Enhancing urban landscape configurations by integrating 3D landscape pattern analysis with people's landscape preferences

Rapid urbanization in China has become an important social-economic issue. During the process of urbanization, a diversity of factors should be balancedly considered for the design of landscape configuration. Amongst these factors, people's landscape preferences are given growing emphasis. Landscape preferences have been widely examined and some studies have been designed to link landscape preferences to landscape patterns. However, most studies have been conducted from a 2D perspective and therefore cannot simulate people's actual perception of local landscape configurations. This paper proposes a framework, based on which 3D landscape pattern analysis and landscape preferences can be efficiently integrated for evaluating urban landscape configurations. Airborne light detection and ranging (Lidar) is an ideal tool for conducting 3D landscape pattern analysis. In accordance with 3D landscape pattern analysis, standardized and generally applicable surveys of landscape preferences can be designed and conducted in different areas. A case study was conducted in Cambridge and Canvey, UK to demonstrate how 3D urban landscape patterns can be analyzed. Furthermore, a case study was conducted in Cambridge, UK and Nanjing, China to explain how people's landscape preferences can be acquired and compared. Landscape pattern analysis indicated that 3D landscape models effectively revealed comprehensive landscape patterns and simulated people's perception of local landscape configurations. For instance, cross-culture surveys on general landscape preferences proved the existence of commonly shared landscape preferences, which may be used as evaluation criteria. This methodology provides reference for landscape planners and decision makers to enhance urban landscape configurations. The methodology is of potential contribution to China's rapid urbanization by suggesting practical approaches to improve landscape patterns according to people's preferences.