scholarly journals Measurement Strategies for Street-Level SLAM Laser Scanning of Urban Environments

2020 ◽  
Vol 27 (1) ◽  
pp. 1-19
Author(s):  
Aino Keitaanniemi ◽  
Antero Kukko ◽  
Juho-Pekka Virtanen ◽  
Matti T. Vaaja
Keyword(s):  
Urban Environment ◽  
Laser Scanning ◽  
Point Clouds ◽  
Satellite System ◽  
Urban Environments ◽  
Measurement Unit ◽  
Street Level ◽  
Measurement Strategy ◽  
Laser Scanners ◽  
Measurement Strategies

Data collection for street-level mapping is currently executed with terrestrial (TLS) or mobile laser scanners (MLS). However, these methods have disadvantages such as TLS requiring a lot of time and MLS being dependent on the global navigation satellite system (GNSS) and an inertial measurement unit (IMU). These are not problems if we use simultaneous localization and mapping (SLAM) based laser scanners. We studied the utility of a SLAM ZEB-REVO scanner for mapping street-level objects in an urban environment by analyzing the geometric and visual differences with a TLS reference. In addition to this, we examined the influence of traffic on the measurement strategy. The results of the study showed that SLAM-based laser scanners can be used for street-level mapping. However, the measurement strategy affects the point clouds. The strategy of walking trajectory in loops produced a 2 cm RMS and 4-6 mm mode of error even in not optimal situations of the sensor in the urban environment. However, it was possible to get an RMS under 2.2 cm and a 32 cm mode of error with other measurement strategies.

scholarly journals Feasibility of Mobile Laser Scanning towards Operational Accurate Road Rut Depth Measurements

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1180
Author(s):  
Aimad El Issaoui ◽  
Ziyi Feng ◽  
Matti Lehtomäki ◽  
Eric Hyyppä ◽  
Hannu Hyyppä ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Laser Scanning ◽  
Satellite System ◽  
Measurement Unit ◽  
High Definition ◽  
Depth Measurement ◽  
Laser Scanners ◽  
Fully Automatic ◽  
Global Navigation Satellite ◽  
Automatic Algorithm

This paper studied the applicability of the Roamer-R4DW mobile laser scanning (MLS) system for road rut depth measurement. The MLS system was developed by the Finnish Geospatial Research Institute (FGI), and consists of two mobile laser scanners and a Global Navigation Satellite System (GNSS)-inertial measurement unit (IMU) positioning system. In the study, a fully automatic algorithm was developed to calculate and analyze the rut depths, and verified in 64 reference pavement plots (1.0 m × 3.5 m). We showed that terrestrial laser scanning (TLS) data is an adequate reference for MLS-based rutting studies. The MLS-derived rut depths based on 64 plots resulted in 1.4 mm random error, which can be considered adequate precision for operational rutting depth measurements. Such data, also covering the area outside the pavement, would be ideal for multiple road environment applications since the same data can also be used in applications, from high-definition maps to autonomous car navigation and digitalization of street environments over time and in space.

scholarly journals THE POTENTIAL OF LIGHT LASER SCANNERS DEVELOPED FOR UNMANNED AERIAL VEHICLES – THE REVIEW AND ACCURACY

2016 ◽  
Vol XLII-2/W2 ◽  
pp. 87-95 ◽  
Author(s):  
M. Pilarska ◽  
W. Ostrowski ◽  
K. Bakuła ◽  
K. Górski ◽  
Z. Kurczyński
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Laser Scanning ◽  
Measurement Accuracy ◽  
Laser Scanner ◽  
Satellite System ◽  
Measurement Unit ◽  
Aerial Vehicles ◽  
Laser Scanners ◽  
Final Measurement ◽  
Global Navigation Satellite

Modern photogrammetry and remote sensing have found small Unmanned Aerial Vehicles (UAVs) to be a valuable source of data in various branches of science and industry (e.g., agriculture, cultural heritage). Recently, the growing role of laser scanning in the application of UAVs has also been observed. Laser scanners dedicated to UAVs consist of four basic components: a laser scanner (LiDAR), an Inertial Measurement Unit (IMU), a Global Navigation Satellite System (GNSS) receiver and an on-board computer. The producers of the system provide users with detailed descriptions of the accuracies separately for each component. However, the final measurement accuracy is not given. This paper reviews state-of-the-art of laser scanners developed specifically for use on a UAV, presenting an overview of several constructions that are available nowadays. The second part of the paper is focussed on analysing the influence of the sensor accuracies on the final measurement accuracy. Mathematical models developed for Airborne Laser Scanning (ALS) accuracy analyses are used to estimate the theoretical accuracies of different scanners with conditions typical for UAV missions. Finally, the theoretical results derived from the mathematical simulations are compared with an experimental use case.

