDL. The study area was the 31km section of upper Sapgyo stream in Geum river basin, and QUAL2E model was adopted. GIS DB was built through the collection of the data which includes point/ non-point source attributes and various thematic maps. The amounts of discharged loads of BOD, T-N and T-P from unit watershed were estimated respectively. Finally, the system, which can operate water quality simulation through simply modifying their values, was developed. The hypothetical three mitigation scenarios were applied, thereby the most efficient mitigation scenario could be chosen by comparison of the results based on GIS. Therefore, it is expected that the developed system can facilitate the decision makers to select the best alternative through the analysis of the available BMPs. Also, it can be used to develop new scenarios using different methods and algorithms. In the future, more study need to be made to enhance its applicability in the perspective of developing mitigation scenarios through the management of individual pollutant sources and extending study areas.

Ontology driven road network analysis based on analytical network process technique

During the past several years, Geographic information system (GIS) has allowed storage, editing, maintenance, dissemination, display and access of geospatial data. Ontologies are a level of description of the knowledge of an application that is independent of internal structure. Existing techniques related to the impedance model for each road segment which is utilized in a route finding algorithm is inadequate. The most impedance models are based on one-dimensional criterion such as distance or time which does not give proper results. Hence, this research investigates how impedance criteria of road segment can represent the real world in GIS using ontology driven architecture. To address this, first several criteria including quantitative as well as qualitative criteria such as traffic and climate are taken into account. Second, to weight these criteria, the Analytical Network Process (ANP) method is proposed. Finally, the impedance model is implemented and verified with real road network data.

GIS based optimal impervious surface map generation using various spatial data for urban nonpoint source management

Impervious surfaces are mainly artificial structures such as rooftops, roads, and parking lots that are covered by impenetrable materials. These surfaces are becoming the major causes of nonpoint source (NPS) pollution in urban areas. The rapid progress of urban development is increasing the total amount of impervious surfaces and NPS pollution. Therefore, many cities worldwide have adopted a stormwater utility fee (SUF) that generates funds needed to manage NPS pollution. The amount of SUF is estimated based on the impervious ratio, which is calculated by dividing the total impervious surface area by the net area of an individual land parcel. Hence, in order to identify the exact impervious ratio, large-scale impervious surface maps (ISMs) are necessary. This study proposes and assesses various methods for generating large-scale ISMs for urban areas by using existing GIS data. Bupyeong-gu, a district in the city of Incheon, South Korea, was selected as the study area. Spatial data that were freely offered by national/local governments in S. Korea were collected. First, three types of ISMs were generated by using the land-cover map, digital topographic map, and orthophotographs, to validate three methods that had been proposed conceptually by Korea Environment Corporation. Then, to generate an ISM of higher accuracy, an integration method using all data was proposed. Error matrices were made and Kappa statistics were calculated to evaluate the accuracy. Overlay analyses were performed to examine the distribution of misclassified areas. From the results, the integration method delivered the highest accuracy (Kappa statistic of 0.99) compared to the three methods that use a single type of spatial data. However, a longer production time and higher cost were limiting factors. Among the three methods using a single type of data, the land-cover map showed the highest accuracy with a Kappa statistic of 0.91. Thus, it was judged that the mapping method using the land-cover map is more appropriate than the others. In conclusion, it is desirable to apply the integration method when generating the ISM with the highest accuracy. However, if time and cost are constrained, it would be effective to primarily use the land-cover map.

An approach for automatic updating of GIS road segments for a pavement management system (PMS)

The GIS-T (Geographic Information System for Transportation) dynamic segmentation (DS) technique can be effectively employed by pavement management systems (PMS) to provide more detailed information on road conditions by using the segments. In most cases, segments present attributes that change frequently either spatially or non-spatially. In order to ensure correct and successful decision-making processes in transportation-related activities, regular updates and revision of segmented data are essential. Manual updating of the segmented data is a complex and time-consuming process. Thus, it is highly beneficial to provide an easy and efficient way to update segments. This paper presents a rule-based method for automatic updating of road segments using the DS technique. The proposed approach was implemented for the Road Maintenance and Transportation Organisation (RMTO) of Iran on road network data of Tehran city. The experimental results indicate many useful aspects of this approach that made it efficient. These include a remarkable decrease of time, cost, occurrence of human-type errors, and complexity involved in update operations.