TOWARDS DEVELOPMENT OF MOBILE MAPPING SYSTEMS

The latest development and evolution of surveying and mobile mapping technologies opens new avenues for the acquisition, update, fast and online processing of data. Currently mobile mapping systems are supported by a series of advanced technologies, including GPS and Inertial Navigation Systems (INS), imaging sensors of high-resolution CCD, SAR, multispectral and hyperspectral sensors, portable computers and highly intelligent processing/automation algorithms. This paper outlines recent developments of micro-GPS technology and integrated mapping systems, including accuracy, integration with GIS and communication techniques. The definition and history of the Mobile Mapping System (MMS) is reviewed and briefly outlined. Advancements in low-cost, micro-GPS technologies are emphasised. Some new advancements of the current MMS will be reviewed to demonstrate recent progress and future trends of development. A few commercial MMSs are also assessed.

The mobile 3D mapping systems (MMS) and the integration with Geographical Information Systems (GIS) represent an innovative and efficient approach to modern topography. It is recommended and useful for infrastructure analysis and urban planning. This modern technology provides accurate, fast, and detailed data, facilitating well-informed decision-making and contributing to the development of sustainable infrastructure in the 21st century. The purpose of this research was to use a mobile mapping system for land surveying measurement of an urban area, independent of pre-established ground control points. On the other hand, the research is supposed to demonstrate the usefulness of kinematic trajectory, digital imaging, and laser scanning in acquiring, storing, and processing point cloud data. This paper shows an affordable method and a modern scanning instrument used for mobile mapping scanning, to create a georeferenced point cloud (PC). The obtained result has centimetric precision of georeferenced point cloud data, even if the average speed of the car was about 30km/h. The trajectory adjustment with static GNSS measurements increases the accuracy of ground control points (GCPs) up to ±5cm for horizontal positioning and vertical positioning. Although this study was carried out while the system was mounted on a car the result followed the national accuracy requirements for land surveying and cadastre fields. In other words, the mobile mapping system is a faster and cost-effective in time alternative to static laser scanning and it is important to continue to explore and adopt these technological solutions to face the future challenges in the field of urban development and infrastructure.

The early development of mobile mapping system (MMS) was restricted to applications that permitted the determination of the elements of exterior orientation from existing ground control. Mobile mapping refers to a means of collecting geospatial data using mapping sensors that are mounted on a mobile platform. Research works concerning mobile mapping dates back to the late 1980s. This process is mainly driven by the need for highway infrastructure mapping and transportation corridor inventories. In the early nineties, advances in satellite and inertial technology made it possible to think about mobile mapping in a different way. Instead of using ground control points as references for orienting the images in space, the trajectory and attitude of the imager platform could now be determined directly. Cameras, along with navigation and positioning sensors are integrated and mounted on a land vehicle for mapping purposes. Objects of interest can be directly measured and mapped from images that have been georeferenced using navigation and positioning sensors. Direct georeferencing (DG) is the determination of time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using the Global Navigation Satellite System (GNSS) and inertial navigation using an Inertial Measuring Unit (IMU). Although either technology used along could in principle determine both position and orientation, they are usually integrated in such a way that the IMU is the main orientation sensor, while the GNSS receiver is the main position sensor. However, GNSS signals are obstructed due to limited number of visible satellites in GNSS denied environments such as urban canyon, foliage, tunnel and indoor that cause the GNSS gap or interfered by reflected signals that cause abnormal measurement residuals thus deteriorates the positioning accuracy in GNSS denied environments. This study aims at developing a novel method that uses ground control points to maintain the positioning accuracy of the MMS in GNSS denied environments. At last, this study analyses the performance of proposed method using about 20 check-points through DG process.