scholarly journals Growing Value: Describing The Nature Of The Relationship Between Street-Level Greenery and Housing Prices in Toronto

2021 ◽  
Author(s):  
Spencer Bridgwater
Keyword(s):  
Urban Environment ◽  
Housing Prices ◽  
Urban Forestry ◽  
Demographic Variables ◽  
Urban Environments ◽  
Developmental Context ◽  
Street Level ◽  
The Relationship ◽  
Aerial Perspective

The role of urban forestry has become increasingly important in the context of sustainability, both from an environmental context, and from a developmental context. Greenery in an urban environment has demonstrable implications for health, air quality, aesthetics, and land value, as described broadly across the literature. Until recently, studies on green urban canopies and housing prices have been limited in their methodology by using aerial-perspective data. The MIT Senseable City Lab in 2015 developed the Treepedia project, which uses Google Street View images to quantify greenery levels in urban environments. Using the green view index (GVI) data from the Treepedia project, street-level greenery densities were compared against housing prices across Toronto. Models for different property types, accounting for characteristic, locational, and demographic variables, were estimated. It was determined that a statistically significant relationship between street-level greenery and housing prices exists in Toronto for detached homes, semi-detached homes, row/townhouse units, condo apartments, and condo townhouses.

scholarly journals Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment

2019 ◽  
Vol 11 (4) ◽  
pp. 442 ◽  
Author(s):  
Zhen Li ◽  
Junxiang Tan ◽  
Hua Liu
Keyword(s):  
Inertial Measurement Unit ◽  
Point Clouds ◽  
Calibration Method ◽  
Satellite System ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Self Calibration ◽  
Global Navigation Satellite ◽  
Mean Square Errors ◽  
Scanning Systems

Mobile LiDAR Scanning (MLS) systems and UAV LiDAR Scanning (ULS) systems equipped with precise Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) positioning units and LiDAR sensors are used at an increasing rate for the acquisition of high density and high accuracy point clouds because of their safety and efficiency. Without careful calibration of the boresight angles of the MLS systems and ULS systems, the accuracy of data acquired would degrade severely. This paper proposes an automatic boresight self-calibration method for the MLS systems and ULS systems using acquired multi-strip point clouds. The boresight angles of MLS systems and ULS systems are expressed in the direct geo-referencing equation and corrected by minimizing the misalignments between points scanned from different directions and different strips. Two datasets scanned by MLS systems and two datasets scanned by ULS systems were used to verify the proposed boresight calibration method. The experimental results show that the root mean square errors (RMSE) of misalignments between point correspondences of the four datasets after boresight calibration are 2.1 cm, 3.4 cm, 5.4 cm, and 6.1 cm, respectively, which are reduced by 59.6%, 75.4%, 78.0%, and 94.8% compared with those before boresight calibration.

scholarly journals Processing Chain for Estimation of Tree Diameter from GNSS-IMU-Based Mobile Laser Scanning Data

2019 ◽  
Vol 11 (6) ◽  
pp. 615 ◽  
Author(s):  
Juraj Čerňava ◽  
Martin Mokroš ◽  
Ján Tuček ◽  
Michal Antal ◽  
Zuzana Slatkovská
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Forest Canopy ◽  
Point Clouds ◽  
Satellite System ◽  
Forest Road ◽  
Forest Mapping ◽  
Fitting Method ◽  
Progressive Technology ◽  
Global Navigation Satellite

Mobile laser scanning (MLS) is a progressive technology that has already demonstrated its ability to provide highly accurate measurements of road networks. Mobile innovation of the laser scanning has also found its use in forest mapping over the last decade. In most cases, existing methods for forest data acquisition using MLS result in misaligned scenes of the forest, scanned from different views appearing in one point cloud. These difficulties are caused mainly by forest canopy blocking the global navigation satellite system (GNSS) signal and limited access to the forest. In this study, we propose an approach to the processing of MLS data of forest scanned from different views with two mobile laser scanners under heavy canopy. Data from two scanners, as part of the mobile mapping system (MMS) Riegl VMX-250, were acquired by scanning from five parallel skid trails that are connected to the forest road. Misaligned scenes of the forest acquired from different views were successfully extracted from the raw MLS point cloud using GNSS time based clustering. At first, point clouds with correctly aligned sets of ground points were generated using this method. The loss of points after the clustering amounted to 33.48%. Extracted point clouds were then reduced to 1.15 m thick horizontal slices, and tree stems were detected. Point clusters from individual stems were grouped based on the diameter and mean GNSS time of the cluster acquisition. Horizontal overlap was calculated for the clusters from individual stems, and sufficiently overlapping clusters were aligned using the OPALS ICP module. An average misalignment of 7.2 mm was observed for the aligned point clusters. A 5-cm thick horizontal slice of the aligned point cloud was used for estimation of the stem diameter at breast height (DBH). DBH was estimated using a simple circle-fitting method with a root-mean-square error of 3.06 cm. The methods presented in this study have the potential to process MLS data acquired under heavy forest canopy with any commercial MMS.

