Nature-based Solutions (NbS) have emerged as critical strategies for addressing global climate change and ecological crises. Light Detection and Ranging (LiDAR) technology offers high-precision 3D data that could significantly enhance NbS implementation, yet its integration into planning and design workflows faces technical barriers. We employed a bibliometric approach to systematically review 4,275 publications from the Web of Science Core Collection (2000–2024), using CiteSpace and Bibliometric R package with Pathfinder algorithm optimization to identify research clusters and evolutionary patterns. Four core application domains were identified: 1) ecological structural analysis, 2) vegetation assessment, 3) river restoration, and 4) urban resilience. LiDAR significantly enhances NbS site selection, spatial scaling, and performance evaluation by translating geometric–structural information into computable ecological metrics. However, challenges regarding data processing complexity, toolchain fragmentation, and interdisciplinary barriers continue to impede the full realization of LiDAR's potential. To address these gaps, we propose an integrated development pathway comprising three aspects: 1) open data sharing platforms to lower application thresholds, 2) AI-driven automation processing to overcome semantic understanding bottlenecks, and 3) standardized interoperability to bridge toolchain fragmentation. This pathway aims to transform LiDAR from a high-precision measurement tool into digital public infrastructure for evidence-based NbS design and governance, facilitating the digital and intelligent transformation of landscape planning and design.
WU et al. (Thu,) studied this question.