Recently the useage of mobile mapping platform have been raised gradually in Taiwan. Currently mobile mapping technologies always apply INS/GNSS integrated system to get exterior orientation of image by Direct Georeferencing (DG). But the accuracy of DG is affected significantly by the accuracy of INS/GNSS integrated system because the error propagation from INS/GNSS integrated system to DG is linear. So the primary objective to increase the accuracy of mobile mapping system is to enhance the accuracy of INS/GNSS integrated system. This research investigates the impact different kinematic satellite positioning method on the positioning and orientation accuracy of an INS/GNSS integrated system. It uses raw measurements of INS/GNSS integrated system to perform three satellite positioning processes, including Differential GNSS (DGNSS), Precise Point Positioning (PPP) and post-processed Virtual Reference Station (VRS). The result shows the accuracy of using VRS in INS/GNSS integrated system satellite positioning is superior compared to other methods. Now the development of Network RTK (Network Real Time Kinematic, NRTK) in Taiwan is gradually becomimg mature. National Land Surveying and Mapping Center established e-GPS based on VRS and the provate company also set up a similar system known as Civil NET. Using post-processed VRS to do satellite positioning can save the cost of manpower which is needed in traditional DGNSS and still remain the accuracy which is needed in mobile mapping system.

Foreword: Advances in mobile mapping technology C.V. Tao and J. Li Part 1 Terrestrial and airborne mobile mapping systems Digital mobile mapping systems-state of the art and future trends K.P. Schwarz and N. El-Sheimy GEOVAN: The mobile mapping system from the Cartographic Institute of Catalonia J. Talaya, E. Bosch, R. Alamus, A. Serra and A. Baron ORTHOROAD: A low cost mobile mapping system for road mapping G. Artese A mobile mapping system for road data capture via a single camera H. Gontran, J. Skaloud and P.-Y. Gillieron Airborne remote sensing supporting traffic flow estimation D.A. Grejner-Brzezinska, C.K. Toth and E. Paska Part 2 Multi-sensor integration Performance analysis of integrated IMU/DGPS systems for mobile mapping systems A.W.L. Ip, N. El-Sheimy and M.M.R. Mostafa Appearance based positioning in urban environments using Kalman filtering L. Paletta, R. Wack, G. Paar, G. Ogris and C. Le Gal Multi-sensor systems for pedestrian navigation and guidance services G. Retscher Integrated technologies for augmented reality applications A. Kealy and S. Scott-Young Part 3 Image processing and object extraction Constrained bundle adjustment of panoramic stereo images for Mars landing site mapping K. Di, F. Xu and R. Li Vehicle classification from LiDAR data to support traffic flow estimates C.K. Toth and D.A. Grejner-Brzezinska Extraction of streets in dense urban areas from segmented LiDAR data X. Hu, C.V. Tao and Y. Hu Semi-automated extraction of urban highway intersections from IKONOS imagery H. Dong, J. Li and M.A. Chapman Part 4 Mobile GIS and distributed GIS Mobile GIS-based navigation guide B. Huang, C. Xie and S.Y. Loh Framework for multi-risk emergency response S. Zlatanova, D. Holweg and M. Stratakis

Abstract. Accurately georeferenced data acquired using mobile mapping systems is of great importance for many geospatial applications. The accuracy of direct georeferencing – the standard procedure in the field of outdoor mobile mapping – strongly relies on GNSS reception and therefore varies greatly depending on the environment. By incorporating control point observations, integrated georeferencing enables homogenous accuracy and reliability over the whole mapping perimeter. Unfortunately, exact measurement and documentation of control points is needed, which often must be done manually. To automate this process, approaches from the field of autonomous vehicles use pole-like objects to support localization in complex urban environments, with the disadvantage of requiring a prior mapping campaign. However, various classes of pole-like objects have been recorded with accurate location and entered in public cadastres, so they could serve as 2D control points. In this paper, we present an approach for improving the trajectory accuracy in challenging urban environments by means of integrated georeferencing. It uses range image observations to pole-like objects from publicly available cadastres. Our approach achieves sub-metre accuracy, with a maximal cross-track difference of 98 cm, using real-world data acquired with our low-cost mobile mapping system. We further demonstrate that it significantly improves discontinuities and inaccuracy peaks in direct georeferencing and that the limiting factors are errors in the depth estimation of available range imaging sensors.

This paper discusses a comprehensive methodology for transforming a static LiDAR (Light Detection and Ranging) system into a mobile mapping system. The initial step involves integrating various sensors, such as GNSS (Global Navigation Satellite System), IMU (Inertial Measurement Unit), and odometry sensors, into the system’s architecture to accurately estimate the position and orientation of the LiDAR sensor at any given time. Specialized algorithms compensate for the vehicle’s motion, and procedural requirements must be followed to ensure safe operation. Hardware integration is critical, requiring proper calibration and validation. Data processing workflows, including algorithms and software tools, play a crucial role in mobile LiDAR mapping systems. The quality and accuracy of the data depend on various factors, and practical considerations such as cost and time are also important. The proposed methodology provides a clear and effective way to transform a terrestrial LiDAR sensor into a mobile mapping system, increasing its flexibility and usability for various applications. However, the detailed analysis, system validation, and data processing details fall outside this paper’s scope and will be discussed in future publications.

