Geodetic imaging with airborne LiDAR: the Earth's surface revealed

Multispectral Light Detection and Ranging Technology and Applications: A Review

Light Detection and Ranging (LiDAR) is a well-established active technology for the direct acquisition of 3D data. In recent years, the geometric information collected by LiDAR sensors has been widely combined with optical images to provide supplementary spectral information to achieve more precise results in diverse remote sensing applications. The emergence of active Multispectral LiDAR (MSL) systems, which operate on different wavelengths, has recently been revolutionizing the simultaneous acquisition of height and intensity information. So far, MSL technology has been successfully applied for fine-scale mapping in various domains. However, a comprehensive review of this modern technology is currently lacking. Hence, this study presents an exhaustive overview of the current state-of-the-art in MSL systems by reviewing the latest technologies for MSL data acquisition. Moreover, the paper reports an in-depth analysis of the diverse applications of MSL, spanning across fields of "ecology and forestry", "objects and Land Use Land Cover (LULC) classification", "change detection", "bathymetry", "topographic mapping", "archaeology and geology", and "navigation". Our systematic review uncovers the potentials, opportunities, and challenges of the recently emerged MSL systems, which integrate spatial-spectral data and unlock the capability for precise multi-dimensional (nD) mapping using only a single-data source.

Reconfigurable coaxial single-photon LIDAR based on the SPAD array

The single-photon avalanche diode (SPAD) array with time-to-digital converter (TDC) circuits on each pixel is an excellent candidate detector for imaging LIDAR systems. However, the low fill-factor of the SPAD array does not allow for efficient use of laser energy when directly adopted in a LIDAR system. Here, we design a reconfigurable coaxial single-photon LIDAR based on the SPAD array and diffractive optical elements (DOEs). We use the DOE and beam expander to shape the laser beam into a laser dot matrix. The total divergence angle of the DOE spot beam is strictly matched to the total field of view (FOV) angle of the SPAD array. Meanwhile, each focused beamlet is individually matched to every active area of the SPAD array detector, which increases the use of output energy about 100 times compared to the diffusion illumination system. Besides, the system uses the active area as the minimum pixel and can support sub-pixel scanning, resulting in higher resolution images. Through this coaxial structure, two different telescope systems after transceiver switching can be reconfigured for imaging targets at different distances. Based on our single-photon LIDAR system, we achieved 3D imaging of targets at 100 m and 180 m using two different telescope configurations.

Ghost imaging lidar system for remote imaging

Research towards practical applications of ghost imaging lidar system especially in longer sensing distance has been urgent in recent years. In this paper we develop a ghost imaging lidar system to boost an extension of remote imaging, where the transmission distance of the collimated pseudo-thermal beam can be improved hugely over long range and just shifting the adjustable lens assembly generates wide field of view suiting for short-range imaging. Based on the proposed lidar system, the changing tendency of illuminating field of view, energy density, and reconstructed images is analyzed and verified experimentally. Some considerations on the improvement of this lidar system are also discussed.

Long-range photon-efficient 3D imaging without range ambiguity

Single-photon light detection and ranging (LiDAR) has broad applications ranging from remote sensing to target recognition. In most cases, however, the repetition period of the pulsed laser limits the maximum distance that can be unambiguously determined. The relative distances are normally obtained using a depth map. Here, we propose and demonstrate a photon-efficient three-dimensional (3D) imaging framework which permits the operation of high laser pulse repetition rates for long-range depth imaging without range ambiguity. Our approach uses only one laser period per pixel and borrows the information from neighboring pixels to reconstruct the absolute depth map of the scene. We demonstrate the absolute depth map recovery at ranges between 2.2 km and 13.8 km using ∼1.41 signal photons per pixel. We also show the capability to image the absolute distances of moving targets in real time.

Point Density Variations in Airborne Lidar Point Clouds

In spite of increasing point density and accuracy, airborne lidar point clouds often exhibit point density variations. Some of these density variations indicate issues with point clouds, potentially leading to errors in derived products. To highlight these issues, we provide an overview of point density variations and show examples in six airborne lidar point cloud datasets that we used in our topographic and geospatial modeling research. Using the published literature, we identified sources of point density variations and issues indicated or caused by these variations. Lastly, we discuss the reduction in point density variations using decimations, homogenizations, and their applicability.

