Measurement and Evaluation of Roadway Geometry for Safety Analyses and Pavement Material Volume Estimation for Resurfacing and Rehabilitation Using Mobile LiDAR and Imagery-based Point Clouds

Roadway safety is a multifaceted issue affected by several variables including geometric design features of the roadway, weather conditions, sight distance issues, user behavior, and pavement surface condition. In recent years, transportation agencies have demonstrated a growing interest in utilizing Light Detecting and Ranging (LiDAR) and other remote sensing technologies to enhance data collection productivity, safety, and facilitate the development of strategies to maintain and improve existing roadway infrastructure. Studies have shown that three-dimensional (3D) point clouds acquired using mobile LiDAR systems are highly accurate, dense, and have numerous applications in transportation. Point cloud data applications include extraction of roadway geometry features, asset management, as-built documentation, and maintenance operations. Another source of highly accurate 3D data in the form of point clouds is close-range aerial photogrammetry using unmanned aerial vehicle (UAV) systems. One of the main advantages of these systems over conventional surveying methods is the ability to obtain accurate continuous data in a timely manner. Traditional surveying techniques allow for the collection of road surface data only at specified intervals. Point clouds from LiDAR and imagery-based data can be imported into modeling and design software to create a virtual representation of constructed roadways using 3D models. From a roadway safety assessment standpoint, mobile LiDAR scanning (MLS) systems and UAV close-range photogrammetry (UAV-CRP) can be used as effective methods to produce accurate digital representations of existing roadways for various safety evaluations. This research used LiDAR data collected by five vendors and UAV imagery data collected by the research team to achieve the following objectives: a) evaluate the accuracy of point clouds from MLS and UAV imagery data for collection roadway cross slopes for system-wide cross slope verification; b) evaluate the accuracy of as-built geometry features extracted from MLS and UAV imagery-based point clouds for estimating design speeds on horizontal and vertical curves of existing roadways; c) Determine whether MLS and UAV imagery-based point clouds can be used to produce accurate road surface models for material volume estimation purposes. Ground truth data collected using manual field survey measurements were used to validate the results of this research. Cross slope measurements were extracted from ten randomly selected stations along a 4-lane roadway. This resulted in a total of 42 cross slope measurements per data set including measurements from left turn lanes. The roadway is an urban parkway classified as an urban principal arterial located in Anderson, South Carolina. A comparison of measurements from point clouds and measurements from field survey data using t-test statical analysis showed that deviations between field survey data and MLS and UAV imagery-based point clouds were within the acceptable range of ±0.2% specified by SHRP2 and the South Carolina Department of Transportation (SCDOT). A surface-to-surface method was used to compute and compare material volumes between terrain models from MLS and UAV imagery-based point clouds and a terrain model from field survey data. The field survey data consisted of 424 points collected manually at sixty-nine 100-ft stations over the 1.3-mile study area. The average difference in height for all MLS data was less than 1 inch except for one of the vendors which appeared to be due to a systematic error. The average height difference for the UAV imagery-based data was approximately 1.02 inches. The relatively small errors indicated that these data sets can be used to obtain reliable material volume estimates. Lastly, MLS and UAV imagery-based point clouds were used to obtain horizontal curve radii and superelevation data to estimate design speeds on horizontal curves. Results from paired t-test statistical analyses using a 95% confidence level showed that geometry data extracted from point clouds can be used to obtain realistic estimates of design speeds on horizontal curves. Similarly, road grade and sight distance were obtained from point clouds for design speed estimation on crest and sag vertical curves. A similar approach using a paired t-test statistical analysis at a 95% confidence level showed that point clouds can be used to obtain reliable design speed information on crest and sag vertical curves. The proposed approach offers advantages over extracting information from design drawings which may provide an inaccurate representation of the as-built roadway

NADIR AND OBLIQUE UAV PHOTOGRAMMETRY TECHNIQUES FOR QUANTITATIVE ROCK FALL EVALUATION IN THE RIMROCKS OF SOUTH-CENTRAL MONTANA

