1st Edition

Advances in Scalable and Intelligent Geospatial Analytics Challenges and Applications

421 Pages 99 Color & 77 B/W Illustrations
by CRC Press

421 Pages 99 Color & 77 B/W Illustrations
by CRC Press

421 Pages 99 Color & 77 B/W Illustrations
by CRC Press

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... Read more

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: Innovative Approaches for Geovisualization and Geovisual Analytics for Big Geospatial Data

11. Dashboard for Earth Observation

Manil Maskey, Rahul Ramachandran, Brian Freitag, Aaron Kaulfus, Aimee Barciauskas, Olaf Veerman, Leo Thomas, Iksha Gurung, and Muthukumaran Ramasubramanian

12. Visual Exploration of LiDAR Point Clouds

Satendra Singh and Jaya Sreevalsan-Nair

Section V: Other Advances in Geospatial Domain

13. Toward a Smart Metaverse City: Immersive Realism and 3D Visualization of Digital Twin Cities

Haowen Xu, Andy Berres, Yunli Shao, Chieh (Ross) Wang, Joshua R. New, and Olufemi A. Omitaomu

14. Current UAS Capabilities for Geospatial Spectral Solutions

David L. Cotten, Andrew Duncan, Andrew Harter, Matt Larson, and Brad Stinson

15. Flood Mapping and Damage Assessment Using Sentinel – 1 & 2 in Google Earth Engine of Port Berge & Mampikony Districts, Sophia Region, Madagascar

Penchala Vineeth Kurapati, Ashish Babu, Kesava Rao Pyla, Prasad NSR, and Venkata Ravi Babu Mandla

Section VI: Case Studies from the Geospatial Domain

16. Fuzzy-Based Meta-Heuristic and Bi-Variate Geo-Statistical Modelling for Spatial Prediction of Landslides

Suvam Das, Shubham Chaudhary, Shantanu Sarkar, and Debi Prasanna Kanungo

17. Understanding the Dynamics of the City through Crowdsourced Datasets: A Case Study of Indore City

Vipul Parmar and Anugrah Anilkumar Nagaich

18. A Hybrid Model for the Prediction of Land Use/Land Cover Pattern in Kurunegala City, Sri Lanka

Mohamed Haniffa Fathima Hasna, Mathanraj Seevarethnam, and Vasanthakumary Selvanayagam

19. Spatio-Temporal Dynamics of Tropical Deciduous Forests under Climate Change Scenarios in India

Rajit Gupta and Laxmi Kant Sharma

20. A Survey of Machine Learning Techniques in Forestry Applications Using SAR Data

Naveen Ramachandran, K.K. Sarma, Dibyajyoti Chutia, and Onkar Dikshit

Biography

Dr. Surya Durbha is a Professor at CSRE, Indian Institute of Technology Bombay (IITB). Before joining IITB, he held an adjunct faculty position in the Electrical and Computer Engineering Department at Mississippi State University. He has published over 80 peer reviewed articles and has written a book on the Internet of Things published by Oxford University Press in March 2021.

Dr. Jibonananda Sanyal serves as the Group Leader for Oak Ridge National Laboratory’s Computational Urban Sciences research group. He is an IEEE Senior Member, an ACM Distinguished Speaker, and a 2017 Knoxville’s 40 under 40 honoree.

Dr. Lexie Yang is a lead research scientist in the GeoAI Group at Oak Ridge National Laboratory. She leads several AI-enabled geoscience data analytics projects with large-scale multi-modality geospatial data. The recent work from her team has been widely used to support national-scale disaster assessment and management by federal and local agencies.

Dr. Sangita S. Chaudhari is a Professor in the Department of Computer Engineering, Ramrao Adik Institute of Technology Nerul, Navi Mumbai, India. She is vice chair of IEEE GRSS Mumbai Chapter and has published several journal articles and book chapters.

Dr. Ujwala Bhangale is an Associate Professor in the Department of Information Technology, at K.J. Somaiya College of Engineering, Somaiya Vidyavihar University, Mumbai, India. She has published several papers in IEEE/ACM publications.

Dr. Ujwala Bharambe is an Assistant Professor in the Department of Computer Engineering, at Thadomal Shahani Engineering College, Mumbai, India. She has published several papers in IEEE/ACM publications.

Dr. Kuldeep Kurte is a research scientist in the Computational Urban Sciences Group (CUSG) at Oak Ridge National Laboratory. He has experience working on various applications on different HPC platforms from NVIDIA Jetson Tk1 to the Summit supercomputer.