Advances in Scalable and Intelligent Geospatial Analytics

图书简介

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.FEATURESDemonstrates the recent advances in geospatial analytics tools, technologies, and algorithmsProvides insight and direction to the geospatial community regarding the future trends in scalable and intelligent geospatial analyticsExhibits recent geospatial applications and demonstrates innovative ways to use big geospatial data to address various domain-specific, real-world problemsRecognizes the analytical and computational challenges posed and opportunities provided by the increased volume, velocity, and veracity of geospatial dataThis 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.

Section I: Introduction to Geospatial Analytics 1. Geospatial Technology – Developments, Present Scenario and Research Challenges Parvatham Venkatachalam Section II: Geo-Ai 2. Perspectives on Geospatial Artificial Intelligence Platforms for Multimodal Spatiotemporal Datasets C. V. Krishnakumar Iyer, Swetava Ganguli, and Vipul Pandey 3. Temporal Dynamics of Place and Mobility Kevin Sparks, Jesse Piburn, Andy Berres, Marie Urban, and Gautam Thakur 4. Geospatial Knowledge Graph Construction Workflow for Semantics-Enabled Remote Sensing Scene Understanding Abhishek Potnis, Surya S Durbha, Rajat Shinde, and Pratyush Talreja 5. Geosemantic Standards-Driven Intelligent Information Retrieval Framework for 3D LiDAR Point Clouds Rajat C. Shinde, Surya S Durbha, Abhishek V. Potnis, and Pratyush V. Talreja 6. Geospatial Analytics Using Natural Language Processing Manimala Mahato and Rekha Ramesh Section III: Scalable Geospatial Analytics 7. A Scalable Automated Satellite Data Downloading and Processing Pipeline Developed on AWS Cloud for Agricultural Applications Ankur Pandit, Suryakant Sawant, Rishabh Agrawal, Jayantrao Mohite, and Srinivasu Pappula 8. Providing Geospatial Intelligence through a Scalable Imagery Pipeline Andrew Reith, Jacob McKee, Amy Rose, Melanie Laverdiere, Benjamin Swan, David Hughes, Sophie Voisin, Lexie Yang, Laurie Varma, Liz Neunsinger, and Dalton Lunga 9. Distributed Deep Learning and Its Application in Geo-spatial Analytics Nilkamal More, Jash Shah, V.B. Nikam, and Biplab Banerjee 10. High-Performance Computing for Processing Big Geospatial Disaster Data Pratyush V. Talreja, Surya S Durbha, Rajat C. Shinde, and Abhishek V. Potnis Section IV: Geovisualization: Innov

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Advances in Scalable and Intelligent Geospatial Analytics 可扩展与智能地理空间分析的进展：挑战与应用 大地测量技术

Advances in Scalable and Intelligent Geospatial Analytics

可扩展与智能地理空间分析的进展：挑战与应用
大地测量技术