# RECORD e13b244754a8414a178e49afae995b23f640983e # TITLE: A GIS-based spatial analysis of housing price and road density in proximity to urban lakes in Wuhan City, China # YEAR: 2015.0 VENUE: Chinese Geographical Science DOI: 10.1007/s11769-015-0788-4 # AUTHORS: Zuo Zhang; Shukui Tan; Wenwu Tang # PAGES: 16 CANDIDATE TABLE PAGES (1-based): [10] # ABSTRACT: As one of the essential urban open spaces, lakes usually contribute immensely to the quality of residents′ daily lives. Different from hedonic approach employed in existing researches on urban open spaces in China, this paper integrates housing price surface with road density to analyze the spatial characteristics in proximity to urban lakes in Wuhan City, China. With the expansion of Wuhan City, urban lakes became polluted, they shrunk or even disappeared, leading to unfavorable conditions for sustainable development of the city. To better understand the spatial relationship between the city and lakes, we classify the urban lakes in Wuhan central area into ′lakes in the urban center′ and ′lakes in urban fringe′. Based on housing price surface we explore the spatial characteristics in proximity to different lakes and differences between the lakes. We also use Geographic Information System (GIS) tool to calculate road density as a supplementary indicator to reflect the accessibility in proximity to urban lakes. The results indicate that relative independence exists between different towns, and the spatial characteristics are different depending on scales and locations. In most of cases, the road density is lower where closer to the lakeshore while the housing price exhibits an opposite pattern. We conclude that city governments and urban planners should give more considerations to these spatial differences, somewhere should be better planned and protected as an important waterfront and somewhere the control of unreasonable real estate development nearby should be strengthened. ===== PAGE 1 (score 11, numeric-paren 0, table-words 0, var-words 11) ===== Chin. Geogra. Sci. 2015 Vol. 25 No. 6 pp. 775–790 Springer Science Press doi: 10.1007/s11769-015-0788-4 www.springerlink.com/content/1002-0063 Received date: 2015-04-01; accepted date: 2015-08-04 Foundation item: Under the auspices of National Natural Science Foundation of China (No. 41201164, L1422012), Humanity and Social Science Youth Foundation of Ministry of Education of China (No. 12YJCZH299), China Postdoctoral Science Foundation (No. 2012M521420, 2014T70693) Corresponding author: TAN Shukui. E-mail: tansk@126.com © Science Press, Northeast Institute of Geography and Agroecology, CAS and Springer-Verlag Berlin Heidelberg 2015 A GIS-based Spatial Analysis of Housing Price and Road Density in Proximity to Urban Lakes in Wuhan City, China ZHANG Zuo1, 2, TAN Shukui1, TANG Wenwu3 (1. College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China; 2. School of Business, Hubei University, Wuhan 430062, China; 3. Department of Geography and Earth Sciences and Center for Applied GIScience, Univer- sity of North Carolina at Charlotte, Charlotte 28223, U.S.A.) Abstract: As one of the essential urban open spaces, lakes usually contribute immensely to the quality of residents′ daily lives. Different from hedonic approach employed in existing researches on urban open spaces in China, this paper integrates housing price surface with road density to analyze the spatial characteristics in proximity to urban lakes in Wuhan City, China. With the expansion of Wuhan City, urban lakes became polluted, they shrunk or even disappeared, leading to unfavorable conditions for sustainable development of the city. To better understand the spatial relationship between the city and lakes, we classify the urban lakes in Wuhan central area into ′lakes in the urban center′ and ′lakes in urban fringe′. Based on housing price surface we explore the spatial characteristics in proximity to differ- ent lakes and differences between the lakes. We also use Geographic Information System (GIS) tool to calculate road density as a sup- plementary indicator to reflect the accessibility in proximity to urban lakes. The results indicate that relative independence exists be- tween different towns, and the spatial characteristics are different depending on scales and locations. In most of cases, the road density is lower where closer to the lakeshore while the housing price exhibits an opposite pattern. We conclude that city governments and urban planners should give more considerations to these spatial differences, somewhere should be better planned and protected as an important waterfront and somewhere the control of unreasonable real estate development nearby should be strengthened. Keywords: urban lakes; housing prices; road density; Geographic Information System (GIS); Wuhan City, China Citation: Zhang Zuo, Tan Shukui, Tang Wenwu, 2015. A GIS-based spatial analysis of housing price and road density in proximity to urban lakes in Wuhan