Agricultural Insights from Space
Machine Learning Applications in Satellite Data Analysis
- 1st Edition - October 1, 2025
- Imprint: Academic Press
- Editors: Dharmendra Singh, Kuldeep Chaurasia, Ghazaala Yasmin
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 4 1 1 3 - 7
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 4 1 1 4 - 4
Agricultural Insights from Space: Machine Learning Applications in Satellite Data Analysis seamlessly integrates theoretical knowledge with practical applications, presen… Read more
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Agricultural Insights from Space: Machine Learning Applications in Satellite Data Analysis seamlessly integrates theoretical knowledge with practical applications, presenting cutting-edge research alongside real-world examples. This book leverages geospatial technology and Artificial Intelligence to address various challenges in agriculture. Readers will find practical examples and case studies demonstrating how machine learning and deep learning techniques can extract valuable insights from remote sensing data, optimizing agricultural processes. Highlighting the significance of satellite data, the book explores the benefits of leveraging space-based information for enhancing agricultural practices.
The book emphasizes the importance of geospatial intelligence and AI technologies in monitoring and managing agricultural activities. It inspires readers to envision a future where these innovative approaches lead to more productive agricultural environments and healthier growth for future generations.
The book emphasizes the importance of geospatial intelligence and AI technologies in monitoring and managing agricultural activities. It inspires readers to envision a future where these innovative approaches lead to more productive agricultural environments and healthier growth for future generations.
- Addresses applications, potential limitations, and challenges in implementing AI-based solutions for agriculture
- Presents a balanced perspective on the benefits associated with AI and geospatial technology
- Emphasizes the importance of responsible and transparent Geo-AI development to ensure equitable and sustainable outcomes
- Uses an interdisciplinary approach to bridge the gap between AI and agriculture science
- Offers practical insights and guidance on leveraging AI to create intelligent, smart, and more sustainable environment for agricultural activities
Professionals, researchers, and experts directly involved in the field of artificial intelligence, Geospatial intelligence, Agricultural scientists, AI researchers and practitioners working on developing machine learning-based solutions for precision agriculture, scientists and engineers interested in leveraging AI techniques to address agricultural growth, productivity, planning and management
1. Overview to Geospatial Technology and Machine Learning in Agriculture
2. Spatial Data Acquisition Methods for Agricultural Monitoring
3. Machine Learning techniques for Crop Identification and Classification
4. Predictive Modeling and analysis of Crop Yield and Productivity
5. Integration of Geospatial Technology and Machine Learning for Precision Agriculture
6. Crop Health Monitoring using Geospatial methods and Deep Learning
7. Integrating Climate Data for Agricultural Resilience using Geospatial approaches
8. Soil Mapping and categorisation using fusion of Satellite Imagery and Machine Learning
9. Geo- AI for Irrigation Management Systems in a smart way
10. Geospatial based mapping and monitoring of Pest and Disease Outbreaks utilising Machine Learning
11. Amalgamation of Geospatial Technology and machine learning for Livestock Management
12. Machine learning and Geospatial technology for Mapping of Agroforestry Systems
13. Geospatial and machine learning based mapping and analysis for Agricultural Sustainability
14. Deep Learning and Geospatial technology-based Decision support systems for smart Agricultural and irrigation applications
15. Case Studies, Best Practices, implementation challenges and opportunities in the adoption of Geospatial Technology and Machine Learning approaches in agricultural domain
2. Spatial Data Acquisition Methods for Agricultural Monitoring
3. Machine Learning techniques for Crop Identification and Classification
4. Predictive Modeling and analysis of Crop Yield and Productivity
5. Integration of Geospatial Technology and Machine Learning for Precision Agriculture
6. Crop Health Monitoring using Geospatial methods and Deep Learning
7. Integrating Climate Data for Agricultural Resilience using Geospatial approaches
8. Soil Mapping and categorisation using fusion of Satellite Imagery and Machine Learning
