scholarly journals An Improved Mobile Mapping System to Detect Road-Killed Amphibians and Small Birds

2019 ◽  
Vol 8 (12) ◽  
pp. 565 ◽  
Author(s):  
Diana Sousa Guedes ◽  
Hélder Ribeiro ◽  
Neftalí Sillero
Keyword(s):  
Scanning System ◽  
Road Mortality ◽  
High Definition ◽  
Mobile Mapping ◽  
The Road ◽  
Moving Platforms ◽  
Mapping System ◽  
Mobile Mapping System ◽  
On The Road ◽  
Mobile Mapping Systems

Roads represent a major source of mortality for many species. To mitigate road mortality, it is essential to know where collisions with vehicles are happening and which species and populations are most affected. For this, moving platforms such as mobile mapping systems (MMS) can be used to automatically detect road-killed animals on the road surface. We recently developed an MMS to detect road-killed amphibians, composed of a scanning system on a trailer. We present here a smaller and improved version of this system (MMS2) for detecting road-killed amphibians and small birds. It is composed of a stereo multi-spectral and high definition camera (ZED), a high-power processing laptop, a global positioning system (GPS) device, a support device, and a lighter charger. The MMS2 can be easily attached to any vehicle and the surveys can be performed by any person with or without sampling skills. To evaluate the system’s effectiveness, we performed several controlled and real surveys in the Évora district (Portugal). In real surveys, the system detected approximately 78% of the amphibians and birds present on surveyed roads (overlooking 22%) and generated approximately 17% of false positives. Our system can improve the implementation of conservation measures, saving time for researchers and transportation planning professionals.

scholarly journals Generation of effective orthophotos for road surfaces using MMS

2014 ◽  
Vol XL-5 ◽  
pp. 621-628
Author(s):  
D. Yagishita ◽  
H. Chikatsu
Keyword(s):  
Laser Scanner ◽  
Road Surface ◽  
Mobile Mapping ◽  
Video Cameras ◽  
The Road ◽  
Lack Of Information ◽  
Mapping System ◽  
Road Surfaces ◽  
Mobile Mapping System ◽  
On The Road

In recent years, high precision and high resolution road surface orthophotos have been generated using video cameras mounted on surveying vehicles. However, there is a serious issue in generating an orthophoto from this image. The shadows of the surrounding structures and vehicles on the road surface cause a lack of information and decrease in visibility. Therefore, the shadows should be removed from the images for exact road management. On the other hand, the Mobile Mapping System with a laser scanner mounted on vehicles has been receiving more attention because the laser scanner intensity is almost unaffected by shadows. This paper presents shadow extraction and shadow correction for generating road surface orthophotos using the laser scanner intensity.

scholarly journals SYSTEM DESIGN, CALIBRATION AND PERFORMANCE ANALYSIS OF A NOVEL 360° STEREO PANORAMIC MOBILE MAPPING SYSTEM

2017 ◽  
Vol IV-1/W1 ◽  
pp. 207-213
Author(s):  
S. Blaser ◽  
S. Nebiker ◽  
S. Cavegn
Keyword(s):  
Calibration Procedure ◽  
Mobile Mapping ◽  
Camera Systems ◽  
3D City Model ◽  
Mapping System ◽  
Mobile Mapping System ◽  
City Model ◽  
And Performance ◽  
Mobile Mapping Systems ◽  
Street Environment

Image-based mobile mapping systems enable the efficient acquisition of georeferenced image sequences, which can later be exploited in cloud-based 3D geoinformation services. In order to provide a 360° coverage with accurate 3D measuring capabilities, we present a novel 360° stereo panoramic camera configuration. By using two 360° panorama cameras tilted forward and backward in combination with conventional forward and backward looking stereo camera systems, we achieve a full 360° multi-stereo coverage. We furthermore developed a fully operational new mobile mapping system based on our proposed approach, which fulfils our high accuracy requirements. We successfully implemented a rigorous sensor and system calibration procedure, which allows calibrating all stereo systems with a superior accuracy compared to that of previous work. Our study delivered absolute 3D point accuracies in the range of 4 to 6 cm and relative accuracies of 3D distances in the range of 1 to 3 cm. These results were achieved in a challenging urban area. Furthermore, we automatically reconstructed a 3D city model of our study area by employing all captured and georeferenced mobile mapping imagery. The result is a very high detailed and almost complete 3D city model of the street environment.

