Urban land use prediction and construction effectiveness assessment supporting SDG 11.3.1 and regional planning goals

Abstract

Urban land use serves as the fundamental foundation for human survival and development, providing essential natural resources. Simulation is an important tool for assessing the impacts of urban planning and construction new urban. To support policy implementation for the development of the Xiongan New Area and promote sustainable urban management, we use the "Data-Information-Knowledge-Wisdom" (DIKW model) as a framework for predicting future land spatial changes considering sustainable development of urban planning. We developed a novel New Urban Multi-objective Land Use Prediction (NUMLUP) method, integrating a Genetic Algorithm (GA), Multi-Objective Planning (MOP), and the Conversion of Land Use and its Effects at Small Region Extent (CLUES) model. Using this approach, we obtained urban land spatial distribution data for three scenarios. Urban land spatial distribution data for the Historical Continuation Scenario (HCS), Policy Planning Scenario (PPS), and Planned Sustainable development scenario (PSDS) were obtained. To evaluate Sustainable Development Goal (SDG) 11.3.1 and Regional Planning Goals (RPGs), we assessed 19 consecutive years of construction effectiveness—covering both past (2017–2023) and future (2023–2035) periods under the three scenarios. The dataset achieved a multi-year overall accuracy (OA) exceeding 0.87 and a kappa index above 0.83, demonstrating strong integration of the NUMLUP model. The area of built up gradually increased, and the wetland was mainly dominated by Baiyangdian, which declined significantly from 2017 to 2023. In the three scenarios, from 2023 to 2035, the expansion of the built-up slows down, and the degree of change in the HCS area is minimal. Under the PPS, forest and wetland areas underwent the most drastic changes, with overall improvement rates ranked as PPS > PSDS > HCS. In contrast, the PSDS led to a significant increase in grassland. Under PSDS, grassland increased significantly. The construction of the three scenarios from 2017 to 2035 has achieved certain results. While PPS and PSDS closely aligned with planning targets, the HCS would fail to meet the 2035 requirements. The PSDS also prompted adjustments in the regional policy’s spatial layout. There were adjustments to the spatial layout of the policy as a result of PSDS. The LCRPGR is consistently greater than 1 from 2023 to 2035, reflecting a rational and comfortable urban plan that provides land use to meet population growth and demand.Furthermore, the PSDS introduced reasonable modifications to the regional plan’s spatial configuration. Our research provides robust support for monitoring sustainable urban development and implementing regional policies.