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Temporal Crop Monitoring with Sentinel-1 SAR Data
Spatial and temporal analysis of crops and other land surface features is the major application of the present spaceborne sensors. Among most of the spaceborne sensors, synthetic aperture radar (SAR) is having the advantage of all-weather capability with low-frequency bands. SAR data is useful for decompositions, crop classifications, etc. In this study, paddy fields are classified using Sentinel-1 ground range detection. Synthetic aperture radar data with the combination of vertical polarization with the horizontal receiver (VV and VH) is selected for the temporal variation analysis and classification analysis of paddy fields along with the plantations. Multi-temporal classification analysis is done using random forest classifier, and correlation obtained is 0.78 and 0.45 in VH and VV polarization, respectively, and the error rate shows significant variation in both the polarizations, i.e., 0.05 and 0.25 (in VH and VV polarizations, respectively), which indicates more error rate in VV polarization band. In this study area, VH polarization shows better classification and correlation compared to VV polarization due to double bounce effect of urban features, paddy and plantation at the stem elongation and booting stage in VV polarization.
Temporal Crop Monitoring with Sentinel-1 SAR Data
Spatial and temporal analysis of crops and other land surface features is the major application of the present spaceborne sensors. Among most of the spaceborne sensors, synthetic aperture radar (SAR) is having the advantage of all-weather capability with low-frequency bands. SAR data is useful for decompositions, crop classifications, etc. In this study, paddy fields are classified using Sentinel-1 ground range detection. Synthetic aperture radar data with the combination of vertical polarization with the horizontal receiver (VV and VH) is selected for the temporal variation analysis and classification analysis of paddy fields along with the plantations. Multi-temporal classification analysis is done using random forest classifier, and correlation obtained is 0.78 and 0.45 in VH and VV polarization, respectively, and the error rate shows significant variation in both the polarizations, i.e., 0.05 and 0.25 (in VH and VV polarizations, respectively), which indicates more error rate in VV polarization band. In this study area, VH polarization shows better classification and correlation compared to VV polarization due to double bounce effect of urban features, paddy and plantation at the stem elongation and booting stage in VV polarization.
Temporal Crop Monitoring with Sentinel-1 SAR Data
Lecture Notes in Civil Engineering
Narasimhan, M. C. (editor) / George, Varghese (editor) / Udayakumar, G. (editor) / Kumar, Anil (editor) / Salma, Shaik (author) / Dodamani, B. M. (author)
2020-09-29
12 pages
Article/Chapter (Book)
Electronic Resource
English
Synthetic aperture radar (SAR) data , Multi-temporal analysis , Crop classification Engineering , Building Materials , Geoengineering, Foundations, Hydraulics , Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution , Transportation Technology and Traffic Engineering , Remote Sensing/Photogrammetry , Sustainable Development
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