City, China. Chinese Geographical Science, 25(6): 775–790. doi: 10.1007/s11769-015-0788-4 1 Introduction Urban open space preserves are usually indispensable to the area sustainability, being an essential element of land use policy in rapidly urbanizing areas (Esbah et al., 2009; Lichtenberg, 2011). However, with the rapid ur- ban expansion, most local governments do not estimate carefully the benefits of such open spaces, and real es- tate developers often fail to consider all public infra- structure costs generated by their projects (Brueckner, 2000). Constant increase in urban sprawl led to loss of open spaces (Smith et al., 2002). Some studies show that open space preserving expands the urban bounda- ries and creates leapfrog development (Irwin and Bockstael, 2004). Other studies found that rapid urbani- zation threatens the availability and accessibility of ur- ban open spaces, but there is no clear conflict between open space preservations and urban spatial expansions (Lichtenberg and Hardie, 2007). Furthermore, as a basic assumption in classical theory, property values decline with distance from the center of the city (Alonso, 1960). A common opinion of follow-up researches is that urban ===== PAGE 10 (score 14, numeric-paren 0, table-words 4, var-words 3) ===== 784 Chinese Geographical Science 2015 Vol. 25 No. 6 Table 4 General statistical descriptions of calculated distances Start of distance Distance Maximum Minimum Mean Standard error DGC 14.68 2.19 7.26 0.79 DSC_HK 13.90 1.96 5.73 1.36 DSC_WC 11.69 1.98 5.44 1.06 Gravity points of lakes DSC_HY 9.26 0.38 4.81 1.76 DGC 15.81 1.43 7.53 0.15 DSC_HK 12.73 0.45 4.42 0.29 DSC_WC 14.89 0.34 5.58 0.19 Value points DSC_HY 10.90 0.25 5.41 0.31 Notes: DGC is distance to geographical center; DSC_HK is distance to sub-center in Hankou District; DSC_WC is distance to sub-center in Wuchang District; DSC_HY is distance to sub-center in Hanyang District Fig. 8 Results of distance comparison for each value point of DSCi and DLSCi for each one. The results indicates that among all the 548 value points, 322 points (58.8%) are closer to the sub centers and 226 points (41.2%) are farther from the sub-centers compared to their closest urban lakes. 3.4 Spatial characteristics in proximity to urban lakes The exponential function is a fair choice to describe the relationship between housing prices and the traveling time from CBD (Osland and Pryce, 2012). In this paper, we explore the spatial characteristics based on the esti- mated results in housing price surface and various dis- tances to sub-centers or lakes. The regression analysis was implemented both for the entire region (Fig. 9a) and for different sectors (Figs. 9b, 9c and 9d). The difference is that the distance in Fig. 9a is from the value point to its urban GC, where the distances in Figs. 9b, 9c and 9d are from the value point to its sub-center. The R2 in Figs. 9b, 9c and 9d are higher than those in Fig. 9a, being es- pecially significant in HK and HY (Fig. 9). The results indicate that, first, the prices in the three towns of the Wuhan City are to some extent independent from each other. With the increase of the distance to the sub-center, there is a clear downward trend for housing prices in HK and HY. Second, HK has the highest overall housing price level, followed by WC and then HY. Additionally, HK has the most significant decline in housing prices with the increase in the distance to the sub-center, while the decline is the slowest in WC. Furthermore, the R2 are lower for the exponential function in WC. This might be due to some big lakes located in this town (e.g., L16) splitting up the built-up areas and resulting in sub-centers being not representative. To examine the relationship between housing pric- es and distances to sub-centers at different scales, we use exponential models to fit the housing prices and the distance to sub-center of value points in ULBZ0–0.5km, ULBZ0.5–1km, and ULBZ1–2km (Fig. 10). The results show that, first, for HK′s urban lakes, the overall level of housing prices in ULBZ0–0.5km is higher than that in ULBZ0.5–1km. This becomes more obvious when getting closer to the sub-center. Sec- ond, for HY′s urban lakes, the regression model of ULBZ0–0.5km is very close to that of the ULBZ0.5–1km. However, the overall level of housing prices in ULBZ0–0.5km and ULBZ0.5–1km is significantly higher than that in ULBZ1–2km. Third, for the urban lakes in WC, the overall housing price level in ULBZ0–0.5km is slightly higher than that in ULBZ0.5–1km, which is sig- nificantly higher than that in ULBZ1–2km. ===== PAGE 11 (score 4, numeric-paren 0, table-words 1, var-words 2) ===== ZHANG Zuo et al. A GIS-based Spatial Analysis of Housing Price and Road Density in Proximity to Urban Lakes in Wuhan… 785 Fig. 9 Relationship between housing prices and distances in different districts. Meanings of all abbreviations see Table 4 Fig. 10 Relationship between housing prices and distance at different scales