Determining Sustainable Development Density using the Urban Carrying Capacity Assessment System

Diverse urban problems in the capital region of Korea occur due to over-development and over-concentration which exceed the region’s carrying capacity. Particularly, environmental problems such as air and water pollution have become more evident and become central issues for urban planners and decision-makers. In achieving sustainable environment through resolving such problems, practical approaches to incorporate the concept of environmental sustainability into managing urban development are needed. This research aims at developing an integrated framework for assessing urban carrying capacity which can determine sustainable development density, and has yielded the following. First, seven determining factors for urban carrying capacity including energy, green areas, roads, subway systems, water supply, sewage treatment, and waste treatment were identified, and the assessment framework was developed by integrating such factors. Second, the UCCAS, a GIS-based carrying capacity assessment system was developed based upon the framework. Finally, through a case study of determining carrying capacity of an urban area, it was revealed that decision support with the UCCAS demonstrated in this research could play a pivotal role in planning and managing urban development more effectively

Developing the Urban Thermal Environment Management and Planning (UTEMP) System to Support Urban Planning and Design

Mathematical Climate Simulation Modeling (MCSM) has the advantage of not only investigating the urban heat island phenomenon but also of identifying the effects of thermal environment improvement plans in detail. As a result, MCSM has been applied worldwide as a scientific tool to analyze urban thermal environment problems. However, the meteorological models developed thus far have been insufficient in terms of their direct application to the urban planning and design fields due to the preprocessing task for modeling operations and the excessive time required. By combining meteorological modeling and Geographic Information System (GIS) analysis methods, this study developed the Urban Thermal Environment Management and Planning (UTEMP) system that is user-friendly and can be applied to urban planning and design. Furthermore, the usefulness of UTEMP was investigated in this study by application to areas where the heat island phenomenon occurs frequently: Seoul, Korea. The accuracy of the UTEMP system was verified by comparing its results to the Automatic Weather Systems (AWSs) data. Urban spatial change scenarios were prepared and air temperature variations according to such changes were compared. Subsequently, the urban spatial change scenarios were distinguished by four cases, including the existing condition (before the development), applications of the thermal environment measures to the existing condition, allowable future urban development (the maximum development density under the urban planning regulations), and application of the thermal environment measures to allowable future development. The UTEMP system demonstrated an accuracy of adj. R2 0.952 and a ±0.91 Root Mean Square Error (RMSE). By applying the UTEMP system to urban spatial change scenarios, the average air temperature of 0.35 °C and maximum air temperature of 1.27 °C were found to rise when the maximum development density was achieved. Meanwhile, the air temperature reduction effect of rooftop greening was identified by an average of 0.12 °C with a maximum of 0.45 °C. Thus, the development of UTEMPS can be utilized as an effective tool to analyze the impacts of urban spatial changes and for planning and design. As a result, the UTEMP system will allow for more efficient and practical establishment of measures to improve the urban thermal environment

Diagnosis and Prioritization of Vulnerable Areas of Urban Ecosystem Regulation Services

Rapid urbanization and population growth have led to drastic degradation of urban ecosystem regulation services (ERS). Urgently needed is the identification of vulnerable areas where ERS are being intensively deteriorated, and preparation of measures to respond to them. This study developed a framework to diagnose and prioritize vulnerable areas of urban ERS. The vulnerability of urban ERS that include carbon storage capacity, flood-risk mitigation capacity, and heat stress reduction capacity was diagnosed with a resolution of 100 m × 100 m grid. Priority areas to improve urban ERS were delineated using hot spot analysis, and the diagnosed results of the urban ERS were categorized by eight combination types including exposure, sensitivity, and adaptability. The spatial and societal problems included in the priority areas were further investigated by overlaying hot spot areas with eight combination maps. Finally, spatial management measures for the priority areas were suggested based on the analysis results. From the detailed diagnosis results of the vulnerable ERS areas, this study provides a framework to link the concept of ERS vulnerability with urban planning. Furthermore, effective spatial planning guidelines can be prepared to improve urban ERS by spatially delineating priority areas to improve urban ERS vulnerability

The usefulness of the GIS - fuzzy set approach in evaluating the urban residential environment

The authors' focus was to determine the usefulness of the fuzzy set approach in evaluating the urban residential environment, compared with the crisp (or Boolean) approach. Particular emphasis was placed upon the comparison of evaluation results produced by the two methods within a geographic information system (GIS). This comparison highlighted the advantages of the GIS - fuzzy set approach as follows. First, it was revealed that the fuzzy set approach could reduce excessive abstraction or exaggeration in environmental phenomena. Hence, without the loss of valuable information, more accurate decisionmaking can be rendered. Second, by integrating membership functions into GIS, greater efficiency of the entire evaluation process was achieved.

