Rate My Professor Somdatta Chakravortty

Dr. Chakravortty's research specializations encompass hyperspectral image processing, nonlinear spectral unmixing, remote sensing applications for environmental monitoring, fractal analysis, and subpixel mapping techniques. Notable publications include 'A Technique for Subpixel Analysis of Dynamic Mangrove Ecosystem Using Hyperspectral Data' published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2018), 'Deep Autoencoder Networks for Hyperspectral Unmixing' in IEEE Transactions on Geoscience and Remote Sensing (2019), 'Change Prediction and Modeling of Dynamic Mangrove Ecosystem Using Remotely Sensed Data' in Journal of Applied Remote Sensing (2021), and 'Assessment of Urbanization of an Area with Hyperspectral Remote Sensing Data' (2015). She authored the book 'Non-Linear Spectral Unmixing of Hyperspectral Data' in 2024. Dr. Chakravortty has coordinated international webinars, including one on geo-informatics during the COVID-19 pandemic, and contributed to DST-funded projects. Her scholarly output demonstrates significant impact in advancing image analysis methods for geospatial and ecological studies, with collaborations involving international researchers.