Pothole Mapping and Patching Quantity Estimates using LiDAR-Based Mobile Mapping Systems

2020 ◽  
Vol 2674 (9) ◽  
pp. 124-134
Author(s):  
Radhika Ravi ◽  
Ayman Habib ◽  
Darcy Bullock
Keyword(s):  
Point Clouds ◽  
Relative Accuracy ◽  
Mobile Mapping ◽  
Cloud Data ◽  
Pavement Distress ◽  
The Road ◽  
Mapping System ◽  
Mobile Mapping System ◽  
The Cost ◽  
Mapping Systems

Pavement distress or pothole mapping is important to public agencies responsible for maintaining roadways. The efficient capture of 3D point cloud data using mapping systems equipped with LiDAR eliminates the time-consuming and labor-intensive manual classification and quantity estimates. This paper proposes a methodology to map potholes along the road surface using ultra-high accuracy LiDAR units onboard a wheel-based mobile mapping system. LiDAR point clouds are processed to detect and report the location and severity of potholes by identifying the below-road 3D points pertaining to potholes, along with their depths. The surface area and volume of each detected pothole is also estimated along with the volume of its minimum bounding box to serve as an aide to choose the ideal method of repair as well as to estimate the cost of repair. The proposed approach was tested on a 10 mi-long segment on a U.S. Highway and it is observed to accurately detect potholes with varying severity and different causes. A sample of potholes detected in a 1 mi segment has been reported in the experimental results of this paper. The point clouds generated using the system are observed to have a single-track relative accuracy of less than ±1 cm and a multi-track relative accuracy of ±1–2 cm, which has been verified through comparing point clouds captured by different sensors from different tracks.

On the applicability of a scan-based mobile mapping system for monitoring the planarity and subsidence of road surfaces – Pilot study on the A44n motorway in Germany

2020 ◽  
Vol 14 (1) ◽  
pp. 39-54 ◽  
Author(s):  
Erik Heinz ◽  
Christian Eling ◽  
Lasse Klingbeil ◽  
Heiner Kuhlmann
Keyword(s):  
Standard Deviation ◽  
Point Clouds ◽  
Road Surface ◽  
Control Points ◽  
Mobile Mapping ◽  
The Road ◽  
Mapping System ◽  
Road Surfaces ◽  
Mobile Mapping System ◽  
Physical Height

AbstractKinematic laser scanning is widely used for the fast and accurate acquisition of road corridors. In this context, road monitoring is a crucial application, since deficiencies of the road surface due to non-planarity and subsidence put traffic at risk. In recent years, a Mobile Mapping System (MMS) has been developed at the University of Bonn, consisting of a GNSS/IMU unit and a 2D laser scanner. The goal of this paper is to evaluate the accuracy and precision of this MMS, where the height component is of main interest. Following this, the applicability of the MMS for monitoring the planarity and subsidence of road surfaces is analyzed. The test area for this study is a 6 km long section of the A44n motorway in Germany. For the evaluation of the MMS, leveled control points along the motorway as well as point cloud comparisons of repeated passes were used. In order to transform the ellipsoidal heights of the MMS into the physical height system of the control points, undulations were utilized. In this respect, a local tilt correction for the geoid model was determined based on GNSS baselines and leveling, leading to a physical height accuracy of the MMS of < 10 mm (RMS). The related height precision has a standard deviation of about 5 mm. Hence, a potential subsidence of the road surface in the order of a few cm is detectable. In addition, the point clouds were used to analyze the planarity of the road surface. In the course of this, the cross fall of the road was estimated with a standard deviation of < 0.07 %. Yet, no deficiencies of the road surface in the form of significant rut depths or fictive water depths were detected, indicating the proper condition of the A44n motorway. According to our tests, the MMS is appropriate for road monitoring.

scholarly journals MOBILE MAPPING OF THE LA CORONA LAVATUBE ON LANZAROTE

2019 ◽  
Vol IV-2/W5 ◽  
pp. 381-387 ◽  
Author(s):  
H. A. Lauterbach ◽  
D. Borrmann ◽  
A. Nüchter ◽  
A. P. Rossi ◽  
V. Unnithan ◽  
...  
Keyword(s):  
Laser Scanner ◽  
Optimization Approach ◽  
Indoor Environments ◽  
Mobile Mapping ◽  
Trajectory Estimation ◽  
Mapping System ◽  
Laser Scanners ◽  
Mobile Mapping System ◽  
Mobile Mapping Systems ◽  
Mapping Systems