As our cities expand into geologically sensitive areas across the greater Rocky Mountain region and beyond, quantitative methods of assessment are increasingly critical for the development of evidence-based alternatives to avoid or mitigate geologic hazards. Unmanned Aerial Vehicle (UAV) photogrammetry can improve these geologic investigations by enabling remote visual inspection, measurement, and spatial analysis while eliminating many of the physical access limitations that contribute to field sampling bias and human error. UAV photogrammetry technology was employed to evaluate fragmental rock fall hazards at two locations in the Rimrocks region of south-central Montana, Zimmerman Trail Road and Phipps Park. At these sites, active retrogressive rock slope instability caused by differential erosion has produced damaging rock fall. Nadir and oblique imagery of the 35-acre Zimmerman Trail Road and 13-acre Phipps Park study areas was acquired with a DJI Phantom 4 Pro UAV and processed into digital photogrammetry with Pix4Dmapper. Remote methods of analysis were employed to measure the orientation of discontinuities in rock fall source areas and to quantify rock fall susceptibility. At Zimmerman Trail Road, photogrammetry data products were used to numerically differentiate rock fall hazard zones along the 0.3-mile long rock slope in accordance with the detailed Rock Fall Hazard Rating System (Pierson, 1991). At Phipps Park, photogrammetry was used to measure the size, run out distance, and change in elevation of high energy rock fall and to generate 2D and 3D slope profiles, which were used to model potential future rock fall. The methods and findings demonstrate how nadir and oblique UAV photogrammetry can be used to implement quantitative, defensible approaches for evaluating rock fall susceptibility and run out potential in geologic investigations of fragmental rock fall hazard areas

UAV photogrammetry in the post-earthquake scenario: case studies in L'Aquila

The main advantage of using the Unmanned Aerial Vehicle (UAV) photogrammetry in a post-earthquake scenario is the ability to completely document the state of the structures and infrastructures, damaged by the earthquake, ensuring the safety of all operators during the data acquisition activities. The safety and accessibility aspect in the area is of crucial concern after an earthquake and sometimes many areas may be inaccessible, but, at the same time, it is necessary to collect data in order to monitor and evaluate the damage. The development of new algorithms in the field of Computer Vision drastically improved the degree of automation of the 3D point clouds generation using the photogrammetry techniques. In addition, data acquisition techniques using the UAV allow a complete 3D model with the highest possible resolution especially with respect to the conventional satellite or aerial photogrammetry to be produced. These advantages make the UAV photogrammetry highly suitable for surveys in a geo-hazard context as in a post-earthquake scenario. Some results from surveys carried out with the UAV photogrammetry after L'Aquila Earthquake occurred in 2009 will be presented and discussed

Accuracy of UAV Photogrammetry in Glacial and Periglacial Alpine Terrain: A Comparison With Airborne and Terrestrial Datasets

Unoccupied Aerial Vehicles (UAVs) equipped with optical instruments are increasingly deployed in high mountain environments to investigate and monitor glacial and periglacial processes. The comparison and fusion of UAV data with airborne and terrestrial data offers the opportunity to analyse spatio-temporal changes in the mountains and to upscale findings from local UAV surveys to larger areas. However, due to the lack of gridded high-resolution data in alpine terrain, the specific challenges and uncertainties associated with the comparison and fusion of multi-temporal data from different platforms in this environment are not well known. Here we make use of UAV, airborne, and terrestrial data from four (peri)glacial alpine study sites with different topographic settings. The aim is to assess the accuracy of UAV photogrammetric products in complex terrain, to point out differences to other products, and to discuss best practices regarding the fusion of multi-temporal data. The surface geometry and characteristic geomorphological features of the four alpine sites are well captured by the UAV data, but the positional accuracies vary greatly. They range from 15 cm (root-mean-square error) for the smallest survey area (0.2 km2) with a high ground control point (GCP) density (40 GCPs km−2) to 135 cm for the largest survey area (>2.5 km2) with a lower GCP density (<10 GCPs km−2). Besides a small number and uneven distribution of GCPs, a low contrast, and insufficient lateral image overlap (<50–70%) seem to be the main causes for the distortions and artefacts found in the UAV data. Deficiencies both in the UAV and airborne data are the reason for horizontal deviations observed between the datasets. In steep terrain, horizontal deviations of a few decimetres may result in surface elevation change errors of several metres. An accurate co-registration and evaluation of multi-temporal UAV, airborne, and terrestrial data using tie points in stable terrain is therefore of utmost importance when it comes to the investigation of surface displacements and elevation changes in the mountains. To enhance the accuracy and quality of UAV photogrammetry, the use of UAVs equipped with multi-spectral cameras and high-precision positioning systems is recommended, especially in rugged terrain and snow-covered areas

