scholarly journals Novel low-cost mobile mapping systems for forest inventories as terrestrial laser scanning alternatives

2021 ◽  
Vol 104 ◽  
pp. 102512
Author(s):  
Martin Mokroš ◽  
Tomáš Mikita ◽  
Arunima Singh ◽  
Julián Tomaštík ◽  
Juliána Chudá ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Low Cost ◽  
Terrestrial Laser Scanning ◽  
Mobile Mapping ◽  
Forest Inventories ◽  
Mobile Mapping Systems ◽  
Mapping Systems

scholarly journals APPLICATION OF MLS DATA TO THE ASSESSMENT OF SAFETY-RELATED FEATURES IN THE SURROUNDING AREA OF AUTOMATICALLY DETECTED PEDESTRIAN CROSSINGS

2018 ◽  
Vol XLII-2 ◽  
pp. 1067-1074 ◽  
Author(s):  
M. Soilán ◽  
B. Riveiro ◽  
A. Sánchez-Rodríguez ◽  
L. M. González-deSantos
Keyword(s):  
Laser Scanning ◽  
Geographical Information ◽  
Mobile Mapping ◽  
Cloud Data ◽  
Traffic Lights ◽  
The Road ◽  
Processing Module ◽  
Pedestrian Crossing ◽  
Mobile Mapping Systems ◽  
Mapping Systems

During the last few years, there has been a huge methodological development regarding the automatic processing of 3D point cloud data acquired by both terrestrial and aerial mobile mapping systems, motivated by the improvement of surveying technologies and hardware performance. This paper presents a methodology that, in a first place, extracts geometric and semantic information regarding the road markings within the surveyed area from Mobile Laser Scanning (MLS) data, and then employs it to isolate street areas where pedestrian crossings are found and, therefore, pedestrians are more likely to cross the road. Then, different safety-related features can be extracted in order to offer information about the adequacy of the pedestrian crossing regarding its safety, which can be displayed in a Geographical Information System (GIS) layer. These features are defined in four different processing modules: Accessibility analysis, traffic lights classification, traffic signs classification, and visibility analysis. The validation of the proposed methodology has been carried out in two different cities in the northwest of Spain, obtaining both quantitative and qualitative results for pedestrian crossing classification and for each processing module of the safety assessment on pedestrian crossing environments.

scholarly journals Smartphones Based Mobile Mapping Systems

2014 ◽  
Vol XL-5 ◽  
pp. 29-34 ◽  
Author(s):  
A. Al-Hamad ◽  
N. El-Sheimy
Keyword(s):  
Mobile Phones ◽  
Spatial Data ◽  
Inertial Sensors ◽  
Low Cost ◽  
Micro Electro Mechanical System ◽  
Mobile Mapping ◽  
Moving Platforms ◽  
Gis Applications ◽  
Mobile Mapping Systems ◽  
Mapping Systems

The past 20 years have witnessed an explosive growth in the demand for geo-spatial data. This demand has numerous sources and takes many forms; however, the net effect is an ever-increasing thirst for data that is more accurate, has higher density, is produced more rapidly, and is acquired less expensively. For mapping and Geographic Information Systems (GIS) projects, this has been achieved through the major development of Mobile Mapping Systems (MMS). MMS integrate various navigation and remote sensing technologies which allow mapping from moving platforms (e.g. cars, airplanes, boats, etc.) to obtain the 3D coordinates of the points of interest. Such systems obtain accuracies that are suitable for all but the most demanding mapping and engineering applications. However, this accuracy doesn't come cheaply. As a consequence of the platform and navigation and mapping technologies used, even an "inexpensive" system costs well over 200 000 USD. Today's mobile phones are getting ever more sophisticated. Phone makers are determined to reduce the gap between computers and mobile phones. Smartphones, in addition to becoming status symbols, are increasingly being equipped with extended Global Positioning System (GPS) capabilities, Micro Electro Mechanical System (MEMS) inertial sensors, extremely powerful computing power and very high resolution cameras. Using all of these components, smartphones have the potential to replace the traditional land MMS and portable GPS/GIS equipment. This paper introduces an innovative application of smartphones as a very low cost portable MMS for mapping and GIS applications.

