학위논문 (석사)-- 서울대학교 대학원 농업생명과학대학 생태조경·지역시스템공학부, 2017. 8. 이동근.Rapid urbanization and decaying downtown areas have caused mass gains in vacant houses in large cities, such as Seoul, and mid-sized cities, such as Incheon and Daejeon. Vacant land and houses lower land prices and can trigger crime, causing negative externalities to adversely affect their surroundings. More cities have been gradually introducing green spaces in vacant land as a means of redevelopment to improve the city and reduce negative externalities. In addition to this societal value, the physical evaporation and shadow effects of green spaces can mitigate the urban heat island effect, which is a serious problem due to the artificial heat of the city. In Korea, quantitative figures for the mitigation of the urban heat island phenomena are derived only for individual sites, and there has been insufficient research on the effects of introducing green spaces into vacant land and housing sites. In particular, it is important to evaluate the potential temperature reduction effect in the planning stage before implementing greening in the vacancies. This is important data that provides baseline data at the decision-making stage. Therefore, it is necessary to quantitatively study the effect of greening vacant land and houses. The purpose of this study is to derive the quantitative effects of urban infrastructure mitigation using meta-analysis to predict the regional effects of green infrastructure on vacant land. First, quantitative figures are derived from the meta- analysis on the impact of a Green Infrastructure Strategy on reducing urban decay. Second, based on the results of the meta-analysis, we quantitatively derive the green infrastructure effect obtained in two selected high-density areas in Sungui-dong, Nam-gu, Incheon. Nam-gu is the second largest city in Incheon and its residential area is the target of urban regeneration. Third, we examine the environmental benefits and opportunity costs of greening. The study was conducted as follows. To understand the quantitative effect of green infrastructure, we derived a regression equation and used meta-analysis to determine the effect of temperature reduction when green space was introduced. Then, the extent of urban decay was evaluated using a previous study and sites A and C, with available ground surface temperature data, were selected in Nam-gu, Incheon. The appropriate type of greening for Sites A and C were selected and the effect of temperature reduction was estimated using meta-analysis results. The results of the study indicate that Sites A and C should be transformed into a Neighborhood Park and pocket park, respectively. These changes would result in a temperature reduction up to 2.751 °C within the park at Site A, and a temperature reduction of ~1.507 °C within a 62-m radius outside the park. The projected performance at Site C was similar, a temperature reduction of up to 2.269 °C internally and ~0.92 °C outside the park. In deriving the results, we considered that various previous studies obtained results from different situations, including climate zones and geography. In addition, the opportunity cost due to greening and the added value to the surrounding area are discussed. Green infrastructure is an effective environmental practice tool to add social, economic, and cultural value. Furthermore, it facilitates the adoption of environment-friendly policies, such as the introduction of green spaces rather developing additional buildings to public places.Chapter 1. Introduction 1
Chapter 2. Literature Review 5
2.1 Greening strategies case study 5
2.2 Case studies of greening vacant land 9
Chapter 3. Methods 12
3.1 Scope of the Study 12
3.1.1 Contents 12
3.1.2 Spatial Context 12
3.2 Methods 15
3.2.1 Study flow 15
3.2.2 Estimation of green infrastructure effect using meta-analysis 17
3.2.3 Selecting the study site and greening type 21
Chapter 4. Results and discussion 26
4.1 Estimation of green infrastructure effect using meta-analysis 26
4.1.1 Results from the search and selection of related documents 26
4.1.2 Derivation of Heat Island Reduction Effect and Trend Equation 28
4.1.3 Equation accuracy 34
4.2 Search and select target sites 40
4.2.1 'Dong' selection for green infrastructure 40
4.2.2 Vacant land for green infrastructure effect 43
4.3 Estimation of green infrastructure effect 51
4.4 Impacts on the surrounding area 52
4.5 The opportunity cost of greening 53
Chapter 5. Conclusions 57
Bibliography 60
Appendix 67
Abstract in Korean 77Maste
