0000-0001-6430-3842 About
Dr Sahoo has many multidisciplinary and multi-institutional collaborative national and international research projects on remote sensing research programs as PI or Co-PI with total funding of INR 105 crores over last 19 years. His major accomplishments in applications of remote sensing and GIS in agriculture includes monitoring biotic and abiotic stresses for assessing crop conditions, Remote Sensing based drought monitoring and early warning, quantitative assessment of soil attributes for fertility and quality assessment and modeling for site specific nutrient requirement, precision agriculture, image and spectral based high throughput plant phenotyping, targeting resource conserving technologies and technologies to reduce agricultural fallow lands through biophysical monitoring and identifying production constraints of marginal lands, land use cover change modelling.
His major research interest is Hyperspectral Remote Sensing for soil and crop health monitoring for precision farming and plant phenomics, UAV remote sensing
Employment
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Indian Agricultural Research Institute Principal Scientist2000 - Present
Education
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Indian Agricultural Research Institute Ph.D.1996 - 2000
Projects & Funding
Projects & funding information is unavailable.
Publications (7)
- A high-resolution remote sensing-based composite index for monitoring agricultural drought in India Save
- Early detection of rice blast disease using hyperspectral remote sensing Save
- Scaling-up plant chlorophyll retrieval from proximal to UAV-borne hyperspectral data using a Gaussian process hybrid model Save
- Detecting Brown Planthopper, Nilaparvata lugens (Stål) Damage in Rice Using Hyperspectral Remote Sensing Save
- Leaf Count Aided Novel Framework for Rice (Oryza sativa L.) Genotypes Discrimination in Phenomics: Leveraging Computer Vision and Deep Learning Applications Save
- Application of thermal imaging and hyperspectral remote sensing for crop water deficit stress monitoring Save
- Evaluation of different water absorption bands, indices and multivariate models for water-deficit stress monitoring in rice using visible-near infrared spectroscopy Save