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CityGML Based 3D Modeling of Urban Area Using UAV Dataset for Estimation of Solar Potential

  • HarikeshEmail author
  • Sachchidanand Singh
  • Vaibhav Shrivastava
  • Vishal Sharma
Conference paper
  • 41 Downloads
Part of the Lecture Notes in Civil Engineering book series (LNCE, volume 51)

Abstract

3D GIS modelling is the latest trend in Remote sensing for urban planning, utility mapping and many more applications. Mapping of an urban area using UAV (unmanned aerial vehicle) remote sensing, gives high accuracy which was not possible through traditional sensors. Urban area, which is continuously expanding, have an urgent need to find alternative energy sources to facilitate their increasing power demand. In this regard, solar energy can prove to be a vital source. In this work, high-resolution DTM (Digital Terrain Model), prepared from RGB point clouds for the Roorkee urban area using UAV survey, is used for building height extraction and 3D visualization, shadow analysis of the buildings and solar potential estimation. The CityGML based 3D city model is generated using UAV cloud dataset. CityGML, which is based on Geographic Markup language, is an open data model for the storage and it facilitates interoperability of virtual 3D city model. 3D GIS model is prepared using Computer Generated Architectural Rule Technique and various other tools such as ESRI City Engine, ArcGIS and FME software. The building height obtained from the 3D model, was validated from ground survey and the solar potential was validated from National Renewable Energy Laboratory, solar maps obtained from https://maps.nrel.gov/nsrdb-viewer/ website. The result depicted that the present status of Roorkee urban area has a strong potential to reduce the electricity load of the city via harnessing the solar energy, thus leading to a sustainable future.

Keywords

3D modelling DEM UAV Geographic markup language CityGML 

Notes

Acknowledgements

We would like to acknowledge Prof. Kamal Jain, Department of Civil engineering, IIT Roorkee to provide us the UAV dataset for this study.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Harikesh
    • 1
    Email author
  • Sachchidanand Singh
    • 1
  • Vaibhav Shrivastava
    • 1
  • Vishal Sharma
    • 1
  1. 1.Indian Institute of Remote SensingDehradunIndia

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