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Cellular automata (CA) based models are among the practical tools to simulate the spatiotemporal evolution of landscape induced by the land use/-cover change (LUCC). Existing models have been struggling to comprehensively handle the intricate spatiotemporal driving relationships amid the nonlinear LUCC process, inevitably leaving obstacles to promote the simulation accuracy. Besides, the landscape patterns, which are both the causes and consequences of various ecological processes, are not considered in most models, making them struggled to support the decision making on regional development strategies. Aiming at overcoming these obstacles, a novel land use/-cover change model concerning spatiotemporal dependency and properties related to landscape evolution (STAPLE) is proposed in this paper. A potential generating module establishing the nonlinear spatiotemporal driving relationship and a spatial allocating module employing a landscape-based CA are integrated for a more realistic LUCC simulation. As a case study, the proposed model is applied in Zhengzhou, China to assess its performance. It is indicated that the STAPLE model achieved a higher simulation accuracy compared with the degraded models. Moreover, the landscape properties, i.e., the compactness and proximity of the patches, are effectively manipulated, which is verified by calculating the corresponding landscape indices. Furthermore, the STAPLE model is applied to explore a low-ecological-risk landscape under different future scenarios in 2035 and 2050. An infilling and remote development strategy is beneficial for Zhengzhou to control the landscape ecological risk induced by urban expansion. The STAPLE model provides a reproducible tool for policy-makers to support decision-making and achieve sustainable development.