Abstract
Paddy crop is one of the foremost food crops in the world. Human consumption accounts for 85% of total production of paddy. Paddy delivers 21% of human per capita energy and 15% of per capita protein. The present study focused on estimating the crop phenological parameters. The phenological parameters were estimated using soil moisture active passive (SMAP), MODIS NDVI, and SCATSAT-1 scatterometer data. The statistical models adopted in the study are two-parameter Gaussian distribution and two-parameter logistic distributions. The puddling stage is the first phenological stage, and it is estimated by the application of soil wetness index (SWI) and anomaly method. The transplanting stage is estimated using the anomaly method. The heading stages are estimated using statistical models, and it is found that Gaussian distribution is the best-fitted model. The harvesting stage is identified using SCATSAT-1 scatterometer and MODIS NDVI data. A chi-square test and degrees of freedom are used to identify the performance and comparison of statistical models. Chi-square test measure is equal to 80.561 and corresponding tabulated chi-square value with N-K-1 degrees of freedom that is equal to 117 is 151.929. The null hypothesis is not rejected.
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Acknowledgements
The work has been carryout under the Space Application Centre (SAC), ISRO R&D project entitled: “Enhanced Vegetation Monitoring Using RapidSCAT and SCATSAT-1 Scatterometer Data.” The authors are thankful to Space Application Centre for funding to this project and Vellore institute of technology (VIT), Vellore for providing facilities for smooth going of the project.
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Palakuru, M., Yarrakula, K., Chaube, N.R. et al. Identification of paddy crop phenological parameters using dual polarized SCATSAT-1 (ISRO, India) scatterometer data. Environ Sci Pollut Res 26, 1565–1575 (2019). https://doi.org/10.1007/s11356-018-3692-5
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DOI: https://doi.org/10.1007/s11356-018-3692-5