Dr. Jyoti-Sharma-Remote Sensing-Best Researcher Award
India Meteorological Department-India
Author Profile
Early Academic Pursuits
Dr. Jyoti Sharma's academic journey commenced with a Bachelor of Science degree in Physics, Mathematics, and Chemistry from M. J. P. Rohilkhand University, Bareilly, followed by a Master's in Physics from the same institution. Her academic pursuits culminated in a Ph.D. in Remote Sensing from the Department of Physics, Indian Institute of Technology, BHU, Varanasi. During her doctoral research, Sharma delved into the retrieval of soil moisture and biophysical parameters using microwave spaceborne observations, showcasing her early interest in remote sensing applications for environmental studies.
Professional Endeavors
Dr. Jyoti Sharma's professional trajectory underscores her commitment to advancing remote sensing techniques for environmental monitoring. She commenced her post-doctoral journey as a Research Associate at the Hydrology Process Group, National Centre for Earth Science Studies, Thiruvananthapuram, Kerala. Following this, she assumed the role of Project Scientist at the India Meteorological Department, New Delhi. These roles provided her with diverse opportunities to apply her expertise in satellite data processing, radar data processing, and image analysis techniques.
Contributions and Research Focus
Dr. Jyoti Sharma's research contributions span various domains within remote sensing and geoscience. Her work encompasses the refinement of algorithms for soil moisture retrieval, improvement of spatial representation of soil moisture data, and the estimation of biophysical parameters using radar and satellite data. Notably, her research has been published in prestigious journals such as Remote Sensing of Environment and IEEE Transactions on Geoscience and Remote Sensing, showcasing the significance of her contributions to the scientific community.
Accolades and Recognition
Sharma's dedication to her research endeavors has garnered recognition from the academic community. She was awarded the Best Poster Award at the International Soil Moisture School (ISMS) by the IEEE-GRSS society in 2023. Additionally, her qualification as a CSIR-NET JRF in Physical Science further underscores her academic prowess and recognition within her field.
Impact and Influence
Dr. Jyoti Sharma's research outputs and participation in academic conferences have contributed significantly to the advancement of remote sensing techniques for environmental monitoring. Her investigations into soil moisture retrieval algorithms and biophysical parameter estimation have implications for agriculture, hydrology, and climate studies. Moreover, her collaborations with national and international research institutions underscore her role in fostering interdisciplinary research partnerships for addressing complex environmental challenges.
Jyoti Sharma's exemplary dedication to advancing remote sensing techniques has earned her the prestigious Remote Sensing Award.
Legacy and Future Contributions
As Dr. Jyoti Sharma continues to evolve professionally, her legacy lies in her contributions to the refinement of remote sensing methodologies for environmental monitoring and assessment. Her interdisciplinary approach and expertise in satellite data processing equip her to address emerging challenges in climate change, land use dynamics, and water resource management. Looking ahead, Sharma's future contributions are poised to further enrich our understanding of Earth's systems and support evidence-based decision-making for sustainable development.
In summary, Jyoti Sharma's academic journey, professional endeavors, research focus, accolades, and future contributions collectively underscore her significant impact on the field of remote sensing and geoscience. Her commitment to excellence and interdisciplinary collaboration positions her as a leading figure in the domain of environmental monitoring and assessment.
Citations
- Citations 109
- h-index 6
- i10-index 3
Notable Publication
- Incorporation of first-order backscattered power in Water Cloud Model for improving the Leaf Area Index and Soil Moisture retrieval using dual-polarized Sentinel-1 SAR data
- Evaluation of Simulated AVIRIS-NG Imagery Using a Spectral Reconstruction Method for the Retrieval of Leaf Chlorophyll Content
- Far-field bistatic scattering simulation for rice crop biophysical parameters retrieval using modified radiative transfer model at X- and C-band
- Synergy of dual–polarimetric radar vegetation descriptor and Gaussian processes regression algorithm for estimation of leaf area index
- Time-series polarimetric bistatic scattering decomposition using comprehensive modified first-order radiative transfer model at C-band for vegetative terrain and validation