Volunteered geographic information (VGI) has received increased attention as a new paradigm for geographic information production, while light detection and ranging (LiDAR) data is widely applied to many fields. This study quantitatively compares LiDAR data and user-generated 3D building models created using Google Building Maker, and investigate the potential applications of the quantitative measures in support of rapid disaster damage assessment. User-generated 3D building models from Google Building Maker are compared with LiDAR-derived building models using 3D shape signatures. Eighteen 3D building models are created in Fremont, California using the Google Building Maker, and six shape functions (distance, angle, area, volume, slope, and aspect) are applied to the 18 LiDAR-derived building models and user-generated ones. A special case regarding the comparison between LiDAR data and building models with indented walls is also discussed. Based on the results, several conclusions are drawn, and limitations that require further study are also discussed.
| Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc149632 |
| Date | 08 1900 |
| Creators | Liu, Yang |
| Contributors | Dong, Pinliang, Rice, Murray D., Tiwari, Chetan |
| Publisher | University of North Texas |
| Source Sets | University of North Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Format | Text |
| Rights | Public, Liu, Yang, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved. |
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