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portada GeoAI for Agricultural Land Degradation Assessment: Predictive Analysis of Groundnut Cover Using Geospatial Intelligence
Type
Physical Book
Publisher
Author
Language
English
Pages
68
Format
Paperback
ISBN13
9786630319880

GeoAI for Agricultural Land Degradation Assessment: Predictive Analysis of Groundnut Cover Using Geospatial Intelligence

Adam Mohamed, Elkhatim Ahmed (Author) · GlobeEdit · Paperback

GeoAI for Agricultural Land Degradation Assessment: Predictive Analysis of Groundnut Cover Using Geospatial Intelligence - Adam Mohamed, Elkhatim Ahmed

New Book Imported to Austria
Delivery: 30 Nov - 02 Dec Shipping: 14 to 15 business days.
66,54 €
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66,54 €

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Synopsis "GeoAI for Agricultural Land Degradation Assessment: Predictive Analysis of Groundnut Cover Using Geospatial Intelligence"

Agricultural land degradation poses a growing threat to food security, particularly in regions affected by conflict and environmental change. This book presents an innovative GeoAI-based framework for assessing land degradation and predicting groundnut (peanut) crop cover in Al-Qadarif State, Sudan-the country's largest rain-fed agricultural region.Using multi-temporal Sentinel-2 satellite imagery, Google Earth Engine, and advanced machine learning algorithms, including Random Forest and Support Vector Machine models, the study maps changes in agricultural land use between 2020 and 2025. It examines the impact of armed conflict on crop production, identifies areas at high risk of land abandonment, and demonstrates the effectiveness of artificial intelligence for monitoring agricultural systems in challenging environments.Combining remote sensing, geospatial analytics, and predictive modeling, this book provides valuable insights for researchers, GIS specialists, policymakers, and agricultural planners. It offers practical guidance for supporting precision agriculture, sustainable land management, and post-conflict reconstruction through data-driven decision-making.

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