scholarly journals MOVING OBJECT CLASSIFICATION USING MULTILAYER LASER SCANNING WITH SPACE SUBDIVISION FRAMEWORK

2020 ◽  
Vol V-4-2020 ◽  
pp. 103-108
Author(s):  
M. Nakagawa ◽  
M. Taguchi
Keyword(s):  
Real Time ◽  
Urban Areas ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Object Classification ◽  
Point Clouds ◽  
Satellite System ◽  
Space Subdivision ◽  
Position Data ◽  
Global Navigation Satellite

Abstract. In this paper, we focus on the development of intelligent construction vehicles to improve the safety of workers in construction sites. Generally, global navigation satellite system positioning is utilized to obtain the position data of workers and construction vehicles. However, construction fields in urban areas have poor satellite positioning environments. Therefore, we have developed a 3D sensing unit mounted on a construction vehicle for worker position data acquisition. The unit mainly consists of a multilayer laser scanner. We propose a real-time object measurement, classification and tracking methodology with the multilayer laser scanner. We also propose a methodology to estimate and visualize object behaviors with a spatial model based on a space subdivision framework consisting of agents, activities, resources, and modifiers. We applied the space subdivision framework with a geofencing approach using real-time object classification and tracking results estimated from temporal point clouds. Our methodology was evaluated using temporal point clouds acquired from a construction vehicle in drilling works.

scholarly journals Fusion of high resolution remote sensing images and terrestrial laser scanning for improved biomass estimation of maize

2014 ◽  
Vol XL-7 ◽  
pp. 101-108 ◽  
Author(s):  
C. Hütt ◽  
H. Schiedung ◽  
N. Tilly ◽  
G. Bareth
Keyword(s):  
High Resolution ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Satellite System ◽  
Biomass Estimation ◽  
Digital Elevation ◽  
Elevation Model ◽  
In The Beginning

In this study, images from the satellite system WorldView-2 in combination with terrestrial laser scanning (TLS) over a maize field in Germany are investigated. Simultaneously to the measurements a biomass field campaigns was carried out. From the point clouds of the terrestrial laser scanning campaigns crop surface models (CSM) from each scanning date were calculate to model plant growth over time. These results were resampled to match the spatial resolution of the WorldView-2 images, which had to orthorectified using a high resolution digital elevation model and atmosphere corrected using the ATCOR Software package. A high direct correlation of the NDVI calculated from the WorldView-2 sensor and the dry biomass was found in the beginning of June. At the same date, the heights from laser scanning can also explain a certain amount of the biomass variation (<i>r</i><sup>2</sup> = 0.6). By combining the NDVI from WorldView-2 and the height from the laser scanner with a linear model, the R2 reaches higher values of 0.86. To further understand the relationship between CSM derived crop heights and reflection indices, a comparison on a pixel basis was performed. Interestingly, the correlation of the NDVI and the crop height is rather low at the beginning of June (<i>r</i><sup>2</sup> = 0,4, <i>n</i> = 1857) and increases significantly (<i>R</i><sup>2</sup> = 0,79, <i>N</i> = 1857) at a later stage.

scholarly journals GEOMETRIC POINT QUALITY ASSESSMENT FOR THE AUTOMATED, MARKERLESS AND ROBUST REGISTRATION OF UNORDERED TLS POINT CLOUDS

2015 ◽  
Vol II-3/W5 ◽  
pp. 89-96 ◽  
Author(s):  
M. Weinmann ◽  
B. Jutzi
Keyword(s):  
3D Reconstruction ◽  
Laser Scanning ◽  
Incidence Angle ◽  
Point Clouds ◽  
Urban Environments ◽  
Coordinate Frame ◽  
Consistency Check ◽  
Geometric Point ◽  
Feature Correspondences ◽  
Urban Accessibility

