Understanding urban growth spatiotemporally is important for landscape and urban development planning. In this study, we examined the spatiotemporal pattern of urban growth of the Colombo Metropolitan Area (CMA)—Sri Lanka’s only metropolitan area—from 1992 to 2014 using remote sensing data and GIS techniques. First, we classified three land-use/cover maps of the CMA (i.e., for 1992, 2001, and 2...

Many studies have reported the thermal effects of urban expansion from non-built-up land; however, how changes in building height in built-up land influence the regional thermal environment is still uncertain. Thus, taking the transitional region between the Chinese megacities of Beijing and Tianjin as the study area, this study investigated the impacts of built-up land expansion in 2D and 3D o...

while different elements including social, economic and cultural elements play a vital role in the emergence of behavioral patterns in humans, one cannot ignore the influence of the physical and spatial characteristics of built environment as a back ground for occurrence of anomic behavior on committing crimes. therefore, a series of approaches and theories such as “crime prevention through env...

China has been through a period of remarkable urban sprawl since the reform and opening-up policy in 1978, with the highest urbanization occurring in the coastal zones. Sustainable urban development requires a better understanding of the spatiotemporal characteristics of urbanization. This study systematically explored urban sprawl in Chinese coastal cities with a visual interpretation method f...

Urban development is a complex process influenced by a number of driving forces, including spatial planning, topography and urban economics. Identifying these drivers is crucial for the regulation of urban development and the calibration of predictive models. Existing land-use models generally consider urban development as a binary process, through the identification of built versus non-built a...

This study analyzes the characteristics of land use/land cover change in Jordan’s Irbid governorate, 1984–2018, and predicts future land use/land cover for 2030 and 2050 using a cellular automata-Markov model. The results inform planners and decision makers of past and current spatial dynamics of land use/land cover change and predicted urban expansion, for a better understanding and successful...