About
Research Fellow of Vegetation Remote Sensing
Research
Research groups
Research interests
- Crop disease/stress detection; Hyperspectral, LiDAR Remote Sensing
- Dynamic Global Vegetation Model (DGVM) and Carbon Credits
- Climate smart precision agriculture and imapct of extream weather event on vegetation phenology
- Forest fire
- Artificial Intellegence (AI) Foundation Model (FM) and?Internet of Things (IoT)
Current research
Currently he is working on several projects: vegetation biophysical variables (FAPAR, LAI, Chlorophyll) estimation from satellite imagery; development of a framework for estimating FAPAR from automated wireless PAR networks; satellite (Sentinel-3, Proba-V, VIIRS, MODIS) land product validation; above ground biomass (AGB) estimation using Sentinel-2 and terrestrial laser scanner (TLS) observation to verify the woodland carbon code (WCC)'s existing protocol for carbon credits; crop classification and crop yield estimation using Sentinel-2 imagery and machine learning approaches; assessment of crop residue burning or the stubble burning for northern India.
Publications
Biography
Somnath Paramanik is a Postdoctoral Research Fellow at the School of Geography and Environmental Science, University of 天发娱乐棋牌_天发娱乐APP-官网|下载, completed Ph.D. at the esteemed Indian Institute of Technology Kharagpur (IIT Kgp). His research focuses on the application of Remote Sensing and GIS in Agriculture and Forestry, with a specific emphasis on the estimation of biophysical parameters such as Leaf Area Index (LAI) and Chlorophyll using a combination of satellite and ground observations. His academic journey includes a Master's degree in Earth System Science and Technology from IIT Kgp (2015-2017) and a Bachelor's degree in Agricultural Engineering from Bidhan Chandra Krishi Viswavidyalaya (2011-2015), India. He is passionate about advancing the understanding of Earth Observation and Geospatial Science and contribute a valuable insights to the fields of Environmental science and Sustainability.