Comprehensive LiDAR simulation with efficient physically-based DART-Lux model (I): Theory, novelty, and consistency validation

• Published in: Remote sensing of environment Vol. 272; p. 112952
• Main Authors: Yang, Xuebo, Wang, Yingjie, Yin, Tiangang, Wang, Cheng, Lauret, Nicolas, Regaieg, Omar, Xi, Xiaohuan, Gastellu-Etchegorry, Jean Philippe
• Format: Journal Article
• Language: English
• Published: New York Elsevier Inc 01.04.2022; Elsevier BV; Elsevier
• Subjects: Algorithms; anisotropy; Bidirectional path tracing; Case studies; Computational efficiency; Computer applications; Computer simulation; Computing time; Configurations; DART; data collection; Earth surface; environment; forests; Information processing; Information retrieval; LiDAR; Modelling; Monte Carlo; photons; Power measurement; Radiative transfer; Radiative transfer model; Remote sensing; Sciences of the Universe; Three dimensional models; Time measurement; Waveforms; DART; Bidirectional path tracing; Radiative transfer model; Monte Carlo; LiDAR
• ISSN: 0034-4257; 1879-0704; 1879-0704
• DOI: 10.1016/j.rse.2022.112952

Light Detection And Ranging (LiDAR) remote sensing is increasingly needed to assess the 3D architecture of Earth's surface. Physically-based LiDAR radiative transfer (RT) models are essential tools for interpreting LiDAR signals, designing LiDAR systems, and validating information retrieval methods. Discrete Anisotropic Radiative Transfer (DART) is one of the most accurate and comprehensive 3D RT models that simulate LiDAR signals of urban and natural landscapes. Its physical modeling relies on a forward Monte Carlo mode optimized by a ray-tracking technique, also called DART-RC (Ray Carlo) mode. However, DART-RC is not adapted to simulate massive LiDAR signals of large landscapes due to its constraints of high memory demand and long computational time. Therefore, we developed a novel computationally efficient LiDAR modeling method based on a new DART modeling mode called DART-Lux. It simulates LiDAR signal by adapting the bidirectional path tracing algorithm of DART-Lux to the time and power measurements and by implementing the LiDAR instrument and multiple product outputs in DART-Lux. We verified the accuracy of DART-Lux for LiDAR modeling using DART-RC as a reference for several case studies with different LiDAR configurations (i.e., single-pulse waveform, multi-pulse point cloud, multi-pulse photon counting, with and without solar signal) on realistic scenes from the RAMI experiment. Results stress that i) DART-Lux is consistent with DART-RC, for example, R2 = 1 and rRMSE = 0.21% for the waveform of a forest simulated with a huge number of rays; ii) DART-Lux converges faster than DART-RC: its processing time is usually about half that of DART-RC, and over ten times smaller if the solar signal is simulated; iii) DART-Lux memory usage can be a hundred times less than DART-RC. Also, several sensitivity studies with various sensor configurations and solar directions illustrate the usefulness of DART-Lux for impact studies. This new DART-Lux LiDAR model opens promising perspectives for large-scale LiDAR applications with 3D modeling. It is already part of the official DART version freely available to scientists (https://dart.omp.eu). •Present a novel LiDAR modeling method based on a DART modeling mode called DART-Lux.•Simulate the LiDAR signal with the bidirectional path tracing algorithm.•DART-Lux has good agreement with much better efficiency compared to previous model.•Express the LiDAR radiative transfer equation in a formulaic manner.•Comparison of bidirectional, forward, and backward tracing methods for LiDAR modeling.