Supervised Learning in Remote Sensing and Geospatial Science

di Aaron E Maxwell (Autore)

Christopher Ramezan (Autore)

Yaqian He (Autore)

Elsevier - Health Sciences Division, 2025

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 assessing model performance. This guide bridges the gap between theory and practice, providing tools and techniques for extracting actionable information from raw geospatial data. The book covers all aspects of supervised learning workflows, including preparing diverse remotely sensed and geospatial data inputs. It equips researchers, practitioners, and students with essential knowledge for applied mapping and modeling tasks, making it an indispensable reference for advancing geospatial science.

• Autore: Aaron E Maxwell, Christopher Ramezan, Yaqian He
• Editore: Elsevier - Health Sciences Division
• Anno: 2025
• Rilegatura: Paperback / softback
• Pagine: 432 p.
• Dimensioni: 276 x 216 mm
• Peso: 450 gr.
• EAN: 9780443293061

Testo in English