scholarly journals A MAN-PORTABLE, IMU-FREE MOBILE MAPPING SYSTEM

2015 ◽  
Vol II-3/W5 ◽  
pp. 17-23 ◽  
Author(s):  
A. Nüchter ◽  
D. Borrmann ◽  
P. Koch ◽  
M. Kühn ◽  
S. May
Keyword(s):  
Laser Scanning ◽  
Low Cost ◽  
Laser Scanner ◽  
Mobile Mapping ◽  
Measurement Systems ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Mems Imu ◽  
Mapping Solution ◽  
Mapping Systems

Mobile mapping systems are commonly mounted on cars, ships and robots. The data is directly geo-referenced using GPS data and expensive IMU (inertial measurement systems). Driven by the need for flexible, indoor mapping systems we present an inexpensive mobile mapping solution that can be mounted on a backpack. It combines a horizontally mounted 2D profiler with a constantly spinning 3D laser scanner. The initial system featuring a low-cost MEMS IMU was revealed and demonstrated at <i>MoLaS: Technology Workshop Mobile Laser Scanning at Fraunhofer IPM</i> in Freiburg in November 2014. In this paper, we present an IMU-free solution.

scholarly journals EVALUATION OF MOBILE MAPPING SYSTEMS FOR INDOOR SURVEYS

2020 ◽  
Vol XLIV-4/W1-2020 ◽  
pp. 119-125
Author(s):  
H. Salgues ◽  
H. Macher ◽  
T. Landes
Keyword(s):  
Laser Scanning ◽  
Point Clouds ◽  
Mobile Mapping ◽  
Area Of Interest ◽  
3D Point Clouds ◽  
Reliable Assessment ◽  
Acquisition Mode ◽  
The One ◽  
Mobile Mapping Systems ◽  
Mapping Systems

Abstract. With their high recording rate of hundreds of thousands of points acquired per second, speed of execution and a remote acquisition mode, SLAM based mobile mapping systems (MMS) are a very powerful solution for capturing 3D point clouds in real time, simply by walking in the area of interest. Regarding indoor surveys, these MMS have been integrated in handheld or backpack solutions and become fast scanning sensors. Despite their advantages, the geometric accuracy of 3D point clouds guaranteed with these sensors is lower than the one reachable with static TLS. In this paper the effectiveness of two recent mobile mapping systems namely the GeoSLAM ZEB-REVO RT and the more recent GreenValley LiBackPack C50 is investigated for indoor surveys. In order to perform a reliable assessment study, several datasets produced with each sensor are compared to the high-cost georeferenced point cloud obtained with static laser scanning target-based technique.

scholarly journals Performance Assessment of Mobile Laser Scanning Systems Using Velodyne Hdl-32e

2021 ◽  
Vol 1 (1) ◽  
pp. 28-33
Author(s):  
Bashar Alsadik
Keyword(s):  
Laser Scanning ◽  
Impact Analysis ◽  
Orientation Angle ◽  
Point Clouds ◽  
Mobile Mapping ◽  
Ongoing Research ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Mobile Mapping Systems ◽  
Mapping Systems

Mapping systems using multi-beam LiDARs are widely used nowadays for different geospatial applications graduating from indoor projects to outdoor city-wide projects. These mobile mapping systems can be either ground-based or aerial-based systems and are mostly equipped with inertial navigation systems INS. The Velodyne HDL-32 LiDAR is a well-known 360° spinning multi-beam laser scanner that is widely used in outdoor and indoor mobile mapping systems. The performance of such LiDARs is an ongoing research topic which is quite important for the quality assurance and quality control topic. The performance of this LiDAR type is correlated to many factors either related to the device itself or the design of the mobile mapping system. Regarding design, most of the mapping systems are equipped with a single Velodyne HDL32 in a specific orientation angle which is different among the mapping systems manufacturers. The LiDAR orientation angle has a significant impact on the performance in terms of the density and coverage of the produced point clouds. Furthermore, during the lifetime of this multi-beam LiDAR, one or more beams may be defected and then either continue the production or returned to the manufacturer to be fixed which then cost time and money. In this paper, the design impact analysis of a mobile laser scanning (MLS) system equipped with a single Velodyne HDL-32E will be clarified and a clear relationship is given between the orientation angle of the LiDAR and the output density of points. The ideal angular orientation of a single Velodyne HDL-32E is found to be at 35° in a mobile mapping system. Furthermore, we investigated the degradation of points density when one of the 32 beams is defected and quantified the density loss percentage and to the best of our knowledge, this is not presented in literature before. It is found that a maximum of about 8% point density loss occurs on the ground and 4% on the facades when having a defected beam of the Velodyne HDL-32E.   

