Mapping direct seeded rice in Raichur district of Karnataka, India
Across South Asia, the cost of rice cultivation has increased due to labor shortage. Direct seeding of rice is widely promoted in order to reduce labor demand during crop establishment stage, and to benefit poor farmers. To facilitate planning and to track farming practice changes, this study presen...
| Autores principales: | , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
American Society for Photogrammetry and Remote Sensing
2015
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/76712 |
| _version_ | 1855537765079318528 |
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| author | Gumma, Murali K. Uppala, D. Mohammed, I.A. Whitbread, Anthony M. Mohammed, I.R. |
| author_browse | Gumma, Murali K. Mohammed, I.A. Mohammed, I.R. Uppala, D. Whitbread, Anthony M. |
| author_facet | Gumma, Murali K. Uppala, D. Mohammed, I.A. Whitbread, Anthony M. Mohammed, I.R. |
| author_sort | Gumma, Murali K. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Across South Asia, the cost of rice cultivation has increased due to labor shortage. Direct seeding of rice is widely promoted in order to reduce labor demand during crop establishment stage, and to benefit poor farmers. To facilitate planning and to track farming practice changes, this study presents techniques to spatially distinguish between direct seeded and transplanted rice fields using multiple-sensor remote sensing imagery. The District of Raichur, a major region in northeast Karnataka, Central India, where irrigated rice is grown and direct seeded rice has been widely promoted since 2000, was selected as a case study. The extent of cropland was mapped using Landsat-8, Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day normalized difference vegetation index (NDVI) time-series data and the cultivation practice delineated using RISAT-1 data for the year 2014. Areas grown to rice were mapped based on the length of the growing period detected using spectral characteristics and intensive field observations. The high resolution imagery of Landsat-8 was useful to classify the rice growing areas. The accuracy of land-use/land-cover (LULC) classes varied from 84 percent to 98 percent. The results clearly demonstrated the usefulness of multiple-sensor imagery from MOD09Q1, Landsat-8, and RISAT-1 in mapping the rice area and practices accurately, routinely, and consistently. The low cost of imagery backed by ground survey, as demonstrated in this paper, can also be used across rice growing countries to identify different rice systems. |
| format | Journal Article |
| id | CGSpace76712 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | American Society for Photogrammetry and Remote Sensing |
| publisherStr | American Society for Photogrammetry and Remote Sensing |
| record_format | dspace |
| spelling | CGSpace767122024-05-01T08:19:21Z Mapping direct seeded rice in Raichur district of Karnataka, India Gumma, Murali K. Uppala, D. Mohammed, I.A. Whitbread, Anthony M. Mohammed, I.R. seed rice cultivation Across South Asia, the cost of rice cultivation has increased due to labor shortage. Direct seeding of rice is widely promoted in order to reduce labor demand during crop establishment stage, and to benefit poor farmers. To facilitate planning and to track farming practice changes, this study presents techniques to spatially distinguish between direct seeded and transplanted rice fields using multiple-sensor remote sensing imagery. The District of Raichur, a major region in northeast Karnataka, Central India, where irrigated rice is grown and direct seeded rice has been widely promoted since 2000, was selected as a case study. The extent of cropland was mapped using Landsat-8, Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day normalized difference vegetation index (NDVI) time-series data and the cultivation practice delineated using RISAT-1 data for the year 2014. Areas grown to rice were mapped based on the length of the growing period detected using spectral characteristics and intensive field observations. The high resolution imagery of Landsat-8 was useful to classify the rice growing areas. The accuracy of land-use/land-cover (LULC) classes varied from 84 percent to 98 percent. The results clearly demonstrated the usefulness of multiple-sensor imagery from MOD09Q1, Landsat-8, and RISAT-1 in mapping the rice area and practices accurately, routinely, and consistently. The low cost of imagery backed by ground survey, as demonstrated in this paper, can also be used across rice growing countries to identify different rice systems. 2015-11-01 2016-09-01T11:12:53Z 2016-09-01T11:12:53Z Journal Article https://hdl.handle.net/10568/76712 en Open Access American Society for Photogrammetry and Remote Sensing Gumma, M.K.; Uppala, D.; Mohammed, I.A.; Whitbread, A.M.; Mohammed, I.R. 2015. Mapping direct seeded rice in Raichur district of Karnataka, India. Photogrammetric Engineering and Remote Sensing 81 (11), 873-880. |
| spellingShingle | seed rice cultivation Gumma, Murali K. Uppala, D. Mohammed, I.A. Whitbread, Anthony M. Mohammed, I.R. Mapping direct seeded rice in Raichur district of Karnataka, India |
| title | Mapping direct seeded rice in Raichur district of Karnataka, India |
| title_full | Mapping direct seeded rice in Raichur district of Karnataka, India |
| title_fullStr | Mapping direct seeded rice in Raichur district of Karnataka, India |
| title_full_unstemmed | Mapping direct seeded rice in Raichur district of Karnataka, India |
| title_short | Mapping direct seeded rice in Raichur district of Karnataka, India |
| title_sort | mapping direct seeded rice in raichur district of karnataka india |
| topic | seed rice cultivation |
| url | https://hdl.handle.net/10568/76712 |
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