Archaeological site monitoring: UAV photogrammetry can be an answer

During archaeological excavations it is important to monitor the new excavated areas and findings day by day in order to be able to plan future excavation activities. At present, this daily activity is usually performed by using total stations, which survey the changes of the archaeological site: the surveyors are asked to produce day by day draft plans and sections which allow archaeologists to plan their future activities. The survey is realized during the excavations or just at the end of every working day and drawings have to be produced as soon as possible in order to allow the comprehension of the work done and to plan the activities for the following day. By using this technique, all the measurements, even those not necessary for the day after, have to be acquired in order to avoid a ‘loss of memory'. A possible alternative to this traditional approach is aerial photogrammetry, if the images can be acquired quickly and at a taken distance able to guarantee the necessary accuracy of a few centimeters. Today the use of UAVs (Unmanned Aerial Vehicles) can be considered a proven technology able to acquire images at distances ranging from 4 m up to 20 m: and therefore as a possible monitoring system to provide the necessary information to the archaeologists day by day. The control network, usually present at each archaeological site, can give the stable control points useful for orienting a photogrammetric block acquired by using an UAV equipped with a calibrated digital camera and a navigation control system able to drive the aircraft following a pre-planned flight scheme. Modern digital photogrammetric software can solve for the block orientation and generate a DSM automatically, allowing rapid orthophoto generation and the possibility of producing sections and plans. The present paper describes a low cost UAV system realized by the research group of the Politecnico di Torino and tested on a Roman villa archaeological site located in Aquileia (Italy), a well-known UNESCO WHL site. The results of automatic orientation and orthophoto production are described in terms of their accuracy and the completeness of information guaranteed for archaeological site excavation managemen

A Comparative Analysis of Phytovolume Estimation Methods Based on UAV-Photogrammetry and Multispectral Imagery in a Mediterranean Forest

Management and control operations are crucial for preventing forest fires, especially in Mediterranean forest areas with dry climatic periods. One of them is prescribed fires, in which the biomass fuel present in the controlled plot area must be accurately estimated. The most used methods for estimating biomass are time-consuming and demand too much manpower. Unmanned aerial vehicles (UAVs) carrying multispectral sensors can be used to carry out accurate indirect measurements of terrain and vegetation morphology and their radiometric characteristics. Based on the UAV-photogrammetric project products, four estimators of phytovolume were compared in a Mediterranean forest area, all obtained using the difference between a digital surface model (DSM) and a digital terrain model (DTM). The DSM was derived from a UAV-photogrammetric project based on the structure from a motion algorithm. Four different methods for obtaining a DTM were used based on an unclassified dense point cloud produced through a UAV-photogrammetric project (FFU), an unsupervised classified dense point cloud (FFC), a multispectral vegetation index (FMI), and a cloth simulation filter (FCS). Qualitative and quantitative comparisons determined the ability of the phytovolume estimators for vegetation detection and occupied volume. The results show that there are no significant differences in surface vegetation detection between all the pairwise possible comparisons of the four estimators at a 95% confidence level, but FMI presented the best kappa value (0.678) in an error matrix analysis with reference data obtained from photointerpretation and supervised classification. Concerning the accuracy of phytovolume estimation, only FFU and FFC presented differences higher than two standard deviations in a pairwise comparison, and FMI presented the best RMSE (12.3 m) when the estimators were compared to 768 observed data points grouped in four 500 m2 sample plots. The FMI was the best phytovolume estimator of the four compared for low vegetation height in a Mediterranean forest. The use of FMI based on UAV data provides accurate phytovolume estimations that can be applied on several environment management activities, including wildfire prevention. Multitemporal phytovolume estimations based on FMI could help to model the forest resources evolution in a very realistic way

MULTISCALE DOCUMENTATION AND MONITORING OF L'AQUILA HISTORICALCENTRE USING UAV PHOTOGRAMMETRY

Nowadays geomatic techniques can guarantee not only a precise and accurate survey for the documentation of our historical heritage but also a solution to monitor its behaviour over time after, for example, a catastrophic event (earthquakes, landslides, ecc). Europe is trying to move towards harmonized actions to store information on cultural heritage (MIBAC with the ICCS forms, English heritage with the MIDAS scheme, etc) but it would be important to provide standardized methods in order to perform measuring operations to collect certified metric data. The final result could be a database to support the entire management of the cultural heritage and also a checklist of "what to do" and "when to do it". The wide range of geomatic techniques provides many solutions to acquire, to organize and to manage data at a multiscale level: high resolution satellite images can provide information in a short time during the "early emergency" while UAV photogrammetry and laser scanning can provide digital high resolution 3D models of buildings, ortophotos of roofs and facades and so on. This paper presents some multiscale survey case studies using UAV photogrammetry: from a minor historical village (Aielli) to the centre of L'Aquila (Santa Maria di Collemaggio Church) from the post-emergency to now. This choice has been taken not only to present how geomatics is an effective science for modelling but also to present a complete and reliable way to perform conservation and/or restoration through precise monitoring techniques, as shown in the third case study