Exploring the Effects of Transportation Supply on Mixed Land-Use at the Parcel Level

Abstract

The interactive relationship between transportation and land use has become more difficult to understand and predict, due to the economic boom and corresponding fast-paced proliferation of private transportation and land-development activities. A lack of coordination between transportation and land-use planning has created an imbalanced provision of transportation infrastructure and land-use patterns; this is indicated by places where a high-density land-development pattern is supported by a low-capacity transport system or vice versa. With this, literature suggests that Mixed Land-Use (MLU) developments have the potential to provide relevant solutions for urban sustainability, smart growth, inclusive public transit use, and efficient land-use. Therefore, this study employed deep neural network models—Long Short-Term Memory (LSTM), and Multilayer Perceptron (MLP)—for forecasting the effect of transportation supply on the MLU pattern at the parcel level in the Jiang’an District, Wuhan, China. The findings revealed a strong relationship between the supply of public transportation and MLU. Moreover, the study results indicated that MLU is widely available in areas with high accessibility, high density, and proximity to the city center. The forecasting results from the MLP and LSTM models showed an average error of 5.55–7.36% and 3.62–4.28% for mixed use, respectively, while most of their 90th percentile errors were less than 13.73% and 10.46% for mixed use, respectively. The proposed models and the findings from this study should be useful for stakeholders and policy makers for more precise forecasting of MLU at the urban level.

Modeling Impact of Transportation Infrastructure-Based Accessibility on the Development of Mixed Land Use Using Deep Neural Networks: Evidence from Jiang’an District, City of Wuhan, China

“…Well-planned transportation infrastructure facilitates the integration of diverse land use types, while MLU development increases transportation accessibility by reducing travel distances and promoting sustainable transportation alternatives. This symbiotic relationship contributes to the development of vibrant, connected, and sustainable communities [30,31]. For instance, Aygoren [32], suggests that if there are two primary uses, it should be classified as MLU.…”

Analyzing Spatial Location Preference of Urban Activities with Mode-Dependent Accessibility Using Integrated Land Use–Transport Models

“…Bhat et al [27] described accessibility as "the ease with which an individual can pursue an activity of a desired type, at a desired place, using a desired mode, and at a desired time." Accessibility is a primary focus of interdisciplinary research including transportation, health, economics, social sciences, urban studies, and geography [4,28]. The origins of spatial systems can be traced back to Tobler's law of geography, which states that "everything is connected to everything else, but nearby objects are more connected than distant things" [29].…”

Evaluating Locational Preference of Urban Activities with the Time-Dependent Accessibility Using Integrated Spatial Economic Models

“…The spatial accessibility of urban facilities has also improved significantly in TOD areas over time [ 36 ]. Similarly, Almansoub et al [ 37 ] conducted a study to evaluate the effect of accessibility on Mixed Land Use (MLU) at parcel level in the city of Wuhan, China. The study results showed a substantial relationship between the supply of public transportation and MLU.…”

“…Accessibility has become of key importance in analytical measurements, and the literature is rich with accessibility applications [ 37 , 43 ]. It is important to understand the shortcomings and the theoretical concepts behind existing models for designing more robust accessibility models.…”