Laser altimetry (lidar) is a remote-sensing technology that holds tremendous promise for mapping snow depth in snow hydrology and avalanche applications. Recently lidar has seen a dramatic widening of applications in the natural sciences, resulting in technological improvements and an increase in the availability of both airborne and ground-based sensors. Modern sensors allow mapping of vegetation heights and snow or ground surface elevations below forest canopies. Typical vertical accuracies for airborne datasets are decimeter-scale with order 1 m point spacings. Ground-based systems typically provide millimeter-scale range accuracy and sub-meter point spacing over 1 m to several kilometers. Many system parameters, such as scan angle, pulse rate and shot geometry relative to terrain gradients, require specification to achieve specific point coverage densities in forested and/or complex terrain. Additionally, snow has a significant volumetric scattering component, requiring different considerations for error estimation than for other Earth surface materials. We use published estimates of light penetration depth by wavelength to estimate radiative transfer error contributions. This paper presents a review of lidar mapping procedures and error sources, potential errors unique to snow surface remote sensing in the near-infrared and visible wavelengths, and recommendations for projects using lidar for snow-depth mapping.

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Lidar measurement of snow depth: a review

The Airborne Snow Observatory: Fusion of scanning lidar, imaging spectrometer, and physically-based modeling for mapping snow water equivalent and snow albedo

In this paper, we study estimator inconsistency in vision-aided inertial navigation systems (VINS) from the standpoint of system's observability. We postulate that a leading cause of inconsistency is the gain of spurious information along unobservable directions, which results in smaller uncertainties, larger estimation errors, and divergence. We develop an observability constrained VINS (OC-VINS), which explicitly enforces the unobservable directions of the system, hence preventing spurious information gain and reducing inconsistency. This framework is applicable to several variants of the VINS problem such as visual simultaneous localization and mapping (V-SLAM), as well as visual-inertial odometry using the multi-state constraint Kalman filter (MSC-KF). Our analysis, along with the proposed method to reduce inconsistency, are extensively validated with simulation trials and real-world experimentation.

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Consistency Analysis and Improvement of Vision-aided Inertial Navigation

Laser scanning and digital outcrop geology in the petroleum industry: A review

Mobile LiDAR technology is currently one of the attractive topics in the fields of remote sensing and laser scanning. Mobile LiDAR enables a rapid collection of enormous volumes of highly dense, irregularly distributed, accurate geo-referenced data, in the form of three-dimensional (3D) point clouds. This technology has been gaining popularity in the recognition of roads and road-scene objects. A thorough review of available literature is conducted to inform the advancements in mobile LiDAR technologies and their applications in road information inventory. The literature review starts with a brief overview of mobile LiDAR technology, including system components, direct geo-referencing, data error analysis and geometrical accuracy validation. Then, this review presents a more in-depth description of current mobile LiDAR studies on road information inventory, including the detection and extraction of road surfaces, small structures on the road surfaces and pole-like objects. Finally, the challenges ...

Use of mobile LiDAR in road information inventory: a review

Abstract Mobile laser scanning (MLS) is the latest approach towards fast and cost-efficient acquisition of 3-dimensional spatial data. Accurately evaluating the boresight alignment in MLS systems is an obvious necessity. However, recent systems available on the market may lack of suitable and efficient practical workflows on how to perform this calibration. This paper discusses an innovative method for accurately determining the boresight alignment of MLS systems by employing 3D laser scanners. Scanning objects using a 3D laser scanner operating in a 2D line-scan mode from various different runs and scan directions provides valuable scan data for determining the angular alignment between inertial measurement unit and laser scanner. Field data is presented demonstrating the final accuracy of the calibration and the high quality of the point cloud acquired during an MLS campaign.

/pdf/boresight-alignment-method-for-mobile-laser-scanning-systems-no0c54v0kl.pdf

Boresight alignment method for mobile laser scanning systems

A method for measuring distances of targets by measuring the time of flight of pulses, in particular laser pulses, reflected on those targets, including the steps of; transmitting pulses having a pulse interval which varies according to a modulation signal as transmitted pulses, and concomitantly recording of reflected pulses as received pulses; determining a first series of distance measurement values from times of flight between transmitted pulses and those received pulses which are respectively received within a first time window following each transmitted pulse; determining at least a second series of distance measurement values from times of flight between transmitted pulses and those received pulses which are respectively received within a second time window following each transmitted pulse; and determining that series of distance measurement values which is least affected by the modulation signal as result of the distance measurement.

Method for measuring distances

The method involves performing laser scanning of two sets of positions and locations to generate two three-dimensional images of a surrounding area (17), respectively. The two sets of positions and locations are measured by an inertial measurement unit (IMU)/global navigation satellite system (GNSS) subsystem (22). Objects in the images are detected, and one of the measured locations is corrected for position measurement errors to obtain corrected location measurement data, where the errors result from comparison of two spatial locations of the objects in the respective images.

Method for improving position and orientation measurement data

Correctly determining a measurement range in light detection and ranging instruments, based on time-of-flight measurements on laser pulses, requires the association of each received echo pulse with its causative emitted laser pulse. Without further precautions, this definite association is only possible under specific conditions constraining the usability of range finders and laser scanners with very high measurement rates. We give an introduction to known techniques for avoiding and resolving range ambiguities. The specific disadvantages of these methods led to the development of a technique based on pulse-position modulation (PPM) of the laser pulse train using a pseudorandom noise signal and the subsequent analysis of the impact of the PPM on groups of consecutive range measurements. The error probability of our approach has been evaluated by simulations based on real scan data. The use of a discrete uniform distribution of amplitudes as a modulation signal shows high detection robustness even for difficult terrain like forest areas. The encouraging results of the simulations led to the practical implementation of PPM to our laser scanners and the development of the associated software RiMTA, which resolves range ambiguities without the necessity of a priori information on the target situation and without any user interaction required.

Resolving range ambiguities in high-repetition rate airborne light detection and ranging applications

Time-of-flight (ToF) range measurements rely on the unambiguous association of each received echo signal to its causative emitted pulse signal. This definite association is difficult when measuring long ranges at a high repetition rate, resulting in ambiguous range measurements. While methods and algorithms exist to overcome this fundamental problem of ToF measurement techniques like radar these may not be directly applied to lidar without adaptations. Especially, in airborne laser scanning, up to now it was a requirement to strictly avoid range ambiguities during data acquisition. We present a new method for resolving range ambiguities fully automatically in scanning lidar, enabling measurements exceeding the maximum unambiguous measurement range by far. As a theoretical foundation of our approach, we introduce a specific model of the lidar transmission path (i.e., emitter–target–receiver) accounting for the time-variability of consecutive measurements. Based on this model, we discuss the influence of intentional variation of the intervals between pulse emissions on the intervals of successively received echoes and delineate an algorithm for automated, definitive association of pulse emissions and their resulting echoes. Simulation results indicate a probability of incorrect associations of <10 −5 , which we positively proved by applying this technique to real-world scan data.

Peter Rieger

Papers

Boresight alignment method for mobile laser scanning systems

Method for measuring distances

Method for improving position and orientation measurement data

Resolving range ambiguities in high-repetition rate airborne light detection and ranging applications

Range ambiguity resolution technique applying pulse-position modulation in time-of-flight scanning lidar applications