Debnath Sourabhi, Paul Manoranjan, Debnath Tanmoy
School of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW 2795, Australia.
J Imaging. 2023 Feb 24;9(3):57. doi: 10.3390/jimaging9030057.
Light detection and ranging (LiDAR) sensors have accrued an ever-increasing presence in the agricultural sector due to their non-destructive mode of capturing data. LiDAR sensors emit pulsed light waves that return to the sensor upon bouncing off surrounding objects. The distances that the pulses travel are calculated by measuring the time for all pulses to return to the source. There are many reported applications of the data obtained from LiDAR in agricultural sectors. LiDAR sensors are widely used to measure agricultural landscaping and topography and the structural characteristics of trees such as leaf area index and canopy volume; they are also used for crop biomass estimation, phenotype characterisation, crop growth, etc. A LiDAR-based system and LiDAR data can also be used to measure spray drift and detect soil properties. It has also been proposed in the literature that crop damage detection and yield prediction can also be obtained with LiDAR data. This review focuses on different LiDAR-based system applications and data obtained from LiDAR in agricultural sectors. Comparisons of aspects of LiDAR data in different agricultural applications are also provided. Furthermore, future research directions based on this emerging technology are also presented in this review.
由于激光雷达（LiDAR）传感器采用非破坏性的数据采集模式，其在农业领域的应用日益广泛。激光雷达传感器发射脉冲光波，这些光波在从周围物体反射后返回传感器。通过测量所有脉冲返回光源的时间来计算脉冲传播的距离。激光雷达获取的数据在农业领域有许多已报道的应用。激光雷达传感器广泛用于测量农业景观和地形以及树木的结构特征，如叶面积指数和树冠体积；它们还用于作物生物量估计、表型特征分析、作物生长等。基于激光雷达的系统和激光雷达数据也可用于测量喷雾漂移和检测土壤特性。文献中还提出，利用激光雷达数据也可以进行作物损害检测和产量预测。本综述重点关注基于激光雷达的不同系统应用以及在农业领域从激光雷达获得的数据。还提供了不同农业应用中激光雷达数据各方面的比较。此外，本综述还介绍了基于这项新兴技术的未来研究方向。
