This book includes concept, state-of-the-art methodologies, techniques used in soil nutrients and irrigation water management. It covers soil moisture flow, nutrient dynamics, crop water estimation techniques, crop water productivity, soil health, crop simulation modeling, and remote sensing/GIS applications in irrigation water management.
This book includes concept, state-of-the-art methodologies, techniques used in soil nutrients and irrigation water management. It covers soil moisture flow, nutrient dynamics, crop water estimation techniques, crop water productivity, soil health, crop simulation modeling, and remote sensing/GIS applications in irrigation water management.
Shivam Gupta is an Assistant Professor in the Department of Irrigation and Drainage Engineering, Mahamaya College of Agricultural Engineering and Technology, Acharya Narendra Dev University of Agriculture and Technology, Ayodhya, Uttar Pradesh. Sushil Kumar Himanshu is an Assistant Professor in the Department of Food, Agriculture and Bio-resources, School of Environment, Resources and Development, Asian Institute of Technology (AIT), Pathum Thani, Thailand. Pankaj Kumar Gupta is a Ramanujan fellow, at the Indian Institute of Technology (IIT) Delhi, India. He is also an adjunct assistant professor at the University of Waterloo, Canada.
Inhaltsangabe
Chapter 1. AI for Sustainable Agriculture in the Face of Climate Change. Chapter 2. Development of a Modeling Approach for Agriculture Crop Type Classification Aiming at Large-Scale Precision Agriculture by Synergistic Utilization of Fused Sentinel-1 and Sentinel-2 Datasets with UAV Datasets. Chapter 3. IoT and Smart Sensor Applications in Nutrient and Irrigation Water Management. Chapter 4. Assessing Nutrient Variability Across Irrigation Management Zones Using Unsupervised Learning and Mixed Models. Chapter 5. Comparative Study on Estimation of Sediment Yield Index Using GIS and Remote Sensing for Soil Erosion Prediction. Chapter 6. Soil Moisture Flows Modeling for Micro-Irrigation and Nutrient Load Management. Chapter 7. Applications of Remote Sensing and GIS Techniques in the Monitoring of Ecosystem Services. Chapter 8. Evaluation of Machine Learning Algorithms in Soil Water Content Prediction at Multiple Depths. Chapter 9. Artificial Intelligence Application in Database Management for SCADA Systems. Chapter 10. Entropy-Weighted-Multi-Criteria Decision-Making (E-MCDM) Approach for Erosion Area Prioritization: Case Study of a Himalayan River Basin. Chapter 11. Role of Urea Super Granule (USG) Applicator in Efficient Management of Nitrogen Fertilizer: Case Study of Rice Farming in Bangladesh. Chapter 12. AI as Improved Agri-Tech Approach for Better Nutrients and Proper Irrigation Water Management: A Comparative Study. Chapter 13. Plasma Technology: An Emerging Tool for Sustainable Agriculture. Chapter 14. Application of Metaheuristic Optimizations for Unconfined Aquifer Parameter Estimation to Improve Irrigation Water Management. Chapter 15. Application of Remote Sensing, GIS, and AI Techniques in the Agricultural Sector. Chapter 16. Flood Modeling Using the AHP Method in a GIS Environment of the Iril River Catchment, Manipur, India. Chapter 17. Agricultural Drought Modelling Through Drought Indices in the Thoubal District, Manipur, India. Chapter 18. Seed Priming: Potential Nutrient Management Tool for Improving Crop Productivity Under Abiotic Stress. Chapter 19. Protected Cultivation: Microclimate-Based Agriculture Under Greenhouse. Chapter 20. Estimation of Groundwater Fluctuation and NDVI Using Geospatial Techniques for Chandigarh City, India. Chapter 21. Holistic Approach for Prediction of Total Nitrogen Based on Machine-Learning Techniques. Chapter 22. Resource Conservation Technologies for Sustainable Management of Soil, Water and Energy in Modern Agriculture.
Chapter 1. AI for Sustainable Agriculture in the Face of Climate Change. Chapter 2. Development of a Modeling Approach for Agriculture Crop Type Classification Aiming at Large-Scale Precision Agriculture by Synergistic Utilization of Fused Sentinel-1 and Sentinel-2 Datasets with UAV Datasets. Chapter 3. IoT and Smart Sensor Applications in Nutrient and Irrigation Water Management. Chapter 4. Assessing Nutrient Variability Across Irrigation Management Zones Using Unsupervised Learning and Mixed Models. Chapter 5. Comparative Study on Estimation of Sediment Yield Index Using GIS and Remote Sensing for Soil Erosion Prediction. Chapter 6. Soil Moisture Flows Modeling for Micro-Irrigation and Nutrient Load Management. Chapter 7. Applications of Remote Sensing and GIS Techniques in the Monitoring of Ecosystem Services. Chapter 8. Evaluation of Machine Learning Algorithms in Soil Water Content Prediction at Multiple Depths. Chapter 9. Artificial Intelligence Application in Database Management for SCADA Systems. Chapter 10. Entropy-Weighted-Multi-Criteria Decision-Making (E-MCDM) Approach for Erosion Area Prioritization: Case Study of a Himalayan River Basin. Chapter 11. Role of Urea Super Granule (USG) Applicator in Efficient Management of Nitrogen Fertilizer: Case Study of Rice Farming in Bangladesh. Chapter 12. AI as Improved Agri-Tech Approach for Better Nutrients and Proper Irrigation Water Management: A Comparative Study. Chapter 13. Plasma Technology: An Emerging Tool for Sustainable Agriculture. Chapter 14. Application of Metaheuristic Optimizations for Unconfined Aquifer Parameter Estimation to Improve Irrigation Water Management. Chapter 15. Application of Remote Sensing, GIS, and AI Techniques in the Agricultural Sector. Chapter 16. Flood Modeling Using the AHP Method in a GIS Environment of the Iril River Catchment, Manipur, India. Chapter 17. Agricultural Drought Modelling Through Drought Indices in the Thoubal District, Manipur, India. Chapter 18. Seed Priming: Potential Nutrient Management Tool for Improving Crop Productivity Under Abiotic Stress. Chapter 19. Protected Cultivation: Microclimate-Based Agriculture Under Greenhouse. Chapter 20. Estimation of Groundwater Fluctuation and NDVI Using Geospatial Techniques for Chandigarh City, India. Chapter 21. Holistic Approach for Prediction of Total Nitrogen Based on Machine-Learning Techniques. Chapter 22. Resource Conservation Technologies for Sustainable Management of Soil, Water and Energy in Modern Agriculture.
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