Development of the high angular resolution 360° LiDAR based on scanning MEMS mirror

Light detection and ranging (LiDAR) using various operational principles has been applied in many fields, e.g., robotics navigation, autonomous vehicles, unmanned aerial flyers, land surveying, etc. The multichannel LiDAR system is of great importance in the field of autonomous driving due to its larger field of view (FoV). However, the number of transceivers limits the vertical angular resolution of multichannel LiDAR systems and makes them costly. On the other hand, the emergence of microelectromechanical systems (MEMS) mirrors may provide a highly promising solution to a low-cost, high angular resolution LiDAR system. We have demonstrated a MEMS mirror-based 360° LiDAR system with high angular resolution and will present the detailed design process and obtained experimental results in this paper. With the combination of the MEMS mirror and a rotation platform for the LiDAR system, a 360° × 8.6° (horizontal × vertical) FoV was achieved. Compared with existing commercial multichannel 360° LiDAR systems, our system has 13.8 times better angular resolution than the Velodyne HDL-64 LiDAR sensor. The experimental results verified an excellent performance of 0.07° × 0.027° (horizontal × vertical) angular resolution, which enhances the panoramic scanning and imaging capability of the LiDAR system, potentially providing more accurate 3D scanning applications in areas such as autonomous vehicles, indoor surveying, indoor robotics navigation, etc.

Scanning single-pixel imaging lidar

Long-range light detection and ranging (lidar) of active illumination optical imaging has widespread applications, such as remote sensing, satellite-based global topography, and target recognition and identification. Here, to make trade-offs among imaging efficiency, resolution, receiving field of view, divergence angle, and detected distance, we demonstrate a scanning single-pixel imaging lidar (SSPIL), enjoying the merits of the traditional pointing-by-pointing scanning imaging and single-pixel imaging. The imaging strategy of SSPIL is divided into scanning search and staring imaging processes. These strategies can save most time consumption for imaging background areas and thus improve imaging efficiency. Three imaging experiments were conducted in real urban atmospheric conditions. The preliminary results show SSPIL has the ability for long-range imaging with high efficiency, high resolution, and a large receiving field of view. Also, from the imaging results, we found that multiple samples can improve the SNR of imaging in the real urban atmosphere. The present work may provide a valuable alternative approach in the long-range active illumination optical imaging fields.

A multidisciplinary approach to locating clandestine gravesites in cold cases: Combining geographic profiling, LiDAR, and near surface geophysics

By nature, clandestine burials are difficult to locate, an issue that can complicate the legal process, and interrupt the natural grief process of the family. The purpose of this paper is to present a three-step process to search for clandestine graves using (1) geographic profiling, (2) light detection and ranging (LiDAR), and (3) near surface geophysics. Each process incrementally decreases the geographic area being searched, while increasing the level of detail provided to investigators. Using two well-known Australian cases and one experimental study, this paper will demonstrate how (1) can highlight potential search areas, (2) can further narrow down the location of potential burial sites within these search areas, and (3) can assist with locating the clandestine grave. Although each technique on its own can successfully locate graves, combining the techniques can provide the most efficient approach to locate those who are missing and buried.

Low-Cost Ultrasonic Range Improvements for an Assistive Device

To achieve optimal mobility, visually impaired people have to deal with obstacle detection and avoidance challenges. Aside from the broadly adopted white cane, electronic aids have been developed. However, available electronic devices are not extensively used due to their complexity and price. As an effort to improve the existing ones, this work presents the design of a low-cost aid for blind people. A standard low-cost HC-SRF04 ultrasonic range is modified by adding phase modulation in the ultrasonic pulses, allowing it to detect the origin of emission, thus discriminating if the echo pulses come from the same device and avoiding false echoes due to interference from other sources. This improves accuracy and security in areas where different ultrasonic sensors are working simultaneously. The final device, based on users and trainers feedback for the design, works with the user’s own mobile phone, easing utilization and lowering manufacturing costs. The device was tested with a set of twenty blind persons carrying out a travel experiment and satisfaction survey. The main results showed a change in total involuntary contacts with unknown obstacles and high user satisfaction. Hence, we conclude that the device can fill a gap in the mobility aids and reduce feelings of insecurity amongst the blind.

