Isbn: 9783032199348 - environmental monitoring with integrated earth observation data and machine learning (studies in computational intelligence, 1278) (9 Ergebnisse)

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Hardcover. Zustand: new. Hardcover. 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. mso-ansi-language: EN-US;">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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Hardcover. Zustand: Brand New. 107 pages. 6.30x0.47x9.49 inches. In Stock.

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Buch. Zustand: 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.…

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Buch. Zustand: 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. …

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Buch. Zustand: 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.…

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