Abstract
This paper outlines the research objectives to investigate the approaches for assessment of vegetation water contents using hyperspectral remote sensing and moisture sensor. Water contents of crops monitor crop health for precision farming and monitoring. In the present research, spectral indices with some chemical extraction procedures were identified for estimation of water contents of crops. The investigated crop species, namely Vigna Radiata, Vigna Mungo, Pearl Millet, and Sorghum were collected from Aurangabad region of Maharashtra, India. Spectral reflectance curve of crop growth patterns was measured using ASD field Spec 4 Spectroradiometer and 150 Soil moisture sensor including healthy, diseased, and dry leaves with standard laboratory environment. It is found that there was a positive correlation between WI and Soil moisture sensor with 0.99, 0.76, and 0.97 accuracy. The research work was implemented using Python open source software. In the conclusion, water estimation from crops may be useful in irrigation mapping and drought risk modeling.
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Acknowledgements
Authors would like to acknowledge particularly for providing partial and technical support UGC SAP (II) DRS Phase-II, DST-FIST, and NISA to Department of Computer Science and IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India and also thank for financial assistance under UGC-BSR research fellowship for this work. The author would also like to acknowledge Department of Physics, for providing lab facility for use of soil moisture sensor Dr. B.A.M.U. Aurangabad.
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Surase, R.R. et al. (2019). Estimation of Water Contents from Vegetation Using Hyperspectral Indices. In: Panda, G., Satapathy, S., Biswal, B., Bansal, R. (eds) Microelectronics, Electromagnetics and Telecommunications. Lecture Notes in Electrical Engineering, vol 521. Springer, Singapore. https://doi.org/10.1007/978-981-13-1906-8_26
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DOI: https://doi.org/10.1007/978-981-13-1906-8_26
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