Agricultural Insights from Space

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. 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.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.

• 1. Overview to Geospatial Technology and Machine Learning in Agriculture2. Spatial Data Acquisition Methods for Agricultural Monitoring3. Machine Learning techniques for Crop Identification and Classification4. Predictive Modeling and analysis of Crop Yield and Productivity5. Integration of Geospatial Technology and Machine Learning for Precision Agriculture6. Crop Health Monitoring using Geospatial methods and Deep Learning7. Integrating Climate Data for Agricultural Resilience using Geospatial approaches8. Soil Mapping and categorisation using fusion of Satellite Imagery and Machine Learning9. Geo- AI for Irrigation Management Systems in a smart way10. Geospatial based mapping and monitoring of Pest and Disease Outbreaks utilising Machine Learning11. Amalgamation of Geospatial Technology and machine learning for Livestock ManagementContributors: Parisha Bankhwal, Sugandha Panwar, Swati Uniyal12. Machine learning and Geospatial technology for Mapping of Agroforestry Systems13. Geospatial and machine learning based mapping and analysis for Agricultural Sustainability14. Deep Learning and Geospatial technology-based Decision support systems for smart Agricultural and irrigation applications15. A case study on Lagrange Polynomials and Machine Learning for Yield Prediction16. Leveraging Deep Learning Ensembles for Rice Disease Classification: A Case Study17. Optimizing Crop Classification with Machine Learning: Insights from a Case Study18. Synthetic Data Generation Using Microwave Modelling with Efficient Application of Machine Learning for Bare land Soil Moisture Retrieval- A case Study