In this paper we provide a description of airborne mapping LiDAR, also known as airborne laser scanning (ALS), technology and its workflow from mission planning to final data product generation, with a specific emphasis on archaeological research. ALS observations are highly customizable, and can be tailored to meet specific research needs. Thus it is important for an archaeologist to fully understand the options available during planning, collection and data product generation before commissioning an ALS survey, to ensure the intended research questions can be answered with the resultant data products. Also this knowledge is of great use for the researcher trying to understand the quality and limitations of existing datasets collected for other purposes. Throughout the paper we use examples from archeological ALS projects to illustrate the key concepts of importance for the archaeology researcher.

A thorough review of available literature was conducted to inform of advancements in mobile LIDAR technology, techniques, and current and emerging applications in transportation. The literature review touches briefly on the basics of LIDAR technology followed by a more in depth description of current mobile LIDAR trends, including system components and software. An overview of existing quality control procedures used to verify the accuracy of the collected data is presented. A collection of case studies provides a clear description of the advantages of mobile LIDAR, including an increase in safety and efficiency. The final sections of the review identify current challenges the industry is facing, the guidelines that currently exist, and what else is needed to streamline the adoption of mobile LIDAR by transportation agencies. Unfortunately, many of these guidelines do not cover the specific challenges and concerns of mobile LIDAR use as many have been developed for airborne LIDAR acquisition and processing. From this review, there is a lot of discussion on “what” is being done in practice, but not a lot on “how” and “how well” it is being done. A willingness to share information going forward will be important for the successful use of mobile LIDAR.

Nearshore estimates of bathymetry are crucial for understanding coastal processes. However, current passive remote sensing methods for estimating bathymetry require in situ depth measurements to train inversion models, which can be difficult or impossible to obtain in many areas. To address this issue, we investigated the fusion of range measurements from the advanced topographic laser altimeter system (ATLAS) aboard the NASA ICESat-2 satellite, and multispectral satellite imagery from European Space Agency (ESA) Sentinel-2 using two common bathymetric inversion algorithms. The active ranging capability of the ATLAS green (532-nm) laser has been shown to generate returns of up to 38-m depth in optically clear waters, providing depth measurements to constrain passive bathymetric inversion results. Data acquired in November 2018 over the nearshore in Destin, FL, USA, offer a proof of concept for this approach. The results of the bathymetric inversion were quantitatively assessed by comparison with airborne bathymetric LiDAR collected using the U.S. Army Corps Coastal Zone Mapping and Imaging LiDAR (CZMIL) system in October–November 2018. Overall, the results of the bathymetric inversion compared with the CZMIL data have a root mean square error (RMSE) of 0.35 m in waters with similar turbidity and bottom reflectivity, and demonstrate that a combination of ICESat-2 depth observations with Sentinel-2 multispectral imagery can estimate seamless nearshore bathymetry for optically clear coastal waters.

In this paper we present a description of a new multispectral airborne mapping light detection and ranging (lidar) along with performance results obtained from two years of data collection and test campaigns. The Titan multiwave lidar is manufactured by Teledyne Optech Inc. (Toronto, ON, Canada) and emits laser pulses in the 1550, 1064 and 532 nm wavelengths simultaneously through a single oscillating mirror scanner at pulse repetition frequencies (PRF) that range from 50 to 300 kHz per wavelength (max combined PRF of 900 kHz). The Titan system can perform simultaneous mapping in terrestrial and very shallow water environments and its multispectral capability enables new applications, such as the production of false color active imagery derived from the lidar return intensities and the automated classification of target and land covers. Field tests and mapping projects performed over the past two years demonstrate capabilities to classify five land covers in urban environments with an accuracy of 90%, map bathymetry under more than 15 m of water, and map thick vegetation canopies at sub-meter vertical resolutions. In addition to its multispectral and performance characteristics, the Titan system is designed with several redundancies and diversity schemes that have proven to be beneficial for both operations and the improvement of data quality.

We evaluate the performance of full waveform LiDAR decomposition algorithms with a high-resolution single band airborne LiDAR bathymetry system in shallow rivers. A continuous wavelet transformation (CWT) is proposed and applied in two fluvial environments, and the results are compared to existing echo retrieval methods. LiDAR water depths are also compared to independent field measurements. In both clear and turbid water, the CWT algorithm outperforms the other methods if only green LiDAR observations are available. However, both the definition of the water surface, and the turbidity of the water significantly influence the performance of the LiDAR bathymetry observations. The results suggest that there is no single best full waveform processing algorithm for all bathymetric situations. Overall, the optimal processing strategies resulted in a determination of water depths with a 6 cm mean at 14 cm standard deviation for clear water, and a 16 cm mean and 27 cm standard deviation in more turbid water.