I Introduction.- II Spatial Big Data Platforms & Infrastructures.- III Spatial Data Acquisition.- IV Indexing and Retrieval of Spatial Big Data.- V Scalable Algorithms for Spatial Analytics.- VI Data Mining, Machine Learning and Artificial Intelligence.- VII Visualization & Interaction.- VIII Applications.
About the Author: Martin Werner The research area of Prof. Werner (*1984) includes methodological research around topics of acquisition, organization, compression, analysis, and visualization of georeferenced or geometric data in large scales. He puts emphasis on methods of distributed computing, machine learning, image and text analysis, randomized data structures, high performance computing and quantum algorithms.
Martin Werner studied mathematics at University Bonn, did a doctorate at the intersection of geometry and applications related to indoor navigation at LMU Munich. In his time as a postdoctoral researcher, junior professor, and senior researcher he completed his view on the processing of spatial data to a comprehensive perspective with stations at LMU Munich, Leibniz-University Hannover, German Aerospace Center (DLR), and UniBW Munich. In April 2020 he joined the faculty of aerospace and geodesy with a professorship for Big Geospatial Data Management.
Yao-Yi Chiang Yao-Yi Chiang, Ph.D., is an Associate Professor (Research) in Spatial Sciences, the Director of the Spatial Computing Laboratory, and the Associate Director of the NSF's Integrated Media Systems Center (IMSC) at the University of Southern California (USC). He is also a faculty member in Data Science in the USC Viterbi Data Science M.S. program. He is an Action Editor of GeoInformatica (Springer). Dr. Chiang received his Ph.D. degree in Computer Science from the University of Southern California, his bachelor's degree in Information Management from the National Taiwan University. His current research combines spatial science theories with computer algorithms to enable the discovery of useful insights from heterogeneous data for solving real-world problems. His research interests include information integration, machine learning, data mining, computer vision, and knowledge graphs. He has received funding from agencies such as NSF, NIH, DARPA, NGA, and NEH, as well as from industry partners such as NTT Global Networks, BAE Systems, Conveyancing Liability Solutions, and TerraGo. He was recently a visiting researcher at Google AI (2019). Before USC, Dr. Chiang worked as a research scientist for Geosemble Technologies and Fetch Technologies in California. Geosemble Technologies was founded based on a patent on geospatial data fusion techniques, and he was a co-inventor.
