Abstract: This article is based on 806 papers from CNKI from 2015 to 2025 and uses CiteSpace tools to systematically sort out the development context of drone engineering monitoring in China. The research shows that the annual publication volume has increased by 30.8%, experiencing a transition through three stages: basic surveying and mapping, intelligent upgrading, and collaborative applications. Policy, technology, and demand are driving the industry's development in coordination. Research institutions exhibit academic dominance, with 86% of the results concentrated in higher education institutions, and there is insufficient interaction between industry, academia, and research. The technological framework centers on "drone + remote sensing + 3D modeling, " with "deep learning + LiDAR + digital twin" becoming points of innovation and being applied in areas such as geological disaster warning, ecological restoration, and engineering safety monitoring. The research focus has shifted from dynamic monitoring to intelligent surveying and emergency assessment, with surveying engineering and deep learning becoming key to technological advancement. In addition, this paper presents a categorized summary of typical application scenarios, providing guidance for readers to select appropriate mature solutions and potential partners based on their actual needs. In the future, challenges regarding data heterogeneity need to be addressed, and an integrated network of "air, ground, and well" needs to be constructed, merging edge computing and quantum sensing to achieve autonomous decision-making, while advancing the development of standard systems and green monitoring technologies to support the dual-carbon strategy and new infrastructure construction. This study provides a reference for optimizing technology and promoting intelligent transformation in the field.