<p><strong>Abstract.</strong> Planetary surfaces consist of rough terrain and cave-like environments. Future planetary exploration demands for accurate mapping. However, recent backpack mobile mapping systems are mostly tested in structured, indoor environments. This paper evaluates the use of a backpack mobile mapping system in a cave-like environment. The experiments demonstrate the abilities of an continuous-time optimization approach by mapping part of a lavatube of the La Corona volcano system on Lanzarote. We compare two strategies for trajectory estimation relying either on 2D or 3D laser scanners and show that a 3D laser scanner substantially improved the final results.</p>

scholarly journals MONITORING CAPABILITIES OF A MOBILE MAPPING SYSTEM BASED ON NAVIGATION QUALITIES

2016 ◽  
Vol XLI-B1 ◽  
pp. 625-631 ◽  
Author(s):  
H. Jing ◽  
N. Slatcher ◽  
X. Meng ◽  
G. Hunter
Keyword(s):  
Change Detection ◽  
Point Clouds ◽  
Mobile Mapping ◽  
Mapping System ◽  
Short Period ◽  
Laser Scanners ◽  
Mobile Mapping System ◽  
Mobile Mapping Systems ◽  
Mapping Systems

Mobile mapping systems are becoming increasingly popular as they can build 3D models of the environment rapidly by using a laser scanner that is integrated with a navigation system. 3D mobile mapping has been widely used for applications such as 3D city modelling and mapping of the scanned environments. However, accurate mapping relies on not only the scanner’s performance but also on the quality of the navigation results (accuracy and robustness) . This paper discusses the potentials of using 3D mobile mapping systems for landscape change detection, that is traditionally carried out by terrestrial laser scanners that can be accurately geo-referenced at a static location to produce highly accurate dense point clouds. Yet compared to conventional surveying using terrestrial laser scanners, several advantages of mobile mapping systems can be identified. A large area can be monitored in a relatively short period, which enables high repeat frequency monitoring without having to set-up dedicated stations. However, current mobile mapping applications are limited by the quality of navigation results, especially in different environments. The change detection ability of mobile mapping systems is therefore significantly affected by the quality of the navigation results. This paper presents some data collected for the purpose of monitoring from a mobile platform. The datasets are analysed to address current potentials and difficulties. The change detection results are also presented based on the collected dataset. Results indicate the potentials of change detection using a mobile mapping system and suggestions to enhance quality and robustness.

scholarly journals Eyes on the Road

2017 ◽  
Vol 139 (12) ◽  
pp. 33-33
Author(s):  
Michael Abrams ◽  
Thomas Romer
Keyword(s):  
Major Advance ◽  
Cruise Control ◽  
Time Data ◽  
High Definition ◽  
The Road ◽  
Software Algorithms ◽  
Mapping System ◽  
Hebrew University ◽  
On The Road ◽  
And Training

This article presents an overview of the EyeQ silicon chip developed by Jerusalem-based company Mobileye. The company has been designing hardware and training software algorithms to help vehicles detect and avoid other vehicles. In a major advance, the company has been able to shrink its Advanced Driving Assist System to fit on a single silicon chip it calls EyeQ. When wired to a camera, the system offers superior cruise control, keeps its vehicle in lane, recognizes traffic signs, and can automatically brake for pedestrians and other dangerously close vehicles. The company, which was founded by Amnon Shashua, a professor of computer science at the Hebrew University of Jerusalem, has already sold 20 million of its chips. The advantage of having so many of them already traveling the world’s highways extends beyond the immediate safety they provide. Mobileye is mining the data those chips collect to create a high-definition mapping system that will work with real-time data to help vehicles navigate and eventually become fully autonomous.

scholarly journals Combined Lane Mapping Using a Mobile Mapping System

2019 ◽  
Vol 11 (3) ◽  
pp. 305 ◽  
Author(s):  
Rui Wan ◽  
Yuchun Huang ◽  
Rongchang Xie ◽  
Ping Ma
Keyword(s):  
Autonomous Systems ◽  
Point Clouds ◽  
Correction Method ◽  
High Definition ◽  
Mobile Mapping ◽  
Pavement Markings ◽  
Mapping System ◽  
Mobile Mapping System ◽  
High Resolution Images ◽  
Saliency Analysis