Establishment of a Geographic Information System-Based Algorithm to Analyze Suitable Locations for Green Roofs and Roadside Trees

Urban green spaces offer various ecosystem services such as those for controlling the urban microclimate, improving water circulation, and providing leisure and recreation opportunities. However, it is almost impossible to create new, large green spaces in cities where urbanization has been long underway. Consequently, small-scale green spaces such as green roofs and roadside trees are gaining attention as features that can increase the effects of ecosystem services. Although the area of individual buildings in urban areas is relatively small, the sum of building rooftop areas account for a large portion of urban areas. Moreover, there are areas widely available throughout cities where street trees could be planted. However, this requires large amounts of accurate databases (DBs) and long-term spatial analyses to identify specific locations suitable for small-scale green facilities on a citywide scale using a geographic information system (GIS). Consequently, in-depth research on this topic has been insufficient. Thus, this study presents an algorithm to analyze locations where green roofs and roadside trees could be introduced based on GIS spatial analysis and verifies the effectiveness of the algorithm built for the city of Seoul. In addition, computational fluid dynamics (CFD) modeling is performed to analyze the temperature reduction effect, the representative function of ecosystem control services that can be brought about by the potential green spaces. The results show that rooftop greening in study areas is possible in 311,793 of 742,770 buildings. The rooftop floor area of buildings that can apply rooftop greening is 33,288,745 m2, which is about 50% of the total area of the rooftop in Seoul. It was found that roadside trees could be planted on a sidewalk with an extension length of 872,725 m and an area of 838,864 m2. A total of 145,366 trees can be planted in the study area. In addition, it was shown that the introduction of green roofs reduced temperatures by 0.13 °C to 0.14 °C and roadside trees reduced temperatures by 0.14 °C to 0.6 °C. With the growing need to improve urban ecosystem services as a result of rapid climate change, the algorithm developed in this study can be utilized to create spatial policies that expand and manage urban green spaces and thereby contribute to the improvement of urban ecosystem services

Diagnosis and Prioritization of Vulnerable Areas of Urban Ecosystem Regulation Services

Rapid urbanization and population growth have led to drastic degradation of urban ecosystem regulation services (ERS). Urgently needed is the identification of vulnerable areas where ERS are being intensively deteriorated, and preparation of measures to respond to them. This study developed a framework to diagnose and prioritize vulnerable areas of urban ERS. The vulnerability of urban ERS that include carbon storage capacity, flood-risk mitigation capacity, and heat stress reduction capacity was diagnosed with a resolution of 100 m × 100 m grid. Priority areas to improve urban ERS were delineated using hot spot analysis, and the diagnosed results of the urban ERS were categorized by eight combination types including exposure, sensitivity, and adaptability. The spatial and societal problems included in the priority areas were further investigated by overlaying hot spot areas with eight combination maps. Finally, spatial management measures for the priority areas were suggested based on the analysis results. From the detailed diagnosis results of the vulnerable ERS areas, this study provides a framework to link the concept of ERS vulnerability with urban planning. Furthermore, effective spatial planning guidelines can be prepared to improve urban ERS by spatially delineating priority areas to improve urban ERS vulnerability

Classifying Urban Climate Zones (UCZs) Based on Spatial Statistical Analyses

The objective of this study is the classification of urban climate zones (UCZs) based on spatial statistical approaches to provide key information for the establishment of thermal environments to improve urban planning. To achieve this, using data from 246 automatic weather stations (AWSs), air temperature maps in the summer of the study area were prepared applying universal kriging interpolation analysis. In addition, 22 preliminary variables to classify UCZs were prepared by a 100 m × 100 m grid. Next, six influential urban spatial variables to classify UCZs were finalized using spatial regression analysis between air temperature and preliminary variables. Finally, the UCZs of the study area were delineated by applying K-mean clustering analysis, and each spatial characteristic of the UCZs was identified. The results found that the accuracy of the air temperature of the study area ranged from ±0.184 °C to ±0.824 °C with a mean 0.501 root mean square predict error (RMSPE). Elevation, normalized difference vegetation index (NDVI), commercial area, average height of buildings, terrain roughness class, building height to road width (H/W) ratio, distance from subway stations, and distance from water spaces were identified as finalized variables to classify UCZs. Finally, a total of 8 types of UCZs were identified and each zone showed a different urban spatial pattern and air temperature range. Based on the spatial statistical analysis results, this study delineated clearer UCZs boundaries by applying influential urban spatial elements that resulted from previous classification studies of UCZs mainly based on pre-determined spatial variables. The methods presented in this study can be effectively applied to other cities to establish urban heat island counter measures that have similar weather observation conditions

