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| Reihe | Studies in Computational Intelligence |
|---|---|
| Themen | Informatik und Informationstechnologie Informatik Künstliche Intelligenz (KI) |
| ISBN | 9783032199348 |
| Sprache | Englisch |
| Erscheinungsdatum | 15.05.2026 |
| Größe | 23.5 x 15.5 cm |
| Verlag | Springer International Publishing |
| Lieferzeit | Lieferung in 7-14 Werktagen |
| Herstellerangaben | Anzeigen Springer Nature Customer Service Center GmbH Europaplatz 3 | DE-69115 Heidelberg ProductSafety@springernature.com |
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.
| Reihe | Studies in Computational Intelligence |
|---|---|
| Themen | Informatik und Informationstechnologie Informatik Künstliche Intelligenz (KI) |
| ISBN | 9783032199348 |
| Sprache | Englisch |
| Erscheinungsdatum | 15.05.2026 |
| Größe | 23.5 x 15.5 cm |
| Verlag | Springer International Publishing |
| Lieferzeit | Lieferung in 7-14 Werktagen |
| Herstellerangaben | Anzeigen Springer Nature Customer Service Center GmbH Europaplatz 3 | DE-69115 Heidelberg ProductSafety@springernature.com |
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