Urban Spatial Monitoring (USM) data is a new form of fundamental geographic information product that captures and records the dynamic changes of urban land use and built environments. As an important component of the natural resources survey and monitoring system, USM provides strong support for the construction of the China Spatial Planning Observation Network (CSPON), a national framework for monitoring and managing spatial development across China. The quality of USM data results is related to the accuracy of statistical analysis outcomes, the scientific decision-making for national economy, people's livelihood and social development, as well as the reliability of natural resources management applications. However, ensuring the quality of such large-scale, multi-source spatial data remains a significant challenge. Based on the analysis of the characteristics of USM results, this paper proposes a three-tier inspection process including overall preliminary inspection, detailed inspection, and off-sample general inspection—each targeting different aspects of data quality; analyzes inspection parameters and items, and determines the inspection methods for different items; further identifies quality elements that can be automatically inspected by programs, and realizes batch automatic inspection of some items by establishing a rule base, while other quality items are evaluated through semi-automated human–computer interactive inspection, with common problems systematically identified and addressed. Finally, the quality inspection results of urban space monitoring data products covering 170 prefecture-level city survey areas spanning approximately 6 million square kilometers demonstrate that the technical route proposed in this paper is feasible, the quality evaluation results are objective, and the proposed approach can serve as a practical reference for quality assurance of large-scale geographic data products.