水科学进展2026，Vol.37Issue(5)：978-992,15.DOI:10.14042/j.cnki.32.1309.2026.05.016
面向数字孪生水网的空天地水工一体化激光雷达感知:进展与展望
Air-space-ground-water-engineering integrated LiDAR sensing for digital twin water networks:progress and prospects
摘要
Abstract
To address the bottlenecks of information fragmentation,inadequate physical mechanism coupling,and low cross-medium sensing accuracy in traditional monitoring for digital twin water networks,this study constructs an air-space-ground-water-engineering integrated LiDAR collaborative sensing framework spanning macro-basin,linear river channel,and micro-hydraulic structure scales.By systematically analyzing the transmission characteristics and attenuation mechanisms of laser pulses in complex media(atmosphere-vegetation-water-structure),this paper focuses on core technologies including multi-source heterogeneous data processing and cross-medium refraction correction,and proposes a physics-data dual-driven full-element inversion method.Integrating satellite laser altimetry,airborne green LiDAR,terrestrial scanning,and underwater acoustic-optic detection,the system achieves high-fidelity characterization of topographic evolution,water resource dynamics,structural defects,and flow capacity.In lake monitoring,engineering supervision,and flood disaster response,it significantly enhances the physical fidelity of hydrological simulations and the timeliness of emergency decision-making.Addressing challenges of high-turbidity signal attenuation and data assimilation,future research will focus on physics-informed neural networks(PINNs),edge-cloud collaborative architectures,and multi-spectral payloads to realize full-element dynamic mapping,thereby supporting the intelligent scheduling of national water networks.关键词
数字孪生水网/激光雷达(LiDAR)/空天地水工一体化/跨介质探测/全要素感知/物理-数据双驱动Key words
digital twin water networks/LiDAR/air-space-ground-water-engineering integration/cross-medium detection/multi-element sensing/physics-data dual-driven modeling分类
建筑与水利引用本文复制引用
付意成,刘志栋,臧文斌,张春玲..面向数字孪生水网的空天地水工一体化激光雷达感知:进展与展望[J].水科学进展,2026,37(5):978-992,15.基金项目
国家自然科学基金项目(U2443208 （）
U2243601) The study is financially supported by the National Natural Science Foundation of China(No.U2443208 （）
No.U2243601). （）
