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  • 标题:Spatial Database Generation of the Rice-Cropping Pattern of India uing Satellite Remote Sensing Data
  • 本地全文:下载
  • 作者:K.R. Manjunath ; Sushma Panigrahy
  • 期刊名称:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
  • 印刷版ISSN:2194-9042
  • 电子版ISSN:2194-9050
  • 出版年度:2009
  • 卷号:XXXVIII-8/W3
  • 页码:262
  • 出版社:Copernicus Publications
  • 摘要:Rice is one of the key food grains linked to the food security of the growing population of the world. India has largest rice area in the world and stands second in production. The rice crop is important both from the food security and climate change point of view. The present paper highlights rice-growing pattern in India derived using satellite remote sensing and Geographic Information System. Multidate SPOT VGT 10-day composite normalised difference vegetation index data is used along with RADARSAT SAR and IRS WiFS data to map the rice area and generate seasonal rice cropping pattern and crop calendar. The spectral growth profiles of rice crop clusters were modeled to derive spatial patterns crop rice calendar. The results showed that there are two major rice cropping pattern; wet season and dry season. The wet season rice calendar varied significantly. The transplantation starts as early as mid April in Jammu. The transplantation in main land India starts from Punjab by end of May and progresses towards eastern states. Out of 43 Mha of total rice lands, wet season occupied 88.8 per cent. Comparatively, less variation of rice transplantation observed during dry season. The average crop duration of wet rice crop was more than dry season rice by 17 days. The prominent states growing dry season crop are West Bengal, Andhra Pradesh and Orissa. Rotation wise, rice- rice rotation accounted for 7.97 percent of the total rice area, mainly found in West Bengal, Andhra Pradesh, Tamilnadu and Orissa. West Bengal state has nearly 31.7 percent area under rice-rice rotations. This is the first time that a spatial data base of rice cropping pattern and crop calendar of India is generated, which will serve as baseline data for relevant simulation studies on climate change and green house gas emission
  • 关键词:Rice Cropping Pattern; Climate Change; Crop Calendar; Remote Sensing; Wet Season
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