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Dongwoo Lee
Research Institute of Spatial Planning & Policy, Hanyang University, Seoul 04763, Korea

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Journal article
Published: 10 August 2021 in Applied Sciences
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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.

ACS Style

Heeju Kim; Kyushik Oh; Dongwoo Lee. Establishment of a Geographic Information System-Based Algorithm to Analyze Suitable Locations for Green Roofs and Roadside Trees. Applied Sciences 2021, 11, 7368 .

AMA Style

Heeju Kim, Kyushik Oh, Dongwoo Lee. Establishment of a Geographic Information System-Based Algorithm to Analyze Suitable Locations for Green Roofs and Roadside Trees. Applied Sciences. 2021; 11 (16):7368.

Chicago/Turabian Style

Heeju Kim; Kyushik Oh; Dongwoo Lee. 2021. "Establishment of a Geographic Information System-Based Algorithm to Analyze Suitable Locations for Green Roofs and Roadside Trees." Applied Sciences 11, no. 16: 7368.

Journal article
Published: 11 July 2019 in Sustainability
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Adverse changes of the landscape resulting from diverse human activities have consequently caused quality decline and functional degradation of the natural landscape, endangering the natural habitats of various species. Meanwhile, technical advancements in the area of spatial analysis including GIS and remote sensing enable many kinds of easy-to-quantify landscape indices. Although some systems were developed to support assess landscape indices, developing systems for practical decision-making in spatial planning was insufficient. In this study, the GIS-based Green Infrastructure Assessment System (GIAS) was developed for integrated assessment of diverse landscape ecological values to use in spatial planning and management based upon indices sets that are mainly represented as structure, function, and dynamics of the landscape. In order to verify the effectiveness of the system, two case studies involving the city of Namyangju, northeast of Seoul, were conducted by applying GIAS to the (1) macro scale and (2) micro scale. The study results demonstrate the capability of GIAS as a planning support tool to perform concrete assessment of landscape ecological values and performance both on the macro and micro scale, and its applicability to diverse stages in spatial planning. By utilizing GIAS, frequent human-induced impacts resulting from development projects can be examined in advance, and proactive alternatives can be prepared. In addition, effective decision-making for scientific and systematic planning and management of green infrastructure can be achieved.

ACS Style

Dongwoo Lee; Kyushik Oh. The Green Infrastructure Assessment System (GIAS) and Its Applications for Urban Development and Management. Sustainability 2019, 11, 3798 .

AMA Style

Dongwoo Lee, Kyushik Oh. The Green Infrastructure Assessment System (GIAS) and Its Applications for Urban Development and Management. Sustainability. 2019; 11 (14):3798.

Chicago/Turabian Style

Dongwoo Lee; Kyushik Oh. 2019. "The Green Infrastructure Assessment System (GIAS) and Its Applications for Urban Development and Management." Sustainability 11, no. 14: 3798.

Journal article
Published: 12 April 2019 in Sustainability
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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.

ACS Style

Dongwoo Lee; Kyushik Oh. Developing the Urban Thermal Environment Management and Planning (UTEMP) System to Support Urban Planning and Design. Sustainability 2019, 11, 2224 .

AMA Style

Dongwoo Lee, Kyushik Oh. Developing the Urban Thermal Environment Management and Planning (UTEMP) System to Support Urban Planning and Design. Sustainability. 2019; 11 (8):2224.

Chicago/Turabian Style

Dongwoo Lee; Kyushik Oh. 2019. "Developing the Urban Thermal Environment Management and Planning (UTEMP) System to Support Urban Planning and Design." Sustainability 11, no. 8: 2224.

Journal article
Published: 30 March 2019 in Sustainability
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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.

ACS Style

Dongwoo Lee; Kyushik Oh; Seunghyun Jung. Classifying Urban Climate Zones (UCZs) Based on Spatial Statistical Analyses. Sustainability 2019, 11, 1915 .

AMA Style

Dongwoo Lee, Kyushik Oh, Seunghyun Jung. Classifying Urban Climate Zones (UCZs) Based on Spatial Statistical Analyses. Sustainability. 2019; 11 (7):1915.

Chicago/Turabian Style

Dongwoo Lee; Kyushik Oh; Seunghyun Jung. 2019. "Classifying Urban Climate Zones (UCZs) Based on Spatial Statistical Analyses." Sustainability 11, no. 7: 1915.