High-definition mapping of 3D lane lines has been widely needed for the highway documentation and intelligent navigation of autonomous systems. A mobile mapping system (MMS) captures both accurate 3D LiDAR point clouds and high-resolution images of lane markings at highway driving speeds, providing an abundant data source for combined lane mapping. This paper aims to map lanes with an MMS. The main contributions of this paper include the following: (1) an intensity correction method was introduced to eliminate the reflectivity inconsistency of road-surface LiDAR points; (2) a self-adaptive thresholding method was developed to extract lane markings from their complicated surroundings; and (3) a LiDAR-guided textural saliency analysis of MMS images was proposed to improve the robustness of lane mapping. The proposed method was tested with a dataset acquired in Wuhan, Hubei, China, which contained straight roads, curved roads, and a roundabout with various pavement markings and a complex roadside environment. The experimental results achieved a recall of 96.4%, a precision of 97.6%, and an F-score of 97.0%, demonstrating that the proposed method has strong mapping ability for various urban roads.

scholarly journals THE PERFORMANCE ANALYSIS OF AN INDOOR MOBILE MAPPING SYSTEM WITH RGB-D SENSOR

2015 ◽  
Vol XL-1/W4 ◽  
pp. 183-188
Author(s):  
G. J. Tsai ◽  
K. W. Chiang ◽  
C. H. Chu ◽  
Y. L. Chen ◽  
N. El-Sheimy ◽  
...  
Keyword(s):  
Low Cost ◽  
Measurement Unit ◽  
Floor Plan ◽  
Mobile Mapping ◽  
Validation And Verification ◽  
Localization And Mapping ◽  
Mapping System ◽  
Mapping Technology ◽  
Mobile Mapping System ◽  
Mobile Mapping Systems

Over the years, Mobile Mapping Systems (MMSs) have been widely applied to urban mapping, path management and monitoring and cyber city, etc. The key concept of mobile mapping is based on positioning technology and photogrammetry. In order to achieve the integration, multi-sensor integrated mapping technology has clearly established. In recent years, the robotic technology has been rapidly developed. The other mapping technology that is on the basis of low-cost sensor has generally used in robotic system, it is known as the Simultaneous Localization and Mapping (SLAM). The objective of this study is developed a prototype of indoor MMS for mobile mapping applications, especially to reduce the costs and enhance the efficiency of data collection and validation of direct georeferenced (DG) performance. The proposed indoor MMS is composed of a tactical grade Inertial Measurement Unit (IMU), the Kinect RGB-D sensor and light detection, ranging (LIDAR) and robot. In summary, this paper designs the payload for indoor MMS to generate the floor plan. In first session, it concentrates on comparing the different positioning algorithms in the indoor environment. Next, the indoor plans are generated by two sensors, Kinect RGB-D sensor LIDAR on robot. Moreover, the generated floor plan will compare with the known plan for both validation and verification.

scholarly journals OBJECT DETECTION FROM MMS IMAGERY USING DEEP LEARNING FOR GENERATION OF ROAD ORTHOPHOTOS

2018 ◽  
Vol XLII-2 ◽  
pp. 573-577
Author(s):  
Y. Li ◽  
M. Sakamoto ◽  
T. Shinohara ◽  
T. Satoh
Keyword(s):  
Point Cloud ◽  
Point Cloud Data ◽  
Mobile Mapping ◽  
Cloud Data ◽  
The Road ◽  
Detection Model ◽  
Proposed Model ◽  
Mapping System ◽  
Mobile Mapping System

In recent years, extensive research has been conducted to automatically generate high-accuracy and high-precision road orthophotos using images and laser point cloud data acquired from a mobile mapping system (MMS). However, it is necessary to mask out non-road objects such as vehicles, bicycles, pedestrians and their shadows in MMS images in order to eliminate erroneous textures from the road orthophoto. Hence, we proposed a novel vehicle and its shadow detection model based on Faster R-CNN for automatically and accurately detecting the regions of vehicles and their shadows from MMS images. The experimental results show that the maximum recall of the proposed model was high &amp;ndash; 0.963 (intersection-over-union &amp;gt;&amp;thinsp;0.7) &amp;ndash; and the model could identify the regions of vehicles and their shadows accurately and robustly from MMS images, even when they contain varied vehicles, different shadow directions, and partial occlusions. Furthermore, it was confirmed that the quality of road orthophoto generated using vehicle and its shadow masks was significantly improved as compared to those generated using no masks or using vehicle masks only.

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