Supervised Learning in Remote Sensing and Geospatial Science, 9780443293061
Paperback
Unlock geospatial insights: Supervised learning for actionable data and mapping.
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Supervised Learning in Remote Sensing and Geospatial Science

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  • Paperback

    444 pages

  • Release Date

    1 October 2025

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Summary

Unlock Earth Insights: A Practical Guide to Supervised Learning in Remote Sensing and Geospatial Science

Supervised Learning in Remote Sensing and Geospatial Science is an invaluable resource focusing on practical applications of supervised learning in remote sensing and geospatial data science. Emphasizing practicality, the book delves into creating labeled datasets for training and evaluating models. It addresses common challenges like data imbalance and offers methods for assessi…

Book Details

ISBN-13:9780443293061
ISBN-10:0443293066
Author:Aaron E. Maxwell, Christopher Ramezan, Yaqian He
Publisher:Elsevier - Health Sciences Division
Imprint:Elsevier - Health Sciences Division
Format:Paperback
Number of Pages:444
Release Date:1 October 2025
Weight:0g
Dimensions:276mm x 216mm
About The Author

Aaron E. Maxwell

Aaron Maxwell is an Assistant Professor in the Department of Geology and Geography at West Virginia University. He is also the director of West Virginia View, an AmericaView member organization, and a faculty director of the West Virginia GIS Technical Center. He holds a PhD in Geology from West Virginia University and is a West Virginia native. The primary objectives of his work are to investigate computational methods to extract useful information from geospatial data that can inform decision making and to train students to be effective and thoughtful geospatial scientists and professionals. His teaching focuses on geographic information science (GISc), remote sensing, and geospatial data science. His research interests include spatial predictive modeling, accuracy assessment, applications of machine learning and deep learning in the geospatial sciences, digital terrain analysis, geographic object-based image analysis (GEOBIA), and geomorphic and forest mapping and modeling.

Christopher Ramezan is an Assistant Professor in the Department of Management Information Systems at West Virginia University. He is also the program director of the Master of Science in Business Cybersecurity Management program in the John Chambers College of Business and Economics. He received his Ph.D. in 2019 in Geography from West Virginia University, specializing in remote sensing. His research interests in remote sensing include applied machine learning, sample selection, model optimization, image segmentation, geographic object-based image analysis (GEOBIA), and land-use land-cover classification. He currently teaches courses on data and network communications, enterprise security architecture, operational technology and industrial control systems security, and cybersecurity data analytics. He has over 10 years’ experience in the information technology field and was the former information security officer of the Eberly College of Arts and Sciences at West Virginia University. He also holds over 20 industry certifications including the CISSP, CISM, CASP, and CDPSE.

Yaqian He is an Assistant Professor in the Department of Geography at the University of Central Arkansas. She obtained her Ph.D. in 2018 in Geography from West Virginia University. Her research focuses on leveraging geospatial methods, deep learning, and machine learning algorithms, as well as Earth System models to detect and attribute land cover and land use change across the globe and assess how such changes in turn affect natural systems (e.g., climate and ecosystem). Her teaching includes geographic information systems, geographic field techniques, python programming for spatial analytics, and cartography. She is also an FAA-certified Remote Pilot.

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