도농복합시는 1995년 지방자치제가 본격 시행되면서 주민 편의를 증진하고, 도시와 농촌 지역의 균형발전을 목적으로 설치되었다. 본 연구는 우리나라 전체 54개 도농복합시를 대상으로 도시 스프롤 측면에서 도시공간구조를 분석하고자 하였다. 이를 위해 밀도 기반의 도시 스프롤 측정 지수를 적용하여 2000년, 2010년, 2020년 도농복합시의 도시 스프롤을 인구밀도 및 고용밀도의 측면에서 탐색하였다. 분석 결과, 도농복합시의 인구 스프롤은 전반적으로 증가한 반면, 고용 스프롤은 감소하는 경향을 보였다. 그리고 도시 규모별 도농복합시의 도시 스프롤은 차별화되어 진행되었음을 확인하였다.

After opening Suwon railway station in 1905, a new road was constructed between Suwon station and Paldalmun(the South gate). It was the starting point to change urban structures of Suwon and shape the new city scape. In 1914, administrative districts of Suwon were reorganized. Suwon-myeon (township, a subdivision of Suwon-gun) was promoted to Suwon-eup(town) in 1931. Suwon-eup expanded its territory and changed the address system from ‘li(里)’ system to Japanese address system, ‘Jeong(町)’ in 1936. From 1920s, road system was changed and transformed Suwon’s urban structures. A straight road was built from Jongro intersection to Janganmun(the north gate) in 1928. Another straight road was constructed between Suwon station to Padamun in the early 1930s. Public office buildings used the Hwa Seong HaengGung(華城行宮) and some of building moved to new location with new buildings. Main buildings of most schools in Suwon were reconstructed since 1930s. Commercial buildings and stores were sprung up and had their own characteristics by region. Around Suwon station, there are more hotels and restaurants than other areas. Rearranging administrative areas, developing road system and new buildings transformed Suwon’s spatial structures. Constructing new roads formed a straight road passing through Suwon. After reorganizing administrative areas, this road turned to be the central axis of Suwon. Buildings in new style on the axis made the modern cityscape in Suwon.

Considering the situation in the early 20th century when the existing urban system centered on urban areas began to change, the biggest factors causing urban structural changes in urban areas are construction of railroad and urban dismantling. The change process of Eupseong, in the microscopic viewpoint, can be understood as a process of change in the course of dismantlement of town's demarcation, improvement of accessibility and urban expansion due to the construction of railroads, process of urban expansion following the crumbling boundaries and structural changes. This study aimed to look at the transformation process of the Eupseong in the early 20th century, focusing on the demolition of the castle and the railway construction from a microscopic point of view of city.

도시 스프롤 정의를 구성하는 핵심적인 두 가지 요소는 저밀도와 분절화이다. 밀도를 기반으로 스프롤을 측정하는 경우 분절화 정도를 파악할 수 없고, 분절화를 중심으로 스프롤을 측정하는 경우 밀도 변화를 고려하기 어렵다. 본 연구의 목적은 밀도와 분절화 정도를 동시에 고려하는 새로운 스프롤 측정치를 고안하는 것이다. 이를 위해 동일한 측정 범위를 갖는 밀도 기반의 스프롤 지수와 두 개의 공간구조 기반 스프롤 지수인 인접 통계량과 분할 지수를 가중치 기법을 이용하여 결합하였다. 이 새로운 측정치를 밀도-공간구조 기반 스프롤 지수로 명명하였다. 밀도, 인접 정보 및 도시화된 지역의 면적을 이용하여 지수를 손쉽게 계산할 수 있고 결합한 세 지수의 측정 범위와 해석 방향이 동일하기 때문에 개발된 지수의 해석이 직관적이다. 사례분석의 결과는 개발된 지수가 밀도기반 접근과 공간구조 기반 접근의 단점을 보완할 수 있음을 보여준다.

The relationship between urban spatial structures and GHG-AP integrated emissions was investigated by statistically analyzing those from 25 administrative districts of Seoul. Urban spatial structures, of which data were obtained from Seoul statistics yearbook, were classified into five categories of city development, residence, environment, traffic and economy. They were further classified into 10 components of local area, population, number of households, residential area, forest area, park area, registered vehicles, road area, number of businesses and total local taxes. GHG-AP integrated emissions were estimated based on IPCC(intergovernmental panel on climate change) 2006 guidelines, guideline for government greenhouse inventories, EPA AP-42(compilation of air pollutant emission factors) and preliminary studies. The result of statistical analysis indicated that GHG-AP integrated emissions were significantly correlated with urban spatial structures. The correlation analysis results showed that registered vehicles for GHG (r=0.803, p<0.01), forest area for AP (r=0.996, p<0.01), and park area for AP (r=0.889, p<0.01) were highly significant. From the factor analysis, three groups such as city and traffic categories, economy category and environment category were identified to be the governing factors controlling GHG-AP emissions. The multiple regression analysis also represented that the most influencing factors on GHG-AP emissions were categories of traffic and environment. 25 administrative districts of Seoul were clustered into six groups, of which each has similar characteristics of urban spatial structures and GHG-AP integrated emissions.