【摘要】 激光雷达LiDAR(Light Detection and Ranging)能够精准地还原被测物体的3D结构，是遥感领域最具革新性的技术之一。近几十年来，LiDAR技术取得了快速的发展，并极大地推动了生态与地学领域的相关研究。本文系统回顾并展望了LiDAR硬件和算法的最新发展及其在生态与地学领域的应用。首先，LiDAR的硬件呈现出多样化、高精度的发展态势，特别是近些年无人驾驶技术的成熟极大丰富了近地面LiDAR平台的类型；其次，深度学习、同步定位与地图构建SLAM(Simultaneous Localization And Mapping)、大模型等人工智能技术的发展极大推动了LiDAR算法的进步，使得点云配准、点云分割与分类、点云与多源数据融合等算法不断推陈出新；最后，本文详述了LiDAR在内陆地形测绘、海洋测绘、地质灾害监测、森林结构测量、树木枝干结构网络、3D辐射传输及场景重建、森林微气候模拟、智慧农业、生物多样性、城市与建筑，以及行星测量11个生态与地学分支领域的应用。未来，随着硬件、算法、及LiDAR大数据的进一步发展，LiDAR将继续推动生态与地学的研究，并有望在更多领域发挥重要作用。更多还原

【Abstract】 LiDAR(Light Detection and Ranging) is one of the most innovative technologies in the field of remote sensing, capable of accurately reconstructing the three-dimensional(3D) structures of the objects being measured. Over the past few decades, LiDAR technology has advanced rapidly, significantly promoting research in the field of ecology and geosciences. This paper systematically reviews and explores the potential future developments in LiDAR hardware and algorithms, as well as their applications in ecology and geosciences.We first pointed out that, driven largely by the rapid advancements of autonomous driving technology, LiDAR hardware has demonstrated a trend towards diversification and enhanced precision. Types of near-ground LiDAR platforms have been particularly enriched, enabling efficient and high-resolution data acquisition at unprecedented spatial and temporal scales. Meanwhile, due to the progress of artificial intelligence technologies such as deep learning, Simultaneous Localization and Mapping(SLAM), and Large Language Model, LiDAR algorithms have also achieved significant development, leading to continuous innovations in point cloud registration, segmentation, classification, and the fusion of point clouds with multi-source data. Regarding LiDAR’s applications in ecology and geosciences, we detailed the applications of LiDAR in 11 research topics of ecology and geosciences: inland topographic mapping, ocean mapping, geological hazard monitoring, forest structure measurement, tree branching networks modeling, 3D radiative transfer and scene reconstruction, forest microclimate simulation, intelligent agriculture, biodiversity monitoring, urban and architectural studies, and planetary survey. Our comprehensive review underscores LiDAR’s versatility and its critical role in advancing both theoretical and applied ecological and geoscience research.Looking ahead, with the continuous advancement of hardware, algorithms, and LiDAR big data, LiDAR will continue to revolutionize research in ecology and geosciences and is poised to play a pivotal role in an even broader range of fields. For instance, combining LiDARderived 3D structural information with radiative transfer modeling, computational fluid dynamics, and plant physiology offers the potential to simulate essential biological processes such as photosynthesis, transpiration, and respiration. The advancement of multispectral and hyperspectral LiDAR systems is expected to tackle the challenge in species identification and vegetation trait quantification, opening possible new frontiers in biodiversity and functional ecology. At a broader scale, LiDAR is expected to support the implementation of “Realistic 3D China,” a comprehensive digital twin of the nation’s surface environment. In addition, LiDAR will be increasingly applied to underground remote sensing, power infrastructure inspection, and Earth system monitoring. In terms of big data, the establishment of LiDARNET(https://lidar. pku. edu. cn/[2025-04-14]), a national open-access platform for near-surface LiDAR data, represents a key milestone in enabling data standardization and large-scale collaboration. With the establishment of LiDARNET and other LiDAR data sharing platforms, the availability of high-resolution LiDAR datasets will be continuously augmented, providing critical foundations for the development of next-generation global vegetation dynamic models and enabling more accurate forecasting and management of ecosystem processes at multiple scales.In short, LiDAR is emerging as a pivotal technology in shaping the future of Earth observation, plant ecology, animal ecology, urban ecology, and a range disciplines of geosciences. With the ongoing advancements in hardware design, algorithm development, and highresolution LiDAR big data, LiDAR is committed to drive transformative breakthroughs across more research fields.更多还原