Technological advances in positioning and imaging sensors, combined with the explosion in wireless mobile communication systems that occurred during the last decade of the twentieth century, practically redefined and substantially extended the concept of mobile mapping. The advent of the first mobile mapping systems (MMS) in the early 1990s initiated the process of establishing modern, virtually ground-control-free photogrammetry and digital mapping. By the end of the last decade, mobile mapping technology had made remarkable progress, evolving from rather simple land-based systems to more sophisticated, real-time multitasking and multisensor systems, operational in land and airborne environments. New specialized systems, based on modern imaging sensors, such as CCD (charge-coupled device) cameras, lidar (Light Detection and Ranging) and hyperspectral/multispectral scanners, are being developed, aimed at automatic data acquisition for geoinformatics, thematic mapping, land classification, terrain modeling, emergency response, homeland security, etc. This paper provides an overview of the mobile mapping concept, with a special emphasis on the MMS paradigm shift from the post-mission to near-real-time systems that occurred in the past few years. A short review of the direct georeferencing concept is given, and the major techniques (sensors) used for platform georegistration, as well as the primary radiolocation techniques based on wireless networks, are presented. An overview of the major imaging sensors and the importance of multisensor system calibration are also provided. Future perspectives of mobile mapping and its extension towards telegeoinformatics are also discussed. Some examples of mobile geospatial technology used in automatic object recognition, real-time highway centerline mapping, thematic mapping, and city modeling with lidar and multispectral imagery are included.

Mobile mapping is a new way of efficiently collecting three-dimensional data from the road environment. Mobile mapping systems are cost efficient and robust technique to acquire information about even highly dynamic environments like highways and urban streets, where the data collection has previously been laborious and even dangerous for the staff performing the surveying. The dynamic mobile mapping systems could access the site with less risk to the personnel and with less need for road closures. The need for high resolution and details captured in to the data for street and road inventories, or city modelling, are the main reasons for the rapid adoption of the mobile mapping techniques in these fields. Lidar based mobile mapping system produces three-dimensional points from the surrounding objects. Typically, two-dimensional profiling scanner is mounted on the system and the third dimension is achieved by the movement of the vehicle. The characteristics of the obtained point cloud depend largely on the sensor arrangement and the sensor properties. The ROAMER, a single-scanner system for road environment mapping presented in this paper, is able to use various tilted scanning planes for the point acquisition with 120 kHz point measurement frequency and up to 48 Hz profile measurement rate. The relative point precision for the system is estimated to be a few millimetres, but is eventually defined absolutely by the accuracy of the navigation solution that could be provided in real-time, or more reliably through post-processing. We believe that in the future, lidar based mobile mapping will be used considerably for urban and road environment modelling, as well as in many other applications in the fields of construction, forestry, railways, and even in environmental modelling and monitoring e.g. hydrology and glaciology. In urban context, the main applications of these models could include urban and environmental planning, road safety assessment, road construction planning and navigation.

Abstract. The early development of mobile mapping system (MMS) was restricted to applications that permitted the determination of the elements of exterior orientation from existing ground control. Mobile mapping refers to a means of collecting geospatial data using mapping sensors that are mounted on a mobile platform. Research works concerning mobile mapping dates back to the late 1980s. This process is mainly driven by the need for highway infrastructure mapping and transportation corridor inventories. In the early nineties, advances in satellite and inertial technology made it possible to think about mobile mapping in a different way. Instead of using ground control points as references for orienting the images in space, the trajectory and attitude of the imager platform could now be determined directly. Cameras, along with navigation and positioning sensors are integrated and mounted on a land vehicle for mapping purposes. Objects of interest can be directly measured and mapped from images that have been georeferenced using navigation and positioning sensors. Direct georeferencing (DG) is the determination of time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using the Global Navigation Satellite System (GNSS) and inertial navigation using an Inertial Measuring Unit (IMU). Although either technology used along could in principle determine both position and orientation, they are usually integrated in such a way that the IMU is the main orientation sensor, while the GNSS receiver is the main position sensor. However, GNSS signals are obstructed due to limited number of visible satellites in GNSS denied environments such as urban canyon, foliage, tunnel and indoor that cause the GNSS gap or interfered by reflected signals that cause abnormal measurement residuals thus deteriorates the positioning accuracy in GNSS denied environments. This study aims at developing a novel method that uses ground control points to maintain the positioning accuracy of the MMS in GNSS denied environments. At last, this study analyses the performance of proposed method using about 20 check-points through DG process.

