Editorial Board Member
Dr. R. N. Singh
Institutional email ID: ram.singh28@icar.org.in
Scientist, ICAR – National Institute of Abiotic Stress Management,
Baramati, Pune - 413 115
Editorial Board Member
Dr. R. N. Singh
Institutional email ID: ram.singh28@icar.org.in
Scientist, ICAR – National Institute of Abiotic Stress Management,
Baramati, Pune - 413 115
Dr. Ram Narayan Singh is a Scientist (Agricultural Meteorology) at the ICAR–National Institute of Abiotic Stress Management (NIASM), Baramati, Pune, India. His research integrates Earth observation data, satellite-based remote sensing, and advanced geospatial analytics to address challenges in climate variability, crop stress monitoring, and sustainable agri-environmental systems. He received his Ph.D. in Agricultural Physics from the ICAR – Indian Agricultural Research Institute (IARI), New Delhi, where he was awarded the IARI Merit (Gold) Medal and multiple national best doctoral thesis awards. He also secured All India Rank 1 in the Agricultural Research Service (ARS) in Agricultural Meteorology. His academic training includes an M.Sc. in Agricultural Physics from IARI and a B.Sc. in Agriculture from Banaras Hindu University. Dr. Singh’s expertise spans satellite remote sensing, thermal and optical imaging, digital image processing, GIS, and machine learning for crop yield prediction, plant disease and abiotic stress detection, and land - atmosphere interaction studies. He has extensively worked with long-term climate datasets, remote sensing derived vegetation indices, and Earth system indicators to quantify climate trends, extremes, and teleconnections with direct implications for food security and environmental resilience. His research record is distinguished by award-winning master’s and doctoral research, multiple national-level academic honors, and a strong portfolio of peer-reviewed publications and scholarly book chapters. He has led and contributed to several interdisciplinary projects integrating remote sensing products, long-term climate data, and advanced statistical and machine learning frameworks, addressing climate services, environmental monitoring, and sustainable resource management. His work is recognized for advancing the application of space-based Earth observation and analytical tools to inform climate adaptation strategies, enhance agricultural productivity, and support data driven decision making in complex agro-environmental systems.