Spatial Tessellations: Concepts and Applications of Voronoi Diagrams, Second Edition

By Atsuyuki Okabe, B. Boots, Kokichi Sugihara, Sung Nok Chiu, D. Kendall. Wiley Series in Probability and Mathematical Statistics, 2000

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Bias in species range estimates from minimum convex polygons: implications for conservation and options for improved planning (2003, background): “The advantage of the α-hull is that it provides a more detailed description of the habitat’s shape, is capable of breaking the hull into several discrete hulls when it spans an uninhabitable region, and yields a hull unconstrained by convexity on its outer surface (Okabe et al., 2000).”
Role of cell regularity and relative density on elasto-plastic compression response of random honeycombs generated using Voronoi diagrams (2014, methodology): “(201 space with the nearest nucleus (Klein, 1989; Moller, 1994; Okabe et al., 1945). This generates n regions that form the so-called Voronoi diagram. In this work, such a division of space has been implemented in Matlab using the Qhull algorithm (Barber et al., 1996).(2) The Voronoi diagram represe”
Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms (2009, background): “The deployment problem studied in this chapter is related to the literature on facility location [Drezner, 1995, Okabe et al., 2000, Du et al., 1999] and geometric optimization [Agarwal and Sharir, 1998, Boltyanski et al., 1999], see also Section 2.4.”