Abstract
Recent innovations in 3D processing and availability of geospatial data have contributed largely to more comprehensive solutions to data visualization. As various data formats are utilized to describe the data, a combination of layers from different sources allow us to represent 3D urban areas, contributing to ideas of emergency management and smart cities. This work focuses on 3D urban environment reconstruction using crowdsourced OpenStreetMap data. Once the data are extracted, the visualization pipeline draws features using coloring for added context. Moreover, by structuring the layers and entities through the addition of simulation parameters, the generated environment is made simulation ready for further use. Results show that urban areas can be properly visualized in 3D using OpenStreetMap data given data availability. The simulation-ready environment was tested using hypothetical flooding scenarios, which demonstrated that the added parameters can be utilized in environmental simulations. Furthermore, an efficient restructuring of data was implemented for viewing the city information once the data are parsed.
Highlights
Storing such information as shape files for two-dimensional models may be considered appropriate, such large data providing 3D information require an efficient method of storage and processing [3]
City Maker was utilized to proceed with environment reconstruction to different sections of selected cities and tested to see if feature extraction and 2D/3D environment reconstruction has the power to represent city information properly
2D and 3D environment reconstruction capabilities of the City Maker were tested and a flood simulation case study was built to evaluate the use of roughness coefficients and storm sewer information
Summary
Storing such information as shape files for two-dimensional models may be considered appropriate, such large data providing 3D information require an efficient method of storage and processing [3]. 3D information is provided through hierarchical and semantically consistent formats [3,8]. Through such an arrangement, different applications, such as the ones for flooding [9,10,11] or urban development planning [12,13] can utilize the data according to their requirements. Providing multiple layers and storing the data in a hierarchical structure, more details can be incorporated into city description, which is essential for realistic and complex scenarios
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