The faithful 3D reconstruction of urban environments is an important prerequisite for tasks such as city modeling, scene interpretation or urban accessibility analysis. Typically, a dense and accurate 3D reconstruction is acquired with terrestrial laser scanning (TLS) systems by capturing several scans from different locations, and the respective point clouds have to be aligned correctly in a common coordinate frame. In this paper, we present an accurate and robust method for a keypoint-based registration of unordered point clouds via projective scan matching. Thereby, we involve a consistency check which removes unreliable feature correspondences and thus increases the ratio of inlier correspondences which, in turn, leads to a faster convergence of the RANSAC algorithm towards a suitable solution. This consistency check is fully generic and it not only favors geometrically smooth object surfaces, but also those object surfaces with a reasonable incidence angle. We demonstrate the performance of the proposed methodology on a standard TLS benchmark dataset and show that a highly accurate and robust registration may be achieved in a fully automatic manner without using artificial markers.

scholarly journals AN ENERGY-BASED APPROACH FOR DETECTION AND CHARACTERIZATION OF SUBTLE ENTITIES WITHIN LASER SCANNING POINT-CLOUDS

2016 ◽  
Vol XLI-B3 ◽  
pp. 167-171
Author(s):  
Reuma Arav ◽  
Sagi Filin
Keyword(s):  
Laser Scanning ◽  
Optimization Problem ◽  
Point Clouds ◽  
Urban Environments ◽  
Natural Environments ◽  
Detection Scheme ◽  
Airborne Laser ◽  
The Common ◽  
Geomorphological Features

Airborne laser scans present an optimal tool to describe geomorphological features in natural environments. However, a challenge arises in the detection of such phenomena, as they are embedded in the topography, tend to blend into their surroundings and leave only a subtle signature within the data. Most object-recognition studies address mainly urban environments and follow a general pipeline where the data are partitioned into segments with uniform properties. These approaches are restricted to man-made domain and are capable to handle limited features that answer a well-defined geometric form. As natural environments present a more complex set of features, the common interpretation of the data is still manual at large. In this paper, we propose a data-aware detection scheme, unbound to specific domains or shapes. We define the recognition question as an energy optimization problem, solved by variational means. Our approach, based on the level-set method, characterizes geometrically local surfaces within the data, and uses these characteristics as potential field for minimization. The main advantage here is that it allows topological changes of the evolving curves, such as merging and breaking. We demonstrate the proposed methodology on the detection of collapse sinkholes.

scholarly journals New Measurement Methods for Structure Deformation and Objects Exact Dimension Determination

2021 ◽  
Vol 906 (1) ◽  
pp. 012060
Author(s):  
Karel Pavelka ◽  
David Zahradník ◽  
Jaroslav Sedina ◽  
Karel Pavelka
Keyword(s):  
Laser Scanning ◽  
Data Transfer ◽  
Rapid Development ◽  
3D Models ◽  
Measurement Unit ◽  
Forthcoming Article ◽  
Repair Work ◽  
Close Range Photogrammetry ◽  
Laser Scanners ◽  
Close Range

Abstract The current rapid development of technologies enables new procedures for deformation and the detecting of construction defects and their modelling and monitoring in BIM. New instruments were developed for fast and sufficiently accurate mapping like personal mobile laser scanners (PLS). In the world of photography, the size of camera sensors is bigger, and the photographs are sharper. The rapid development of computer performance enables automatic and complex calculations, which lead to large sets of detailed 3D data and a high degree of automation. This influences photogrammetry and its methods. The results are more detailed and more accurate. Deformation, defects and exact dimensions (metrology) of different structures or objects can be currently measured by digital close-range photogrammetry. Cracks and cavities are monitored for structure status detection. This is important for planning reconstruction and for financial reasons. For structures like cooling towers, chimneys, or bridges can be created on a 3D model with a high texture resolution for finding and monitoring cracks and cavities. Deformations or defects that were found must be in scale, and measurable for the calculation of the scope of repair work and its price. The generated 3D object model can then be used for further measurements, for the price estimation of renovation, and for the creation of a BIM, in which all processes can be modelled and watched. Deformation can be monitored over time by creating additional models after a defined period. Captured 3D models from different periods can be compared in software like CloudCompare to determine the progress of degradational changes. The trend of the aging of the structure can be traced, which will be helpful for the reasonable planning of reconstruction. Based on the rapid development and miniaturization of measuring devices, new, smaller, easier to use, and more perfect devices are constructed. This also applies to the new group of laser scanners constructed for basic measurement and structure modeling for BIM. Conventional laser scanners can be accurate, but they are relatively large and heavy, difficult to transport and measuring with them is relatively slow (stop and go type). If the project goal is the classic construction, documentation of the object, data transfer to BIM or basic documentation of objects, PLS is the ideal device. Thanks to the development of accurate IMU (inertial measurement unit) and SLAM (simultaneous localization and mapping) technologies, these devices are on the rise. The forthcoming article will inform about the methods of accurate close-range photogrammetry and mobile laser scanning and will show their advantages with specific examples.

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