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ISPRS Int. J. Geo-Inf. 2015, 4(4), 2267-2291; doi:10.3390/ijgi4042267

Cloud-Based Geospatial 3D Image Spaces—A Powerful Urban Model for the Smart City

Institute of Geomatics Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Gründenstrasse 40, 4132 Muttenz, Switzerland
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Academic Editors: Jochen Schiewe and Wolfgang Kainz
Received: 28 July 2015 / Revised: 5 October 2015 / Accepted: 14 October 2015 / Published: 26 October 2015
(This article belongs to the Special Issue Geo-Information Fostering Innovative Solutions for Smart Cities)
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Abstract

In this paper, we introduce the concept and an implementation of geospatial 3D image spaces as new type of native urban models. 3D image spaces are based on collections of georeferenced RGB-D imagery. This imagery is typically acquired using multi-view stereo mobile mapping systems capturing dense sequences of street level imagery. Ideally, image depth information is derived using dense image matching. This delivers a very dense depth representation and ensures the spatial and temporal coherence of radiometric and depth data. This results in a high-definition WYSIWYG (“what you see is what you get”) urban model, which is intuitive to interpret and easy to interact with, and which provides powerful augmentation and 3D measuring capabilities. Furthermore, we present a scalable cloud-based framework for generating 3D image spaces of entire cities or states and a client architecture for their web-based exploitation. The model and the framework strongly support the smart city notion of efficiently connecting the urban environment and its processes with experts and citizens alike. In the paper we particularly investigate quality aspects of the urban model, namely the obtainable georeferencing accuracy and the quality of the depth map extraction. We show that our image-based georeferencing approach is capable of improving the original direct georeferencing accuracy by an order of magnitude and that the presented new multi-image matching approach is capable of providing high accuracies along with a significantly improved completeness of the depth maps. View Full-Text
Keywords: smart city; urban modeling; mobile mapping; stereovision; image matching; georeferencing; cloud computing; 3D monoplotting; augmentation smart city; urban modeling; mobile mapping; stereovision; image matching; georeferencing; cloud computing; 3D monoplotting; augmentation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Nebiker, S.; Cavegn, S.; Loesch, B. Cloud-Based Geospatial 3D Image Spaces—A Powerful Urban Model for the Smart City. ISPRS Int. J. Geo-Inf. 2015, 4, 2267-2291.

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