Mapping the Underworld – State-of-the-art review

Metje, Nicole; Atkins, P.R.; Brennan, M.J.; Chapman, David; Lim, Han-Cheol; Machell, John; Muggleton, J.M.; Pennock, S.R.; Ratcliffe, J D; Redfern, M.A.; Rogers, C. D. F.; Saul, Adrian J.; Shan, Q.; Swingler, S.G.; Thomas, Andrew

doi:10.1016/j.tust.2007.04.002

Cited by 142 publications

(82 citation statements)

References 46 publications

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“…Over the past century it was common practice for public service providers to install, operate and repair their networks separately [6], so it is now very difficult to find accurate records of utility network maps in cities in both industrialized and developing countries. This crucial problem will worsen as cities expand and their networks increase in size and complexity [2] [3]. Urban works will thus be more prone to delays with concomitant additional costs [9] [10].…”

Section: Introductionmentioning

confidence: 99%

Detection of manhole covers in high-resolution aerial images of urban areas by combining two methods

Pasquet¹,

Desert

Bartoli

et al. 2015

2015 Joint Urban Remote Sensing Event (JURSE)

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Abstract-The detection of small objects from aerial images is a difficult signal processing task. To localise small objects in an image, low-complexity geometry-based approaches can be used, but their efficiency is often low. Another option is to use appearance-based approaches that give better results but require a costly learning step. In this paper, we treat the specific case of manhole covers. Currently many manholes are not listed or are badly positioned on maps. We implement two conventional previously published methods to detect manhole covers in images. The first one searches for circular patterns in the image while the second uses machine learning to build a model of manhole covers. The results show non optimal performances for each method. The two approaches are combined to overcome this limit, thus increasing the overall performance by about forty percent.

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Section: Introductionmentioning

confidence: 99%

Detection of manhole covers in high-resolution aerial images of urban areas by combining two methods

Pasquet¹,

Desert

Bartoli

et al. 2015

2015 Joint Urban Remote Sensing Event (JURSE)

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“…With the population growth and urban development, it is challenging not only to maintain an up-todate spatial database of existing underground utility networks (UUN) but also to acquire spatial data of buried infrastructures in non-invasive ways (Jeong et al, 2004;Navigant Consulting, 2005;Pouliot and Girard 2016). For any development project requiring excavation and trenching, it has become more and more essential to acknowledge the necessity of having an available and reliable current database of UUN in order to avoid interruption of services and downtime costs due to damage (Costello et al, 2007;Lew and Anspach, 2000;Metje et al, 2007). For example, Info-excavation reported 4.5 damages per day in 2015 for an approximate cost of $109 million CAN (Info-excavation, 2015).…”

Section: The Lack Of Underground Utility Datamentioning

confidence: 99%

“…Furthermore, offering a more comprehensive approach for covering preprocessing, acquisition, and visualization of relevant existing data for on-site consultation contributes to the effectiveness of identifying underground elements in the field. Many manuals and standards provide guideline for collection and mapping of underground infrastructure (ASCE, 2002;CCGA, 2014;Chen and Cohn, 2010;CSA, 2016;Metje et al, 2007). However, these standards do not seem to be known (or sometimes disregarded) by many GPR practitioners.…”

Section: Research Project Objectivesmentioning

confidence: 99%

A Webgis to Support GPR 3d Data Acquisition: A First Step for the Integration Of Underground Utility Networks in 3d City Models

Tabarro¹,

Pouliot²,

Fortier³

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:For the planning and sustainable development of large cities, it is critical to accurately locate and map, in 3D, existing underground utility networks (UUN) such as pipelines, cables, ducts, and channels. An emerging non-invasive instrument for collecting underground data such as UUN is the ground-penetrating radar (GPR). Although its capabilities, handling GPR and extracting relevant information from its data are not trivial tasks. For instance, both GPR and its complimentary software stack provide very few capabilities to co-visualize GPR collected data and other sources of spatial data such as orthophotography, DEM or road maps. Furthermore, the GPR interface lacks functionalities for adding annotation, editing geometric objects or querying attributes. A new approach to support GPR survey is proposed in this paper. This approach is based on the integration of multiple sources of geospatial datasets and the use of a Web-GIS system and relevant functionalities adapted to interoperable GPR data acquisition. The Web-GIS is developed as an improved module in an existing platform called GVX. The GVX-GPR module provides an interactive visualization of multiple layers of structured spatial data, including GPR profiles. This module offers new features when compared to traditional GPR surveys such as geo-annotated points of interest for identifying spatial clues in the GPR profiles, integration of city contextual data, high definition drone and satellite pictures, as-built, and more. The paper explains the engineering approach used to design and develop the Web GIS and tests for this survey approach, mapping and recording UUN as part of 3D city model.

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“…Non-invasive surveying can be performed with traditional topographic methods or by GPS positioning, by measuring the positions of the surface elements of the networks, like manholes, catch basins, transformers, hydrants, exchange boxes, etc., and subsequently inferring the presence and the approximate planar location of the buried lines. Another possibility is the GPR (Ground Penetrating Radar) technique (Metje et al, 2007), which allows reconstructing the main 3D geometry of underground elements. But, despite the major advantage of exploring the underground with trenchless means, there are limitations to the GPR technology linked to soil type and saturation and to the utility depth; besides, performing the survey of a large area is an expensive solution.…”

Section: Introductionmentioning

confidence: 99%

A Shared Database of Underground Utility Lines for 3d Mapping and Gis Applications

Cazzaniga

Carrión

Migliaccio

et al. 2013

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:For the purpose of facility management it is very important to have detailed and up-to-date databases of underground utility lines, but such data are not always available with adequate accuracy. Hence, the need of collecting and organizing suitable information on underground services is a fundamental issue when dealing with urban data. Besides, by analyzing the process of designing and laying new underground infrastructures it is possible to implement an efficient and cost-effective approach to integrate and update existing maps by exploiting the surveying required for the installation of new facilities. It is also important to underline that collecting all the data in a unique integrated database (and GIS) gives the possibility to share (at least at a local level) the cartographic and thematic information for an optimal management of underground networks. In this paper, a database (DB) model for archiving the underground lines data is presented. The structure of the DB has been designed by following the standard methodology for the modelling of a relational DB, going through successive phases and originating the external, conceptual and logical model. Finally, preliminary tests have been carried on for parts of the DB to verify quality parameters.

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Mapping the Underworld – State-of-the-art review

Cited by 142 publications

References 46 publications

Detection of manhole covers in high-resolution aerial images of urban areas by combining two methods

Detection of manhole covers in high-resolution aerial images of urban areas by combining two methods

A Webgis to Support GPR 3d Data Acquisition: A First Step for the Integration Of Underground Utility Networks in 3d City Models

A Shared Database of Underground Utility Lines for 3d Mapping and Gis Applications

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