Simulating and Predicting the Impacts of Light Rail Transit Systems on Urban Land Use by Using Cellular Automata: A Case Study of Dongguan, China

Abstract

Abstract:The emergence of Light Rail Transit systems (LRTs) could exert considerable impacts on sustainable urban development. It is crucial to predict the potential land use changes since LRTs are being increasingly built throughout the world. While various land use and land cover change (LUCC) models have been developed during the past two decades, the basic assumption for LUCC prediction is the continuation of present trends in land use development. It is therefore unreasonable to predict potential urban land use changes associated with LRTs simply based on earlier trends because the impacts of LRT investment may vary greatly over time. To tackle this challenge, our study aims to share the experiences from previous lines with newly planned lines. Dongguan, whose government decided to build LRTs around 2008, was selected as the study area. First, we assessed the impacts of this city's first LRT (Line R2) on three urban land use types (i.e., industrial development, commercial and residential development, and rural development) at different periods. The results indicate that Line R2 exerted a negative impact on industrial development and rural development, but a positive impact on commercial and residential development during the planning stage of this line. Second, such spatial impacts (the consequent land use changes) during this stage were simulated by using artificial neural network cellular automata. More importantly, we further predicted the potential impacts of Line R1, which is assumed to be a newly planned line, based on the above calibrated model and a traditional method respectively. The comparisons between them demonstrate the effectiveness of our method, which can easily take advantage of the experiences from other LRTs. The proposed method is expected to provide technical support for sustainable urban and transportation planning.

A Comparison of Vacancy Dynamics between Growing and Shrinking Cities Using the Land Transformation Model

“…Inversely, an excess of abandoned structures or underutilized land could possibly cause economic, social and environmental problems such as urban disinvestment, reduced tax revenues, overburdened social programs, increased stock of vacant housing, and increased crime and poverty (7). As such, forecasting future vacant land dynamics can be socially, physically and environmentally beneficial for both growing and shrinking cities and is critical first step to develop proactive land use policies (6,8,9) in an effort to not waste public funds to operate or maintain under- or unused facilities and public services. Due to technological constraints and time limits, unfortunately, few academic studies and planning practices seek to advance land use prediction modeling, especially in regard to vacant properties.…”

Identification Method for Optimal Urban Bus Corridor Location

“…Because different objective functions have different dimensions, the objective function needs to be normalized. Based on Reference [36], we transformed the multi objective programming problem into a single-objective programming problem, as expressed in (11) and (12). F 1max , F 2max , and F 3max are the maximize value of function F 1 , F 2 , and F 3 , which need to be calculated in advance.…”

“…Cervero and Dai combined BRT and transit-oriented development and, based on case studies in Bogota, Curitiba, Seoul, and other cities [10,11], proved that BRT can improve transportation in crowded cities and enhance land-development intensity along the BRT corridor. Most studies on public transport corridors analyzed the impact of the centralized transportation system on the potential land-use changes [12] and the impact of traffic corridors on urban areas and urban forms [13].…”

Influences of Different Transport Routes and Road Nodes on Industrial Land Conversion: A Case Study of Changchun City of Jilin Province, China

“…A wealth of studies have documented the interaction between transportation and land use with regard to land use structure, intensity and property value (Boyce et al, 1972;Gamble et al, 1974;Baerwald, 1982;Cervero and Landis, 1997;Bowes and Ihlanfeldt, 2001;Perk and Catalá, 2009;Roukouni et al, 2012;Lin et al, 2018;Cordera et al, 2019;Zhao and Shen, 2019). Knight and Trygg (1977) studied the extent of the impact of the transportation system on land use.…”