Prediction of the spatial distribution of high-rise residential buildings by the use of a geographic field based autologistic regression model

Abstract

As an indicator of urbanization, high-rise residential buildings, can meet the space requirements of an increasing population and improve land use efficiency. Such buildings are continuously built in the central areas of cities worldwide despite residential suburbanization. To predict high-rise residential building location, this study employs a geographic field model-based autologistic regression model (GFM-autologistic model). In line with this goal, a model is determined using both the value of the area under the receiver operating characteristic curve (ROC) and the Akaike information criterion (AIC) for GFM-autologistic, Euclidean distance (ED)-logistic and ED-autologistic models. The minimum AIC and the maximum ROC values of the GFM-autologistic model indicate that this model has the best fit. The GFM defines the external effect of ecological elements and locational factors, and it also quantifies distance decay through a linear intensity function with an influence threshold, thereby avoiding the bias caused by ED. Moreover, land prices are positive related to building height. High-rise residential development also considers open public spaces, such as rivers and city plazas. In summary, the spatial distribution of high-rise residential buildings displays a distance decay in the effect of ecological elements such as open spaces. Thus, this manuscript provides a theoretical basis for modern-city development planning and modern high-rise residential development.

Sixty-Year Changes in Residential Landscapes in Beijing: A Perspective from Both the Horizontal (2D) and Vertical (3D) Dimensions

“…The residential neighborhoods built in more recent years tended to have more tall buildings and thus greater average building height. These high-rise residential apartments were built to meet the need of accelerated population growth in Beijing and to improve the land use efficiency [36,37]. The changes in the height of the residential neighborhoods and their spatial distribution may have great social-ecological implications.…”

Comparisons of three‐dimensional urban forms in different urban expansion types: 58 sample cities in China

“…Therefore, the balance between urban desirability and suburban liveability makes the correlation between the two-dimensional forms and the three-dimensional forms of China more complex. In fact, the emergence of high-rise buildings in China is relatively random (Zhou, Liu, Chen, Zeng, & Wang, 2015) (Ye & Zhuang, 2017), which is different from Western countries whose high-rise buildings are located in CBDs. In China, more high-rise buildings may occur in outlying areas away from the city center as well.…”

“…Therefore, the balance between urban desirability and suburban liveability makes the correlation between the two‐dimensional forms and the three‐dimensional forms of China more complex. In fact, the emergence of high‐rise buildings in China is relatively random (Zhou, Liu, Chen, Zeng, & Wang, 2015) and does not necessarily exist in infilling regions close to downtown areas. A number of new towns and districts have a high‐development intensity and population density (Ye & Zhuang, 2017), which is different from Western countries whose high‐rise buildings are located in CBDs.…”

A Pricing Model for Urban Rental Housing Based on Convolutional Neural Networks and Spatial Density: A Case Study of Wuhan, China

“…The geographic field changes regularly, and the influences of geographic objects on other things are decay functions from their original locations. Jiao [31] and Liang [14] used the GFM to establish housing locational and neighborhood variables, which could more reasonably evaluate the degrees of influence between geographic objects [42,43]. However, in the real world, with the increase in the number of geographic objects, the actual influence of each single object can be gradually diminished.…”