Evaluation of Radarsat-2 quad-pol SAR time-series images for monitoring groundwater irrigation
Groundwater assists farmers to irrigate crops for fulfilling the crop-water requirement. Indian agriculture system is characterized by three cropping seasons known as Kharif (monsoon), Rabi (post-monsoon) and summer (pre-monsoon). In tropical countries like India, monitoring cropping practices using...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2019-10-01
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| Series: | International Journal of Digital Earth |
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| Online Access: | http://dx.doi.org/10.1080/17538947.2019.1604834 |
| _version_ | 1827811192937119744 |
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| author | Amit Kumar Sharma Laurence Hubert-Moy Buvaneshwari Sriramulu M. Sekhar Laurent Ruiz S. Bandyopadhyay Shiv Mohan Samuel Corgne |
| author_facet | Amit Kumar Sharma Laurence Hubert-Moy Buvaneshwari Sriramulu M. Sekhar Laurent Ruiz S. Bandyopadhyay Shiv Mohan Samuel Corgne |
| author_sort | Amit Kumar Sharma |
| collection | DOAJ |
| description | Groundwater assists farmers to irrigate crops for fulfilling the crop-water requirement. Indian agriculture system is characterized by three cropping seasons known as Kharif (monsoon), Rabi (post-monsoon) and summer (pre-monsoon). In tropical countries like India, monitoring cropping practices using optical remote sensing during Kharif and Rabi seasons is constraint due to the cloud cover, which can be well addressed by microwave remote sensing. In the proposed research, the strength of C-band polarimetric Synthetic Aperture Radar (SAR) time series images were evaluated to classify groundwater irrigated croplands for the Kharif and Rabi cropping seasons of the year 2013. The present study was performed in the Berambadi experimental watershed of Kabini river basin, southern peninsular India. A total of fifteen polarimetric variables were estimated includes four backscattering coefficients (HH, HV, VH, VV) and eleven polarimetric indices for all Radarsat-2 SAR images. The cumulative temporal sum (seasonal and dual-season) of these parameters was supervised classified using Support Vector Machine (SVM) classifier with intensive ground observation samples. Classification results using the best equation (highest accuracy and kappa) shows that the Kharif, Rabi and irrigated double croplands are respectively 9.58 km2 (20.6%), 16.14 km2 (34.7%) and 6.22 km2 (13.4%) with a kappa coefficient respectively 0.84, 0.74 and 0.94. |
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| format | Article |
| id | doaj.art-9c50f3cb13f14ee4bc25c77ae9618b1f |
| institution | Directory Open Access Journal |
| issn | 1753-8947 1753-8955 |
| language | English |
| last_indexed | 2024-03-11T23:01:51Z |
| publishDate | 2019-10-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj.art-9c50f3cb13f14ee4bc25c77ae9618b1f2023-09-21T14:57:08ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552019-10-0112101177119710.1080/17538947.2019.16048341604834Evaluation of Radarsat-2 quad-pol SAR time-series images for monitoring groundwater irrigationAmit Kumar Sharma0Laurence Hubert-Moy1Buvaneshwari Sriramulu2M. Sekhar3Laurent Ruiz4S. Bandyopadhyay5Shiv Mohan6Samuel Corgne7Univ Rennes, UMR LETG CNRSUniv Rennes, UMR LETG CNRSIndian Institute of ScienceIndian Institute of ScienceUMR 1069 SAS, INRA, Agro-campus OuestEOS, Indian Space Research OrganizationPLANEX, Physical Research LaboratoryUniv Rennes, UMR LETG CNRSGroundwater assists farmers to irrigate crops for fulfilling the crop-water requirement. Indian agriculture system is characterized by three cropping seasons known as Kharif (monsoon), Rabi (post-monsoon) and summer (pre-monsoon). In tropical countries like India, monitoring cropping practices using optical remote sensing during Kharif and Rabi seasons is constraint due to the cloud cover, which can be well addressed by microwave remote sensing. In the proposed research, the strength of C-band polarimetric Synthetic Aperture Radar (SAR) time series images were evaluated to classify groundwater irrigated croplands for the Kharif and Rabi cropping seasons of the year 2013. The present study was performed in the Berambadi experimental watershed of Kabini river basin, southern peninsular India. A total of fifteen polarimetric variables were estimated includes four backscattering coefficients (HH, HV, VH, VV) and eleven polarimetric indices for all Radarsat-2 SAR images. The cumulative temporal sum (seasonal and dual-season) of these parameters was supervised classified using Support Vector Machine (SVM) classifier with intensive ground observation samples. Classification results using the best equation (highest accuracy and kappa) shows that the Kharif, Rabi and irrigated double croplands are respectively 9.58 km2 (20.6%), 16.14 km2 (34.7%) and 6.22 km2 (13.4%) with a kappa coefficient respectively 0.84, 0.74 and 0.94.http://dx.doi.org/10.1080/17538947.2019.1604834radarsat-2synthetic aperture radarpolarimetric indicesirrigated croplandsupport vector machine classifierkabini critical zone observatory |
| spellingShingle | Amit Kumar Sharma Laurence Hubert-Moy Buvaneshwari Sriramulu M. Sekhar Laurent Ruiz S. Bandyopadhyay Shiv Mohan Samuel Corgne Evaluation of Radarsat-2 quad-pol SAR time-series images for monitoring groundwater irrigation International Journal of Digital Earth radarsat-2 synthetic aperture radar polarimetric indices irrigated cropland support vector machine classifier kabini critical zone observatory |
| title | Evaluation of Radarsat-2 quad-pol SAR time-series images for monitoring groundwater irrigation |
| title_full | Evaluation of Radarsat-2 quad-pol SAR time-series images for monitoring groundwater irrigation |
| title_fullStr | Evaluation of Radarsat-2 quad-pol SAR time-series images for monitoring groundwater irrigation |
| title_full_unstemmed | Evaluation of Radarsat-2 quad-pol SAR time-series images for monitoring groundwater irrigation |
| title_short | Evaluation of Radarsat-2 quad-pol SAR time-series images for monitoring groundwater irrigation |
| title_sort | evaluation of radarsat 2 quad pol sar time series images for monitoring groundwater irrigation |
| topic | radarsat-2 synthetic aperture radar polarimetric indices irrigated cropland support vector machine classifier kabini critical zone observatory |
| url | http://dx.doi.org/10.1080/17538947.2019.1604834 |
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