Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 208,28
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Idioma: Inglés
Publicado por Springer, Berlin, Springer, 2026
ISBN 10: 3032199344 ISBN 13: 9783032199348
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 156,28
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book offers practical insights for researchers and policymakers to demonstrate how EO and ML can strengthen environmental monitoring to support informed decision-making, and advance sustainable development. The Earth faces rising challenges like climate instability, land degradation, water scarcity, rapid urban expansion, etc., making reliable environmental monitoring imperative. Traditional methods lack the precision and scale required for global environmental monitoring. However, advances in Earth Observation (EO) and Machine Learning (ML) enable accurate, large-scale environmental monitoring through accessible open-source datasets. Further ML integration with these datasets supports predictive analysis and detailed environmental assessments. Thus, this book outlines the principles of EO, data management, ML integration, and applies them through a case study of the Narmada River Basin, India to examine land use, pollution, and the overall environmental conditions.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 218,61
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 217,34
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Idioma: Inglés
Publicado por Springer, Berlin, Springer Jul 2026, 2026
ISBN 10: 3032199344 ISBN 13: 9783032199348
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 149,79
Cantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book offers practical insights for researchers and policymakers to demonstrate how EO and ML can strengthen environmental monitoring to support informed decision-making, and advance sustainable development. The Earth faces rising challenges like climate instability, land degradation, water scarcity, rapid urban expansion, etc., making reliable environmental monitoring imperative. Traditional methods lack the precision and scale required for global environmental monitoring. However, advances in Earth Observation (EO) and Machine Learning (ML) enable accurate, large-scale environmental monitoring through accessible open-source datasets. Further ML integration with these datasets supports predictive analysis and detailed environmental assessments. Thus, this book outlines the principles of EO, data management, ML integration, and applies them through a case study of the Narmada River Basin, India to examine land use, pollution, and the overall environmental conditions. 84 pp. Englisch.
Librería: moluna, Greven, Alemania
EUR 127,40
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
Librería: preigu, Osnabrück, Alemania
EUR 132,10
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Añadir al carritoBuch. Condición: Neu. Environmental Monitoring with Integrated Earth Observation Data and Machine Learning | Srija Roy (u. a.) | Buch | xxiii | Englisch | 2026 | Springer | EAN 9783032199348 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 149,79
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book offers practical insights for researchers and policymakers to demonstrate how EO and ML can strengthen environmental monitoring to support informed decision-making, and advance sustainable development. The Earth faces rising challenges like climate instability, land degradation, water scarcity, rapid urban expansion, etc., making reliable environmental monitoring imperative. Traditional methods lack the precision and scale required for global environmental monitoring. However, advances in Earth Observation (EO) and Machine Learning (ML) enable accurate, large-scale environmental monitoring through accessible open-source datasets. Further ML integration with these datasets supports predictive analysis and detailed environmental assessments. Thus, this book outlines the principles of EO, data management, ML integration, and applies them through a case study of the Narmada River Basin, India to examine land use, pollution, and the overall environmental conditions.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 108 pp. Englisch.