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This book focuses on feature extraction methods for optical geospatial data using Machine Learning (ML). It is a practical guide for professionals and graduate students starting a career in information extraction. It explains spatial feature extraction in an easy-to-understand way and includes real case studies.
List of contents
Introduction. Geospatial Big Data for Machine Learning. Spatial Feature Extraction. Building Height Estimation. 3D Feature Mapping. Applications and Case Studies.
About the author
Dr. Bharath H. Aithal, is currently an assistant professor at Ranbir and Chitra Gupta School of Infrastructure Design and Management at Indian Institute of Technology Kharagpur. He obtained his Ph.D. from Indian Institute of Science. His areas of interest are spatial pattern analysis, Urban growth modelling, natural disasters, geoinformatics, landscape modelling, urban planning, open-source GIS, and digital image processing. He has published over 50 research papers in reputed peer reviewed journals and has presented over 100 papers in international and national conferences and symposiums. In 2020 he published with CRC Press,
Urban Growth Patterns in India: Spatial Analysis for Sustainable Development and has contributed 6 book chapters to other publications.
Dr. Prakash P.S. is a postdoctoral researcher at Irish Centre of High-End Computing, Galway, Ireland, working on geo-spatial technologies. Prakash has substantial experience with earth observation datasets, including remote sensing, drone-based imagery, surveying, spatial libraries, machine learning, and artificial intelligence technologies. He has worked in geospatial technology and the renewable energy industry for over four years. His other qualifications include a Master of Technology in Geoinformatics from Bangalore's Karnataka State Remote Sensing Application Center and a Bachelor of Civil Engineering from Bangalore's Rashtreeya Vidyalaya College of Engineering.
Summary
This book focuses on feature extraction methods for optical geospatial data using Machine Learning (ML). It is a practical guide for professionals and graduate students starting a career in information extraction. It explains spatial feature extraction in an easy-to-understand way and includes real case studies.
