Abstract
In India, the majority of the population relies heavily on rice as it is their primary source of nutrition. Rice crop yield productivity depends on seasonal variations and mainly depends on hydrological conditions. Long-term water clogging in rice fields for an extended period causes crop flooding and reduces production in terms of quality and quantity. This study deals with the identification of rice crop fields and their flooding due to surface irrigation using Sentinel-1 SAR data. The identification of rice fields was attempted by classifying the image data using a random forest algorithm. For crop flooding analysis, the temporal backscatter of the corresponding fields has been extracted from SAR data and local thresholding is used. The temporal analysis of the SAR backscattering showed a similar tendency in terms of crop growth. The overall accuracy of rice crop classification for VH and VV is 97.30% and 92.24% with RMSE errors of 0.0143 and 0.0145, respectively, obtained at the peak stage of the crop. From the crop flooding analysis, it is observed that crop fields have been flooded at the growth stage due to surface irrigation and rainfall. We identified crop flooding even at the crop mature stage. In the analysis, it has been observed that the flooding is not due to irrigation water but is due to the precipitation water.
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Authors wish to thank and acknowledge the ESA for providing freely Sentinel-1A SAR data and SNAP software with S-1TBX for the study.
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N, K., Salma, S. & Dodamani, B.M. Identifying Rice Crop Flooding Patterns Using Sentinel-1 SAR Data. J Indian Soc Remote Sens 50, 1569–1584 (2022). https://doi.org/10.1007/s12524-022-01553-4
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DOI: https://doi.org/10.1007/s12524-022-01553-4