scholarly journals Performance Evaluation of Two Indoor Mapping Systems: Low-Cost UWB-Aided Photogrammetry and Backpack Laser Scanning

2018 ◽  
Vol 8 (3) ◽  
pp. 416 ◽  
Author(s):  
Andrea Masiero ◽  
Francesca Fissore ◽  
Alberto Guarnieri ◽  
Francesco Pirotti ◽  
Domenico Visintini ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Laser Scanning ◽  
Low Cost ◽  
Mapping Systems

scholarly journals Extraction of Guardrails from MMS Data Using Convolutional Neural Network

2021 ◽  
Vol 15 (3) ◽  
pp. 258-267
Author(s):  
Hiroki Matsumoto ◽  
◽  
Yuma Mori ◽  
Hiroshi Masuda
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Asset Management ◽  
Extraction Method ◽  
Point Clouds ◽  
Mobile Mapping ◽  
Method Point ◽  
Mobile Mapping Systems ◽  
Capture Point ◽  
Mapping Systems

Mobile mapping systems can capture point clouds and digital images of roadside objects. Such data are useful for maintenance, asset management, and 3D map creation. In this paper, we discuss methods for extracting guardrails that separate roadways and walkways. Since there are various shape patterns for guardrails in Japan, flexible methods are required for extracting them. We propose a new extraction method based on point processing and a convolutional neural network (CNN). In our method, point clouds and images are segmented into small fragments, and their features are extracted using CNNs for images and point clouds. Then, features from images and point clouds are combined and investigated using whether they are guardrails or not. Based on our experiments, our method could extract guardrails from point clouds with a high success rate.

scholarly journals CLASSIFICATION OF RAILWAY ASSETS IN MOBILE MAPPING POINT CLOUDS

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 219-225
Author(s):  
M. Corongiu ◽  
A. Masiero ◽  
G. Tucci
Keyword(s):  
Spatial Information ◽  
Point Clouds ◽  
Railway Track ◽  
Neural Net ◽  
Mobile Mapping ◽  
Geospatial Information ◽  
Railway System ◽  
Point Neighborhood ◽  
Mobile Mapping Systems ◽  
Mapping Systems

Abstract. Nowadays, mobile mapping systems are widely used to quickly collect reliable geospatial information of relatively large areas: thanks to such characteristics, the number of applications and fields exploiting their usage is continuously increasing. Among such possible applications, mobile mapping systems have been recently considered also by railway system managers to quickly produce and update a database of the geospatial features of such system, also called assets. Despite several vehicles, devices and acquisition methods can be considered for the data collection of the railway system, the predominant one is probably that based on the use of a mobile mapping system mounted on a train, which moves all along the railway tracks, enabling the 3D reproduction of the entire railway track area.Given the large amount of data collected by such mobile mapping, automatic procedures have to be used to speed up the process of extracting the spatial information of interest, i.e. assets positions and characteristics.This paper considers the problem of extracting such information for what concerns cantilever and portal masts, by exploiting a mixed approach. First, a set of candidate areas are extracted and pre-processed by considering certain of their geometric characteristics, mainly extracted by using eigenvalues of the covariance matrix of a point neighborhood. Then, a 3D modified Fisher vector-deep learning neural net is used to classify the candidates. Tests on such approach are conducted in two areas of the Italian railway system.

Sign in / Sign up

Export Citation Format

Share Document