Artificial intelligence techniques in extracting building and tree footprints using aerial imagery and LiDAR data-Reference-Cited by-同舟云学术

Artificial intelligence techniques in extracting building and tree footprints using aerial imagery and LiDAR data

Published:2020-11-19 Issue: Volume: Page:1-29
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Vayghan Saeideh Sahebi¹,Salmani Mohammad²,Ghasemkhani Neda³,Pradhan Biswajeet⁴⁵⁶^ORCID,Alamri Abdullah⁷

Affiliation:

1. Department of Remote Sensing and GIS, Kharazmi University, Tehran, Iran

2. Department of Remote Sensing and GIS, University of Tehran, Tehran, Iran

3. Department of Geography and Urban Planning, Islamic Azad University, Tehran, Iran

4. The Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and Information Technology, University of Technology Sydney, New South Wales, Australia

5. Department of Energy and Mineral Resources Engineering, Sejong University, Gwangjin-gu, Korea Seoul

6. Earth Observation Center, Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

7. Department of Geology and Geophysics, College of Science, King Saud University, Riyadh, Saudi Arabia

Funder

University of Technology Sydney

King Saud University

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2020.1844311

Reference53 articles.

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3. Building Detection in Complex Scenes Thorough Effective Separation of Buildings from Trees

4. Axelsson P.1992. Minimum description length as an estimator with robust properties. In: Proc Int Work Robust Comput Vis. p. 137–150.

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