The Contribution of Ecosystem Regulating Services Based on Their Interrelationship in the Urban Ecosystem

The urban ecosystem provides many services that help humans lead physically and mentally healthy lives. The quality of such urban ecosystem services is closely related to various urban forms, such as land cover, land use, buildings, infrastructure, population, and type and scale of green space. This study aims to promote the overall improvement and balance of an urban ecosystem’s regulating services. Initially, ecosystem regulating services are assessed according to the type of the urban space, and their contributions are analyzed based on linear regression slope and pairwise comparison of the ecosystem services. The contribution of ecosystem regulating services of Suwon City in South Korea was assessed through the following process: (1) selection of assessment indices and assessment methods for urban ecosystem regulating services; (2) urban space classification; (3) ecosystem regulating service assessment by type of urban space; and (4) pairwise comparison of ecosystem regulating services by type and for the entire study area. The study areas are classified into six type areas: forests (type A), agricultural land (type B), low-rise residential areas (type C), mid-rise mixed (residential and commercial) areas (type D), high-rise residential areas (type E), and industrial and barren land (type F). By studying representative regulating services, such as vegetation vitality, flood reduction capacity, carbon storage capacity, and heat reduction capacity, this study confirmed that type A provided the best service, while type C provided the worst. In addition, the relative contribution analysis between the regulating services based on pairwise comparison showed that the standard deviation between the contributions was 0.04 when diagnosing the entire study area, but apparently no types except type A were balanced. The reason such regulating services are imbalanced is that their vegetation vitality was calculated to be the lowest compared with the assessment indices of type A. Additionally, this imbalance was found to be most severe in the mid-rise mixed (residential and commercial) districts. Through this study, the spatial types in which the ecosystem regulating services in Suwon City are imbalanced could be determined. It was also revealed that regulating services should be prioritized for improvement in order to achieve greater balance in urban ecosystem. Such pairwise comparison results can be effectively utilized in determining the area and supply needed when formulating urban greening plans and forest restoration plans

Diurnal and seasonal variations in the effect of urban environmental factors on air temperature: A consecutive regression analysis approach

This study investigates the diurnal and seasonal variations in the effect of environmental features on air temperature in Seoul, Korea. We expect that this study will lead to the identification of factors that can be applied for urban heat island mitigation strategies in summer without leading to an unintended result in winter. As our dependent variable, we employed the smoothed 31-day moving average of air temperatures, where we controlled the seasonal variation by normalizing the values observed from 247 automatic weather stations (AWS) from 2015 to 2016. Subsequently, we conducted consecutive log–log regression analyses of each day to examine patterns of change in regression coefficients and the significance of each independent variable. For independent variables, we applied built environment features including albedo, land-use, average building floors, the sky view factor, and green and water areas. This study provides analytical results regarding the relationship between environmental factors and air temperature. This study also addresses imperative issues for planners, especially regarding albedo, wind path, building geometry, and land use types. Finally, this study gives useful insights for managing the diurnal and seasonal variations of urban thermal environment in the mega-city.ISSN:1660-4601ISSN:1661-782

Improving urban thermal environments by analysing sensible heat flux patterns in zoning districts

This study developed a method of improving Seoul's thermal environment by focusing on sensible heat flux and types of land-use and cover to mitigate the urban heat island (UHI) effect. First, the relationships between the sensible heat flux in summer and (a) the land cover ratio, and (b) the heights and densities of buildings in different land-use zoning districts were identified and analysed. The rationale for improving the thermal environment was then considered based on the physical relationships among heat, space, and the thermal-environment type. Energy budget distribution data were then used to identify an optimised land-use plan to mitigate the UHI effect. Spatial data describing the physical elements in land-use zoning were then generated using high-resolution images of the sensible heat flux distribution and directly correlated to existing land-use and thermal comfort. Finally, a K-means clustering analysis was employed to determine the unfavourable and favourable thermal areas in each zoning district based on correlated sensible heat flux data. The results indicate that the highest concentration of unfavourable thermal areas of all studied zoning districts was neighbourhood commercial districts, which accounted for 9.9% of the total identified unfavourable thermal areas, whereas the lowest level of sensible heat flux was observed in single-family residential areas. This study thus developed a basis for a spatial planning framework that can be used to improve the thermal conditions of cities and encourage summer energy savings using zoning-based requirements.N