Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur L2-9783725881857
Quantité disponible : Plus de 20 disponibles
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Hardcover. Etat : new. Hardcover. Soil is one of Earth's most vital resources, playing a central role in sustaining terrestrial ecosystems, food production, and climate regulation. It regulates water flow and quality, stores carbon, and supplies essential nutrients for plant growth. Understanding key soil properties, including moisture, texture, organic matter, and nutrient availability, is therefore fundamental for soil health assessment, effective land management, and sustainable agriculture. As the need for robust soil protection strategies grows, new monitoring capacities such as hyperspectral sensing are significantly expanding our data horizons. Consequently, the integration of remote sensing with AI and machine learning has emerged as a powerful framework for tracking soil degradation, providing critical support for policy-making and carbon credit systems. This Reprint presents recent advances in methodologies, workflows, and sensing technologies for estimating and monitoring soil properties using spaceborne and proximal data. The contributions address digital soil mapping, AI-based prediction frameworks, uncertainty-aware modelling, soil organic carbon estimation, soil moisture assessment, and the monitoring of soil degradation and erosion. Overall, this Reprint illustrates the expanding role of Earth observation in soil science and demonstrates how advances in AI, machine learning, and sensor integration are supporting more robust, scalable, and operational soil monitoring frameworks for research and daily applications. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783725881857
Quantité disponible : 1 disponible(s)
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9783725881857
Quantité disponible : Plus de 20 disponibles
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Hardcover. Etat : new. Hardcover. Soil is one of Earth's most vital resources, playing a central role in sustaining terrestrial ecosystems, food production, and climate regulation. It regulates water flow and quality, stores carbon, and supplies essential nutrients for plant growth. Understanding key soil properties, including moisture, texture, organic matter, and nutrient availability, is therefore fundamental for soil health assessment, effective land management, and sustainable agriculture. As the need for robust soil protection strategies grows, new monitoring capacities such as hyperspectral sensing are significantly expanding our data horizons. Consequently, the integration of remote sensing with AI and machine learning has emerged as a powerful framework for tracking soil degradation, providing critical support for policy-making and carbon credit systems. This Reprint presents recent advances in methodologies, workflows, and sensing technologies for estimating and monitoring soil properties using spaceborne and proximal data. The contributions address digital soil mapping, AI-based prediction frameworks, uncertainty-aware modelling, soil organic carbon estimation, soil moisture assessment, and the monitoring of soil degradation and erosion. Overall, this Reprint illustrates the expanding role of Earth observation in soil science and demonstrates how advances in AI, machine learning, and sensor integration are supporting more robust, scalable, and operational soil monitoring frameworks for research and daily applications. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9783725881857
Quantité disponible : 1 disponible(s)
Vendeur : AussieBookSeller, Truganina, VIC, Australie
Hardcover. Etat : new. Hardcover. Soil is one of Earth's most vital resources, playing a central role in sustaining terrestrial ecosystems, food production, and climate regulation. It regulates water flow and quality, stores carbon, and supplies essential nutrients for plant growth. Understanding key soil properties, including moisture, texture, organic matter, and nutrient availability, is therefore fundamental for soil health assessment, effective land management, and sustainable agriculture. As the need for robust soil protection strategies grows, new monitoring capacities such as hyperspectral sensing are significantly expanding our data horizons. Consequently, the integration of remote sensing with AI and machine learning has emerged as a powerful framework for tracking soil degradation, providing critical support for policy-making and carbon credit systems. This Reprint presents recent advances in methodologies, workflows, and sensing technologies for estimating and monitoring soil properties using spaceborne and proximal data. The contributions address digital soil mapping, AI-based prediction frameworks, uncertainty-aware modelling, soil organic carbon estimation, soil moisture assessment, and the monitoring of soil degradation and erosion. Overall, this Reprint illustrates the expanding role of Earth observation in soil science and demonstrates how advances in AI, machine learning, and sensor integration are supporting more robust, scalable, and operational soil monitoring frameworks for research and daily applications. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9783725881857
Quantité disponible : 1 disponible(s)
Vendeur : preigu, Osnabrück, Allemagne
Buch. Etat : Neu. Recent Advances in Remote Sensing of Soil Science | Buch | Englisch | 2026 | MDPI AG | EAN 9783725881857 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 136373225
Quantité disponible : 5 disponible(s)