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Big data : techniques and technologies in geoinformatics
- Date_TXT
- Boca Raton : CRC press, cop. 2014
- Cote
- 526.6 KAR
- Auteur
- Karimi, Hassan A.
- Type de document
- Livre
Description :
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.
Features
• Explains the challenges and issues of big data in geoinformatics applications
• Discusses and analyzes the techniques, technologies, and tools for storing, managing, and computing geospatial big data
• Familiarizes the readers with the advanced techniques and technologies used for geospatial big data research
• Provides insight into new opportunities offered by geospatial big data
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.