Abstract
The proposed research activity is based on the study and development of advanced monitoring techniques for the inspection and mapping of road infrastructures. Data detection (initial and periodic) is one of the most important phases of the process to be followed for the knowledge of the current state of road infrastructure and this is fundamental for the design and intervention choices. This operation can be done both through traditional (such as GNSS receivers, total motorized station and 3D laser scanner) and innovative tools (such as remote sensing, mobile mapping systems vehicles or road drones and APAs). Recently, technological development has offered the possibility to use tools that allow continuous detection of the object to be investigated, and there is the possibility to have multiple sensors at the same time that allow to make high-performance surveys. The aim of the research will be the design and implementation of an innovative measurement and component sensor system to be equipped on technological systems for data acquisition. The research also consists on the implementation of dedicated algorithms for the management of the amount of georeferenced data obtained and their representation on GIS (Geographic Information System) platforms as “open and updatable” thematic cartography. In this context, the establishment and update of the Road Cadastre is also included, intended (in our application) as a computer tool for storing, querying, managing and visualizating of all the data that the owner/manager acquired on its road network. In it will be possible to represent the elements inherent geometric characteristics elements of the roads and their relevance, as well as the permanent installations and services related to the needs of the circulation; in this way we can obtain a continuos updated database that allow rapid selective searches for topics.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hinz, S., Baumgartner, A., Mayer, H., Wiedemann, C., Ebner, H.: Road extraction focussing on urban areas. In: Baltsavias, E.P, Gruen, A., Gool, L.V. (eds.) Automatic Extraction of Man-made Objects from Aerial and Space Images (III), pp. 255–265. A.A. Balkema Publishers (2001)
Soilán, M., Riveiro, B., Martínez-Sánchez, J., Arias, P.: Automatic road sign inventory using mobile mapping systems. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 XXIII ISPRS Congress, vol. XLI-B3, Prague, Czech Republic, 12–19 July 2016
Gruen, A., Li, H.: Road extractions from aerial and satellite images by dynamic programming. ISPRS J. Photogram. Remote Sens. 50(4), 111–120 (1995)
Grüen, A., Li, H.: Linear feature extraction with 3-D LSB-snakes. In: Automatic Extraction of Man-Made Objects from Aerial and Space Images (II), pp. 287–298. BirkhäuserVerlag, Basel (1997)
Hatger, C., Brenner, C.: Extraction of road geometry parameters from laser scanning and existing databases. In: Proceeding of ISPRS Workshop: 3D Reconstruction from Airborne Laserscanner and InSAR DATA, Dresden, Germany, 8–10 October 2003
Serna, A., Marcotegui, B.: Detection, segmentation and classification of 3D urban objects using mathematical morphology and supervised learning. ISPRS J. Photogrammetry Remote Sens. 93, 243–255 (2014)
Barrile V., Cotroneo F.: A software for the automatic update of the road cadastre in the GIS environment. Bull. Ital. Soc. Photogrammetry Topogr. (2006)
Barrile, V., Leonardi, G., Fotia, A., Bilotta, G., Ielo, G.: Real-time update of the road cadastre in GIS environment from an MMS rudimentary system. In: International Symposium on New Metropolitan Perspectives, pp. 240–247 (2018)
Yu, Y., Li, J., Guan, H., Wang, C., Yu, J.: Semiautomated extraction of streetlight poles from mobile LiDAR point-clouds. IEEE Trans. Geosci. Remote Sens. 53(3), 1374–1386 (2015)
Cireşan, D., Meier, U., Schmidhuber, J.: Multi-column deep neural networks for image classification. Neural Netw. 32, 333–338 (2012)
Huang, C., Abu Al-Rub, R., Masad, E., Little, D.: Three dimensional simulations of asphalt pavement permanent deformation using a nonlinear viscoelastic and viscoplastic model. J. Mater. Civil Eng. 23, 56–68 (2011)
Bacher, U., Mayer, H.: Automatic road extraction from IRS satellite images in agricultural and desert areas. In: XXth Congress ISPRS, Istanbul, Turkey, 12–23 July 2004
Goeman, W., Martinez-Fonte, L., Bellens, R., Gautaman, S.: Automated verification of road network data by VHR satellite images using road statistics. In: Proceedings of IPSRS Workshop: High Resolution Earth Imaging for Geospatial Information, Hannover, Germany (2005)
Barrile, V., Cotroneo, F., Praticò, F.: Automatic updating processes of road surface surveys and surface defects: proposal of an innovative high-performance method. In: SIIV National Conference Cosenza, Italy (2006)
Wallace, S., Hatcher, M., Priestnall, G., Morton, R.: Research into a framework for automatic linear feature identification and extraction. In: Automatic Extraction of Man-Made Objects from Aerial and Space Images (III), pp. 381–390. Balkema Publishers, Lisse (2001)
Wiedemann, C., Ebner, H.: Automatic completion and evaluation of road networks. Int. Arch. Photogram. Remote Sens. 33(B3/2), 979–986 (2000)
Zhang, C., Baltsavias, E., Gruen, A.: Updating of cartographic road databases by image analysis. In: Baltsavias, E.P, Gruen, A., Gool, L.V. (eds.) Automatic Extraction of Man-made Objects from Aerial and Space Images (III), pp. 243–253. A.A. Balkema Publishers (2001)
Hinz, S., Baumgartner, A.: Urban road net extraction integrating internal evaluation models. In: International Society for Photogrammetry and Remote Sensingpp, Graz, Austria, pp. 255–265 (2002)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Barrile, V., Fotia, A., Bernardo, E., Bilotta, G. (2020). Road Cadastre an Innovative System to Update Information, from Big Data Elaboration. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12252. Springer, Cham. https://doi.org/10.1007/978-3-030-58811-3_51
Download citation
DOI: https://doi.org/10.1007/978-3-030-58811-3_51
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-58810-6
Online ISBN: 978-3-030-58811-3
eBook Packages: Computer ScienceComputer Science (R0)