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Scientific Article details

Title Cloud-Based Geospatial 3D Image Spaces-A Powerful Urban Model for the Smart City
ID_Doc 37411
Authors Nebiker, S; Cavegn, S; Loesch, B
Title Cloud-Based Geospatial 3D Image Spaces-A Powerful Urban Model for the Smart City
Year 2015
Published Isprs International Journal Of Geo-Information, 4.0, 4
DOI 10.3390/ijgi4042267
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.
Author Keywords smart city; urban modeling; mobile mapping; stereovision; image matching; georeferencing; cloud computing; 3D monoplotting; augmentation
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000367723300025
WoS Category Computer Science, Information Systems; Geography, Physical; Remote Sensing
Research Area Computer Science; Physical Geography; Remote Sensing
PDF https://www.mdpi.com/2220-9964/4/4/2267/pdf?version=1445870734
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