SPADs and SiPMs Arrays for Long-Range High-Speed Light Detection and Ranging (LiDAR)

Light Detection and Ranging (LiDAR) is a 3D imaging technique, widely used in many applications such as augmented reality, automotive, machine vision, spacecraft navigation and landing. Achieving long-ranges and high-speed, most of all in outdoor applications with strong solar background illumination, are challenging requirements. In the introduction we review different 3D-ranging techniques (stereo-vision, projection with structured light, pulsed-LiDAR, amplitude-modulated continuous-wave LiDAR, frequency-modulated continuous-wave interferometry), illumination schemes (single point and blade scanning, flash-LiDAR) and time-resolved detectors for LiDAR (EM-CCD, I-CCD, APD, SPAD, SiPM). Then, we provide an extensive review of silicon- single photon avalanche diode (SPAD)-based LiDAR detectors (both commercial products and research prototypes) analyzing how each architecture faces the main challenges of LiDAR (i.e., long ranges, centimeter resolution, large field-of-view and high angular resolution, high operation speed, background immunity, eye-safety and multi-camera operation). Recent progresses in 3D stacking technologies provided an important step forward in SPAD array development, allowing to reach smaller pitch, higher pixel count and more complex processing electronics. In the conclusions, we provide some guidelines for the design of next generation SPAD-LiDAR detectors.

Multiplatform-SfM and TLS Data Fusion for Monitoring Agricultural Terraces in Complex Topographic and Landcover Conditions

Agricultural terraced landscapes, which are important historical heritage sites (e.g., UNESCO or Globally Important Agricultural Heritage Systems (GIAHS) sites) are under threat from increased soil degradation due to climate change and land abandonment. Remote sensing can assist in the assessment and monitoring of such cultural ecosystem services. However, due to the limitations imposed by rugged topography and the occurrence of vegetation, the application of a single high-resolution topography (HRT) technique is challenging in these particular agricultural environments. Therefore, data fusion of HRT techniques (terrestrial laser scanning (TLS) and aerial/terrestrial structure from motion (SfM)) was tested for the first time in this context (terraces), to the best of our knowledge, to overcome specific detection problems such as the complex topographic and landcover conditions of the terrace systems. SfM–TLS data fusion methodology was trialed in order to produce very high-resolution digital terrain models (DTMs) of two agricultural terrace areas, both characterized by the presence of vegetation that covers parts of the subvertical surfaces, complex morphology, and inaccessible areas. In the unreachable areas, it was necessary to find effective solutions to carry out HRT surveys; therefore, we tested the direct georeferencing (DG) method, exploiting onboard multifrequency GNSS receivers for unmanned aerial vehicles (UAVs) and postprocessing kinematic (PPK) data. The results showed that the fusion of data based on different methods and acquisition platforms is required to obtain accurate DTMs that reflect the real surface roughness of terrace systems without gaps in data. Moreover, in inaccessible or hazardous terrains, a combination of direct and indirect georeferencing was a useful solution to reduce the substantial inconvenience and cost of ground control point (GCP) placement. We show that in order to obtain a precise data fusion in these complex conditions, it is essential to utilize a complete and specific workflow. This workflow must incorporate all data merging issues and landcover condition problems, encompassing the survey planning step, the coregistration process, and the error analysis of the outputs. The high-resolution DTMs realized can provide a starting point for land degradation process assessment of these agriculture environments and supplies useful information to stakeholders for better management and protection of such important heritage landscapes.

Radial and tangential velocity effects of a probed scanning mirror on laser Doppler frequency shift

A laser Doppler vibrometer (LDV) is precise and fast in measuring the translational velocity of a vibrating diffuse surface. However, it could fail to measure the tangential velocity of a rotating mirror. While the specular reflection away from the mirror can be recovered by a retroreflective collector, the recovered LDV reading is found to deviate from the true tangential velocity of the probed scanning mirror. This happens because the probed spot shifts radially along the rotating mirror surface and thus introduces extra Doppler shift, while the laser beam is aimed at a constant height on the scanning mirror. Here, we derive an analytical relationship between the laser Doppler shift and the tangential velocity of the measured spot. With the input of the prescribed scan profile, we recover the true reading of tangential velocity of the scanning mirror even at a large rotational angle. This corrected LDV reading is as precise as the measurement by a high-speed camera.

Stability Assessment of Coastal Cliffs Incorporating Laser Scanning Technology and a Numerical Analysis

We investigated the cliff coast in Jastrzebia Gora, Poland. The measurements that were taken between 2014 and 2018 by applying terrestrial, mobile, and airborne laser scanning describe a huge geometric modification involving dislocations in a 2.5 m range. Differential maps and a volumetric change analysis made it possible to identify the most deformed cliff’s location. Part of the monitoring of coastal change involved the measurement of a cliff sector in order to determine the soil mass flow down the slope. A full geometric image of the cliff was complemented by a stability assessment that incorporated numerical methods. The analysis showed that the stability coefficients, assuming a particular soil strata layout and geotechnical parameters, are unsafely close to the limit value. Moreover, the numerical computations, which were performed under simplifying assumptions, were not able to capture a multitude of other random factors that may have an impact on the soil mass stability. Thus, displacements of both reinforced soil and gabions were detected that are intended to prevent the cliff from deforming and to protect the infrastructure in its vicinity. The array of applied measurement methods provides a basis for the development of research aimed at optimization of applied tools, safety improvements, and a rapid reaction to threats.

