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Explainable Machine Learning for Geospatial Data Analysis: A Data-Centric Approach

Explainable Machine Learning for Geospatial Data Analysis: A Data-Centric Approach

Paperback

Technology & EngineeringTravel GeneralGeneral Computers

ISBN10: 1032503815
ISBN13: 9781032503813
Publisher: CRC Press
Published: Jun 22 2026
Pages: 266
Weight: 0.87
Height: 0.59 Width: 6.14 Depth: 9.21
Language: English

Explainable machine learning (XML), a subfield of AI, is focused on making complex AI models understandable to humans. This book highlights and explains the details of machine learning models used in geospatial data analysis. It demonstrates the need for a data-centric, explainable machine learning approach to obtain new insights from geospatial data. It presents the opportunities, challenges, and gaps in the machine and deep learning approaches for geospatial data analysis and how they are applied to solve various environmental problems in land cover changes and in modeling forest canopy height and aboveground biomass density. The author also includes guidelines and code scripts (R, Python) valuable for practical readers.

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