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.

Abstract. 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.

During the past dozen years, several mobile mapping systems based on the use of imaging and positioning sensors mounted on terrestrial (and aerial) vehicles have been developed. Recently, systems characterized by an increased portability have been proposed in order to enable mobile mapping in environments that are difficult to access for vehicles, in particular for indoor environments. In this work the performance of a low-cost mobile mapping system is compared with that of: (i) a state-of-the-art terrestrial laser scanning (TLS), considered as the control; (ii) a mobile mapping backpack system (Leica Pegasus), which can be considered as the state-of-the-art of commercial mobile mapping backpack systems. The aim of this paper is two-fold: first, assessing the reconstruction accuracy of the proposed low-cost mobile mapping system, based on photogrammetry and ultra-wide band (UWB) for relative positioning (and a GNSS receiver if georeferencing is needed), with respect to a TLS survey in an indoor environment, where the global navigation satellite system (GNSS) signal is not available; second, comparing such performance with that obtained with the Leica backpack. Both mobile mapping systems are designed to work without any control point, to enable an easy and quick survey (e.g., few minutes) and to be easily portable (relatively low weight and small size). The case study deals with the 3D reconstruction of a medieval bastion in Padua, Italy. Reconstruction using the Leica Pegasus backpack allowed obtaining a smaller absolute error with respect to the UWB-based photogrammetric system. In georeferenced coordinates, the root mean square (RMS) error was respectively 16.1 cm and 50.3 cm; relative error in local coordinates was more similar, respectively 8.2 cm and 6.1 cm. Given the much lower cost (approximately $6k), the proposed photogrammetric-based system can be an interesting alternative when decimetric reconstruction accuracy in georeferenced coordinates is sufficient.

ABSTRACTMobile mapping systems (MMS) are widely used technology nowadays for spatial data collection of large scale projects like for city and highway mapping. The systems are mainly equipped with laser scanning sensors and/or imaging sensors mounted on a moving vehicle during the scene capture. Imaging sensors are normally cameras which either capture perspective or panoramic images covering the whole horizon of the vehicle. The orientation of the captured panoramic images is accurate to centimeters’ level because of the precise positioning and navigation systems equipped with these mapping systems. However, the positioning accuracy of mobile mapping systems can be degraded in city centers or urban canyons because of the satellite signal disturbances.In this article, we discuss the following objectives: (1) the possibility to use the mobile mapping images for cultural heritage documentation and as built surveying and how accurate the mapping can be; (2) the concept of using the mobile mapping images as a tool of georeferencing the crowdsource images; and (3) the efficiency of using the multi-temporal mobile mapping images for occluded free cultural heritage facade orthophotos. The mobile mapping systems of CycloMedia with two panoramic products of Cyclorama images (12 MP) and HD Cycloramas (100 MP) are used for the experimental tests in this research article.

Mobile mapping is an efficient technology to acquire spatial data of the environment. As a supplement of vehicle-borne and air-borne methods, Backpack mobile mapping system (MMS) has a wide application prospect in indoor and underground space. High-precision positioning and attitude determination are the key to MMS. Usually, GNSS/INS integrated navigation system provides reliable pose information. However, in the GNSS-denied environments, there is no effective long-term positioning method. With the development of simultaneous localization and mapping (SLAM) algorithm, it provides a new solution for indoor mobile mapping. This paper develops a portable backpack mobile mapping system, which integrates multi-sensor such as LiDAR, IMU, GNSS and panoramic camera. The 3D laser SLAM algorithm is applied to the mobile mapping to realize the acquisition of geographic information data in various complex environments. The experimental results in typical indoor and outdoor scenes show that the system can achieve high-precision and efficient acquisition of 3D information, and the relative precision of point cloud is 2~4cm, which meets the requirements of scene mapping and reconstruction.