Detection and Analysis of Crop Stresses in Precision Agriculture Using Sentinel-2 Images
The ability to identify and monitor plant reactions to stress remotely has become a very challenging task for precision agriculture. Amongst the key factors in improving productivity of agriculture, one is, the identification of crop stresses. Therefore, relying just on visual inspection may lead to an inaccurate diagnosis, which would ultimately prevent the damaged plants from receiving corrective measures. Crop Stress can be abiotic like drought, flood, and salinity, while biotic stress includes weeds, other wild plants, and pests. In this paper, a focus has been laid to identify various causes of crop stress in the area located near the district of Gonda, situated in Uttar Pradesh state, India. For this purpose, Sentinel-2 images have been utilized to obtain the various vegetation indices such as NDVI, NDWI, GNDVI, PSSR, and Aphid Index, which are the most common to extract abiotic and biotic stress in crops.
Authors
- Gausiya Yasmeen (ORCID: https://orcid.org/0000-0002-7853-1376)
- Ajay Kumar Maurya (ORCID: https://orcid.org/0000-0002-1343-3257)
- Tasneem Ahmed
Institutions
- National Institute of Technology Patna (IN)
- Integral University (IN)
Publication Details
- Published
- 2024-12-02
- DOI
- https://doi.org/10.1109/ingarss61818.2024.10984001
- Citations
- 1
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.60