Abstract
Industrial parks and company growth are vital for urban planning and development. With temporal data collection, mathematical model based growth predictions of industrial parks becomes feasible. In this study, an industrial park Land development Simulation and Company Growth Projections (LSGP) framework is proposed by applying satellite data for land development simulation and social big data for company growth analysis. The cellular automata model is developed to simulate land use development, and the logistic function is applied to set up company growth projection model for selected industrial parks. Results show that the LSGP framework can effectively simulate industrial park land expansion and growth patterns with the following main findings: (1) Underlying land growth follows similar patterns, and key influencing factors are similar, such as traffic convenience, adjacent to urban centers; (2) Company growth pattern follows a logistic growth curve, with each subgroup of companies following the same pattern; (3) Models developed based on a selected industrial park can be transferred to another, i.e., case-based studies can be applied to newly planned industrial parks; (4) The LSGP framework may be further developed to simulate various land use projects and emulate growth patterns for additional areas of interest.