Abstract:The purpose of this study was to develop a low impact development-based district unit planning (LID-DP) model and to verify the model by applying it to a test site. To develop the model, we identified various barriers to the urban planning process and examined the advantages of various LID-related techniques to determine where in the urban development process LID would provide the greatest benefit. The resulting model provides (1) a set of district unit planning processes that consider LID standards and (2) a set of evaluation methods that measure the benefits of the LID-DP model over standard urban development practices. The developed LID-DP process is composed of status analysis, comprehensive analysis, basic plan, and sectoral plans. To determine whether the LID-DP model met the proposed LID targets, we applied the model to a test site in Cheongju City, Chungcheongbuk-do Province, Republic of Korea. The test simulation showed that the LID-DP plan reduced nonpoint source pollutants (total nitrogen, 113%; total phosphorous, 193%; and biological oxygen demand, 199%); reduced rainfall runoff (infiltration volume, 102%; surface runoff, 101%); and improved the conservation rate of the natural environment area (132%). The successful application of this model also lent support for the greater importance of non-structural techniques over structural techniques in urban planning when taking ecological factors into account.Keywords: low impact development; urban planning; district unit planning; LID-based district unit planning model; land-use planning

The goal of this study is to analyze the interrelated direct and indirect impacts of urban development intensity (UDI) characteristics on carbon dioxide (CO 2 ) emissions in Korea. The study also compares the main arguments and analysis results of previous studies on cities that are effective in reducing CO 2 emissions. To do this, factors attributable to the UDI characteristics of Korea were selected, and CO 2 emissions were calculated. Then, the impact of UDI characteristics on CO 2 emissions was analyzed using the partial least squares structural equation model. The main results show that the physical, spatial, and socio-demographic characteristics of UDI have a direct impact on CO 2 emissions, and physical, economic, and city-type characteristics indirectly affect CO 2 emissions. As a result, we reach the following conclusions: (i) dense urban forms reduce CO 2 emissions; (ii) economic characteristics of UDI have impact on total CO 2 emissions, having both negative and positive effects; and (iii) medium and small cities have higher per capita CO 2 emissions than do large cities. communication infrastructure on CO 2 emissions. Land use patterns and density elements represent spatial characteristics, and transportation and communication infrastructure facilities exhibit physical characteristics. Similarly, Guerin et al. [8] found that factors such as age, gender, and education level, which indicate social and economic characteristics, such as income and house ownership, affect energy consumption. Brownstone and Golob [9] found that spatial characteristics, such as residential density, affect vehicle mileage and fuel consumption. Tate et al. [10] and Mendes [11] developed the UDI index based on physical characteristics, such as land coverage and infrastructure, and socio-demographic characteristics, such as census block group.However, as pointed out by Wang et al [7], virtually no studies comprehensively address the UDI characteristics relevant to urban planning. For example, Newman and Kenworthy [6] argued that physical factors, such as transportation-related automobiles and transportation facilities, accelerate CO 2 , but their research fails to include economic factors, such as price or income changes. Similarly, Talbi [12] studied the relationship between CO 2 and economic aspects, such as GDP, fuel consumption, fuel ratio, and energy efficiency, and found that the latter two are important for CO 2 emissions. However, this author did not consider the fact that energy consumption patterns or CO 2 emissions may vary due to other factors, such as age or city type. Schipper et al. [13] and Guerin, Yust and Coopet [8] considered socio-demographic and economic characteristics but limited their study of energy consumption to the residential sector. Similarly, Fragkias et al. [14] examined the relationship between city size and CO 2 emissions based on population, but they did not sufficiently address other characteristics influencing this relationship.Though previous studies do not comprehensively address UDI charac...

This study aimed to evaluate environmental injustice and analyze ood vulnerability characteristics in consideration of environmental justice and urban ood disaster prevention planning. We investigated various urban disaster prevention factors applied to the urban development process in Seoul from the perspective of environmental justice. Flood risk areas were identi ed and ood damage data from 2000 to 2018 were collected. Furthermore, a panel analysis was performed and the nal model was selected. The ood vulnerability characteristics were found to be detached houses having basements, aged detached houses, land area for detached houses, public assistance recipients, and population aged 65 years or above, which had impact factors of 8.323, 3.781, -2.877, 3.257, and 2.637, respectively. The results indicate that not only the socially vulnerable population lacks the ability to respond to oods, but buildings and areas with poor residential environments also suffer from ood damage. This implies that there is socioeconomically disproportionate exposure (termed as environmental injustice) in the process of urban ood prevention planning and urban development. Our results can contribute qualitatively and quantitatively to prepare a ood prevention plan based on environmental justice paradigm.

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