Spatial Gems

Spatial gems are computational techniques for processing spatial data. This book, a follow-up to the first Spatial Gems volume, is a further collection of techniques contributed by leading research experts. Although these approaches were developed by their authors as part of larger research projects, the gems represent fundamental solutions that are generically applicable to many different problems. Our goal is to expose these useful techniques that are not yet in textbooks and often buried inside technical research papers to share them with software developers, graduate students, professors, and professional researchers.

John Krumm graduated from the School of Computer Science at Carnegie Mellon University in 1993 with a Ph.D. in robotics and a thesis on texture analysis in images. He worked at the Robotics Center of Sandia National Laboratories in Albuquerque, NM, for the next four years. His main projects there were computer vision for object recognition for use in robots and vehicles. He has been at Microsoft Research in Redmond, WA, USA, since 1997, and is currently a senior principal researcher. His research focuses on understanding peoples' location and how to use that information to benefit the user. In 2017, he received a 10-year impact award for a paper on location privacy from the ACM UbiComp conference, and another from the same conference in 2021. He is an inventor on 75 patents. Dr. Krumm was a PC chair for UbiComp 2007, ACM SIGSPATIAL 2013, and ACM SIGSPATIAL 2014. He is a past coeditor in chief of the Journal of Location Based Services. He currently serves as an associate editor for ACM Transactions on Spatial Algorithms and Systems and on the editorial board of IEEE Pervasive Computing Magazine. He is on the executive committee of ACMSIGSPATIAL and part of the Science Advisory Committee of the Geospatial Science and Human Security Division at Oak Ridge National Laboratory.

Andreas Züfle is an associate professor at George Mason University, USA. He received his Ph.D. in Computer Science at Ludwig Maximilian University of Munich, Germany (LMU), in 2013. Dr. Züfle's research focuses on data management. He is mainly known for his contribution to the field of geospatial data management and mining. In this area, he has made contributions in several subareas, notably uncertain data management, spatial indexing, clustering, and geosimulation. His interdisciplinary work has applications in geosciences, transportation, epidemiology, and social science.