finelybook
Advances in Scalable and Intelligent Geospatial Analytics: Challenges and Applications 1st Edition
by Surya S Durbha (Editor), Jibonananda Sanyal (Editor), Lexie Yang (Editor), Sangita S Chaudhari (Editor), Ujwala Bharambe (Editor), Kuldeep Kurte (Editor), Ujwala Bhangale (Editor)
Publisher Finelybook 出版社: CRC Press; 1st edition (May 12, 2023)
Language 语言: English
pages 页数: 428 pages
ISBN-10 书号: 1032200316
ISBN-13 书号: 9781032200316
Book Description
Geospatial data acquisition and analysis techniques have experienced tremendous growth in the last few years, providing an opportunity to solve previously unsolved environmental- and natural resource-related problems. However, a variety of challenges are encountered in processing the highly voluminous geospatial data in a scalable and efficient manner. Technological advancements in high-performance computing, computer vision, and big data analytics are enabling the processing of big geospatial data in an efficient and timely manner. Many geospatial communities have already adopted these techniques in multidisciplinary geospatial applications around the world. This book is a single source that offers a comprehensive overview of the state of the art and future developments in this domain.
FEATURES
Demonstrates the recent advances in geospatial analytics tools, technologies, and algorithms
Provides insight and direction to the geospatial community regarding the future trends in scalable and intelligent geospatial analytics
Exhibits recent geospatial applications and demonstrates innovative ways to use big geospatial data to address various domain-specific, real-world problems
Recognizes the analytical and computational challenges posed and opportunities provided by the increased volume, velocity, and veracity of geospatial data
This book is beneficial to graduate and postgraduate students, academicians, research scholars, working professionals, industry experts, and government research agencies working in the geospatial domain, where GIS and remote sensing are used for a variety of purposes. Readers will gain insights into the emerging trends on scalable geospatial data analytics.