Long-range depth imaging using a single-photon detector array and non-local data fusion

The ability to measure and record high-resolution depth images at long stand-off distances is important for a wide range of applications, including connected and automotive vehicles, defense and security, and agriculture and mining. In LIDAR (light detection and ranging) applications, single-photon sensitive detection is an emerging approach, offering high sensitivity to light and picosecond temporal resolution, and consequently excellent surface-to-surface resolution. The use of large format CMOS (complementary metal-oxide semiconductor) single-photon detector arrays provides high spatial resolution and allows the timing information to be acquired simultaneously across many pixels. In this work, we combine state-of-the-art single-photon detector array technology with non-local data fusion to generate high resolution three-dimensional depth information of long-range targets. The system is based on a visible pulsed illumination system at a wavelength of 670 nm and a 240 × 320 array sensor, achieving sub-centimeter precision in all three spatial dimensions at a distance of 150 meters. The non-local data fusion combines information from an optical image with sparse sampling of the single-photon array data, providing accurate depth information at low signature regions of the target.

Detectability of Repeated Airborne Laser Scanning for Mountain Landslide Monitoring

Multi-temporal airborne laser scanning (ALS) surveys have become a prime consideration for detecting landslide movements and evaluating landslide risk in mountain areas. The minimum elevation change (or detectability) that can be detected by repeated ALS surveys has become a critical threshold for landslide researchers and engineers to decide if ALS is a capable tool for detecting targeted landslides and arranging the minimum time span between two scans if ALS is a choice. The National Center for Airborne Laser Mapping (NCALM) at the University of Houston conducted three repeated ALS surveys at the Slumgullion landslide site in Colorado, U.S. over one week in July of 2015. These repeated ALS surveys provide valuable datasets for evaluating the vertical detectability of multi-temporal ALS surveys in a typical mountain area. According to this study, the difference of digital elevation models (DDEM) derived from ALS has the ability of detecting a minimum elevation change of 5 cm over flatter and moderately rugged terrain areas (slope < 20 degrees) and a minimum of a 10-cm elevation change over rugged terrain areas (20 degrees < slope < 40 degrees). However, the DDEM values over highly rugged terrain areas (slope > 40 degrees), such as cliff and landslide scarps, should be interpolated with caution. Global Navigation Satellite Systems (GNSS) and Terrestrial Laser Scanning (TLS) surveys were also performed at the middle portion of the landslide area for assessing the accuracy of ALS datasets. The accuracy of ALS varies from approximately one decimeter (~10 cm) to one foot (~30 cm) depending on the roughness of terrain surface and vegetation coverage (point density). The detectability and accuracy estimates of ALS measurements obtained from the case study could be used as a reference for estimating the performance of modern ALS in mountain areas with similar topography and vegetation coverage.

Systematic Comparison of Power Line Classification Methods from ALS and MLS Point Cloud Data

Power lines classification is important for electric power management and geographical objects extraction using LiDAR (light detection and ranging) point cloud data. Many supervised classification approaches have been introduced for the extraction of features such as ground, trees, and buildings, and several studies have been conducted to evaluate the framework and performance of such supervised classification methods in power lines applications. However, these studies did not systematically investigate all of the relevant factors affecting the classification results, including the segmentation scale, feature selection, classifier variety, and scene complexity. In this study, we examined these factors systematically using airborne laser scanning and mobile laser scanning point cloud data. Our results indicated that random forest and neural network were highly suitable for power lines classification in forest, suburban, and urban areas in terms of the precision, recall, and quality rates of the classification results. In contrast to some previous studies, random forest yielded the best results, while Naïve Bayes was the worst classifier in most cases. Random forest was the more robust classifier with or without feature selection for various LiDAR point cloud data. Furthermore, the classification accuracies were directly related to the selection of the local neighborhood, classifier, and feature set. Finally, it was suggested that random forest should be considered in most cases for power line classification.