9. Geo- AI for Irrigation Management Systems in a smart way
10. Geospatial based mapping and monitoring of Pest and Disease Outbreaks utilising Machine Learning
11. Amalgamation of Geospatial Technology and machine learning for Livestock Management
12. Machine learning and Geospatial technology for Mapping of Agroforestry Systems
13. Geospatial and machine learning based mapping and analysis for Agricultural Sustainability
14. Deep Learning and Geospatial technology-based Decision support systems for smart Agricultural and irrigation applications
15. Case Studies, Best Practices, implementation challenges and opportunities in the adoption of Geospatial Technology and Machine Learning approaches in agricultural domain
- Edition: 1
- Published: October 1, 2025
- Imprint: Academic Press
- Language: English
DS
Dharmendra Singh
Dharmendra Singh is Senior Professor in Electronics and Communication Engineering Department, Indian Institute of Technology Roorkee, Roorkee, India and a Senior Member of IEEE with more than 27 years of experience of teaching and research. He has received many international awards and recognition, as well as the best innovation award in India Mobile Congress for the development of Satellite Based Agriculture Information System, and the best Industrial Research award by Institution of Engineers, Roorkee Chapter. He has twice received the National GOLD Award for e-governance for Outstanding research on Citizen Centric Services and has ranked among the top 2% scientists of the world in the field of Electronics and Telecommunication, by independent study done by Stanford University.
He has published extensively and developed several products including those releated to Technology for Stealth Material, Agriculture Information System, Through the wall imaging system, ground penetrating radar, Radomes, etc. His main research interests involve microwave/mm wave imaging and numerical modeling, radar absorbing materials, stealth application, Artificial Intelligence, Computer Vision, Deep Learning, Machine Learning, Data Fusion, ICT, Satellite data application, polarimetric and interferometric application of microwave data. He is also the Coordinator of DRONE RESEARCH CENTER, IIT Roorkee.
Affiliations and expertise
Senior Professor in Electronics and Communication Engineering Department, Indian Institute of Technology, Roorkee, IndiaKC
Kuldeep Chaurasia
Dr. Kuldeep is currently working as Associate Professor in the School of Computer Science Engineering and Technology, Bennett University, India. Dr. Kuldeep is a highly accomplished scholar, having earned his doctoral degree in Geomatics from the prestigious Indian Institute of Technology Roorkee, India. He has also made significant contributions as a research scientist in the implementation of national projects, working with Regional Centre, National Remote Sensing Centre, ISRO, Dept. of space, Hyderabad, India. Dr. Kuldeep's expertise lies in the application of Machine learning and Deep learning in geospatial domain, LULC mapping, flood mapping and modelling, Spatial Data Management, Computer Networks and Geo-Blockchain. He has published many research papers in reputed international journals/conferences. His passion for these areas of research has led to many breakthroughs in the field, making him a highly respected and sought-after expert in the academic community.
Affiliations and expertise
Associate Professor, School of Computer Science Engineering and Technology, Bennett University, IndiaGY
Ghazaala Yasmin
Dr. Ghazaala Yasmin is an Assistant Professor (Senior Grade) in the Dept. of CSE & IT at Jaypee Institute of Information Technology (JIIT). She has also worked as Assistant Professor in the Department of Computer Science Engineering at St. Thomas’ College of Engineering and Technology, Kolkata. She has 8 years of teaching and research experience. She received her Ph.D. degree from Indian Institute of Engineering Science and Technology (IIEST), Shibpur at Department of Computer Science and Technology, West Bengal. She did her M.Tech from Calcutta University in Computer Science and Engineering. Her research interests are Computer Vision, audio and video processing Medical Imaging, Agricultura data analysis, Machine and Deep Learning, Data Mining, NLP. She has published several reputed SCI journals and IEEE transaction and also published in reputative International Conference papers in analysis field. She has organized SERB funded workshop and international conferences like CIPR.
Affiliations and expertise
Assistant Professor (Senior Grade), Department of CSE & IT, Jaypee Institute of Information Technology (JIIT), India