English

Potential UAV Landing Sites Detection through Digital Elevation Models Analysis

Computer Vision and Pattern Recognition 2021-07-16 v1 Graphics

Abstract

In this paper, a simple technique for Unmanned Aerial Vehicles (UAVs) potential landing site detection using terrain information through identification of flat areas, is presented. The algorithm utilizes digital elevation models (DEM) that represent the height distribution of an area. Flat areas which constitute appropriate landing zones for UAVs in normal or emergency situations result by thresholding the image gradient magnitude of the digital surface model (DSM). The proposed technique also uses connected components evaluation on the thresholded gradient image in order to discover connected regions of sufficient size for landing. Moreover, man-made structures and vegetation areas are detected and excluded from the potential landing sites. Quantitative performance evaluation of the proposed landing site detection algorithm in a number of areas on real world and synthetic datasets, accompanied by a comparison with a state-of-the-art algorithm, proves its efficiency and superiority.

Keywords

Cite

@article{arxiv.2107.06921,
  title  = {Potential UAV Landing Sites Detection through Digital Elevation Models Analysis},
  author = {Efstratios Kakaletsis and Nikos Nikolaidis},
  journal= {arXiv preprint arXiv:2107.06921},
  year   = {2021}
}

Comments

Proceedings of the 2019 27th European Signal Processing Conference (EUSIPCO) satellite workshop "Signal Processing Computer vision and Deep Learning for Autonomous Systems"

R2 v1 2026-06-24T04:12:16.467Z