Considerations for Achieving Cross-Platform Point Cloud Data Fusion across Different Dryland Ecosystem Structural States

Remotely sensing recent growth, herbivory, or disturbance of herbaceous and woody vegetation in dryland ecosystems requires high spatial resolution and multi-temporal depth. Three dimensional (3D) remote sensing technologies like lidar, and techniques like structure from motion (SfM) photogrammetry, each have strengths and weaknesses at detecting vegetation volume and extent, given the instrument's ground sample distance and ease of acquisition. Yet, a combination of platforms and techniques might provide solutions that overcome the weakness of a single platform. To explore the potential for combining platforms, we compared detection bias amongst two 3D remote sensing techniques (lidar and SfM) using three different platforms [ground-based, small unmanned aerial systems (sUAS), and manned aircraft]. We found aerial lidar to be more accurate for characterizing the bare earth (ground) in dense herbaceous vegetation than either terrestrial lidar or aerial SfM photogrammetry. Conversely, the manned aerial lidar did not detect grass and fine woody vegetation while the terrestrial lidar and high resolution near-distance (ground and sUAS) SfM photogrammetry detected these and were accurate. UAS SfM photogrammetry at lower spatial resolution under-estimated maximum heights in grass and shrubs. UAS and handheld SfM photogrammetry in near-distance high resolution collections had similar accuracy to terrestrial lidar for vegetation, but difficulty at measuring bare earth elevation beneath dense herbaceous cover. Combining point cloud data and derivatives (i.e., meshes and rasters) from two or more platforms allowed for more accurate measurement of herbaceous and woody vegetation (height and canopy cover) than any single technique alone. Availability and costs of manned aircraft lidar collection preclude high frequency repeatability but this is less limiting for terrestrial lidar, sUAS and handheld SfM. The post-processing of SfM photogrammetry data became the limiting factor at larger spatial scale and temporal repetition. Despite the utility of sUAS and handheld SfM for monitoring vegetation phenology and structure, their spatial extents are small relative to manned aircraft.

Buried shallow fault slip from the South Napa earthquake revealed by near-field geodesy

Earthquake-related fault slip in the upper hundreds of meters of Earth's surface has remained largely unstudied because of challenges measuring deformation in the near field of a fault rupture. We analyze centimeter-scale accuracy mobile laser scanning (MLS) data of deformed vine rows within ±300 m of the principal surface expression of the M (magnitude) 6.0 2014 South Napa earthquake. Rather than assuming surface displacement equivalence to fault slip, we invert the near-field data with a model that allows for, but does not require, the fault to be buried below the surface. The inversion maps the position on a preexisting fault plane of a slip front that terminates ~3 to 25 m below the surface coseismically and within a few hours postseismically. The lack of surface-breaching fault slip is verified by two trenches. We estimate near-surface slip ranging from ~0.5 to 1.25 m. Surface displacement can underestimate fault slip by as much as 30%. This implies that similar biases could be present in short-term geologic slip rates used in seismic hazard analyses. Along strike and downdip, we find deficits in slip: The along-strike deficit is erased after ~1 month by afterslip. We find no evidence of off-fault deformation and conclude that the downdip shallow slip deficit for this event is likely an artifact. As near-field geodetic data rapidly proliferate and will become commonplace, we suggest that analyses of near-surface fault rupture should also use more sophisticated mechanical models and subsurface geomechanical tests.

Multi-beam single-photon-counting three-dimensional imaging lidar

Photon-counting laser ranging has attracted a lot of research interest for its application in the altimeter. In this letter, we report a large scale multi-beam photon-counting laser imaging system by using 100 laser beams in linear array as the light source. Taking advantage of a 100-channel low-noise high-efficiency single-photon detector, the three-dimensional image of remote targets could be constructed rapidly according to the time-of-flight measurement. This system provides a solution for a high-speed, high-resolution, low energy-consumption pushbroom airborne or spaceborne laser altimeter.

Identifying Ancient Settlement Patterns through LiDAR in the Mosquitia Region of Honduras

The Mosquitia ecosystem of Honduras occupies the fulcrum between the American continents and as such constitutes a critical region for understanding past patterns of socio-political development and interaction. Heavy vegetation, rugged topography, and remoteness have limited scientific investigation. This paper presents prehistoric patterns of settlement and landuse for a critical valley within the Mosquitia derived from airborne LiDAR scanning and field investigation. We show that (i) though today the valley is a wilderness it was densely inhabited in the past; (ii) that this population was organized into a three-tiered system composed of 19 settlements dominated by a city; and, (iii) that this occupation was embedded within a human engineered landscape. We also add to a growing body of literature that demonstrates the utility of LiDAR as means for rapid cultural assessments in undocumented regions for analysis and conservation. Our ultimate hope is for our work to promote protections to safeguard the unique and critically endangered Mosquitia ecosystem and other similar areas in need of preservation.