Big Data Techniques and Technologies in Geoinformatics
Big data has always been a major challenge in geoinformatics as geospatial data come in various types and formats, new geospatial data are acquired very fast, and geospatial databases are inherently very large. And while there have been advances in hardware and software for handling big data, they often fall short of handling geospatial big data efficiently and effectively. Big Data: Techniques and Technologies in Geoinformatics tackles these challenges head on, integrating coverage of techniques and technologies for storing, managing, and computing geospatial big data.
Providing a perspective based on analysis of time, applications, and resources, this book familiarizes readers with geospatial applications that fall under the category of big data. It explores new trends in geospatial data collection, such as geo-crowdsourcing and advanced data collection technologies such as LiDAR point clouds. The book features a range of topics on big data techniques and technologies in geoinformatics including distributed computing, geospatial data analytics, social media, and volunteered geographic information.
With chapters contributed by experts in geoinformatics and in domains such as computing and engineering, the book provides an understanding of the challenges and issues of big data in geoinformatics applications. The book is a single collection of current and emerging techniques, technologies, and tools that are needed to collect, analyze, manage, process, and visualize geospatial big data.
Distributed and Parallel Computing, Monir H. Sharker and Hassan A. Karimi
GEOSS Clearinghouse: Integrating Geospatial Resources to Support the Global Earth Observation System of Systems, Chaowei Yang, Kai Liu, Zhenlong Li, Wenwen Li, Huayi Wu, Jizhe Xia, Qunying Huang, Jing Li, Min Sun, Lizhi Miao, Nanyin Zhou, and Doug Nebert
Using a Cloud Computing Environment to Process Large 3D Spatial Datasets, Ramanathan Sugumaran, Jeffrey Burnett, and Marc P. Armstrong
Building Open Environments to Meet Big Data Challenges in Earth Sciences, Meixia Deng and Liping Di
Developing Online Visualization and Analysis Services for NASA Satellite-Derived Global Precipitation Products during the Big Geospatial Data Era, Zhong Liu, Dana Ostrenga, William Teng, and Steven Kempler
Algorithmic Design Considerations for Geospatial and/or Temporal Big Data, Terence van Zyl
Machine Learning on Geospatial Big Data, Terence van Zyl
Spatial Big Data: Case Studies on Volume, Velocity, and Variety, Michael R. Evans, Dev Oliver, Xun Zhou, and Shashi Shekhar
Exploiting Big VGI to Improve Routing and Navigation Services, Mohamed Bakillah, Johannes Lauer, Steve H.L. Liang, Alexander Zipf, Jamal Jokar Arsanjani, Amin Mobasheri, and Lukas Loos
Efficient Frequent Sequence Mining on Taxi Trip Records Using Road Network Shortcuts, Jianting Zhang
Geoinformatics and Social Media: New Big Data Challenge, Arie Croitoru, Andrew Crooks, Jacek Radzikowski, Anthony Stefanidis, Ranga R. Vatsavai, and Nicole Wayant
Insights and Knowledge Discovery from Big Geospatial Data Using TMC-Pattern, Roland Assam and Thomas Seidl
Geospatial Cyberinfrastructure for Addressing the Big Data Challenges on the Worldwide Sensor Web, Steve H.L. Liang and Chih-Yuan Huang
OGC Standards and Geospatial Big Data, Carl Reed