Thursday 25th of April 2024
 

Automated Extraction of Geospatial Features from Satellite Imagery: Computer Vision Oriented Plane Surveying


Usman Babawuro and Zou Beiji

The paper explores and assesses the potential uses of high resolution satellite imagery and digital image processing algorithms for the auto detection and extraction of geospatial features, farmlands, for the purpose of statutory plane surveying tasks. The satellite imagery was georectified to provide the planar surface necessary for morphometric assessments followed by integrated image processing algorithms. Precisely, Canny edge algorithm followed by morphological closing as well as Hough transform for extracting lines of features was used. The algorithms were tested using Quick bird satellite imagery and in all cases we obtained encouraging results. This shows that computer vision and image processing using high resolution satellite imagery could be used for cadastration purposes, where property boundaries are needed and used for compensation purposes and other statutory surveying functions. The error matrix of the delineated boundaries is estimated as equal to 73.33%.

Keywords: Satellite imagery, Morphological operations, Hough Transform, Plane surveying, computer vision

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ABOUT THE AUTHORS

Usman Babawuro
Usman Babawuro graduated from the Department of Surveying, Ahmadu Bello University, ABU, Zaria, Nigeria, with a Bachelor degree in Surveying. He then, obtained PGD and MSc in Computer Science and Technology from Central South University Changsha, China in 2002. He worked as a Surveyor for some years, executing legal surveys in Nigeria. Then he joined the services of the Department of Computer Science, Kano University of Science and Technology, KUST, Wudil, Nigeria as an academic staff. To further his educational career, in 2009, he pursued a Doctoral Programme, at the School of Information Science and Engineering, Central South University, Changsha, China, where he worked with Image Processing and Virtual Reality Laboratory of the University for his research. He has authored several papers in international journals and conferences. He is a professional member of Nigerian Computer Society, NCS, and Computer Registration Council of Nigeria, CPN. His research interest includes image and video processing, pattern recognition, feature extraction and machine learning.

Zou Beiji
Zou Beiji • Education Background 1978 – 1982 Zhejiang University, Hangzhou, China, BSC Computer Software. 1982 – 1984 Qinghua University, Beijing, China, MSc Computer Application. 1997 – 2001 Hunan University, Changsha, China, Ph.D. Control Theory and Engineering • Research Experience 2002 – 2003 Qinghua University Post Doctor 2003–2004 Griffith University, Australia as a Visiting Scholar.


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