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  • 标题:SATELLITE REMOTE SENSING AND GIS TECHNOLOGIES TO AID SUSTAINABLE MANAGEMENT OF INDIAN IRRIGATION SYSTEMS
  • 本地全文:下载
  • 作者:S. M. Chintapalli ; P. V. Raju ; K. Abdul Hakeem
  • 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:2000
  • 卷号:XXXIII Part B7(/1-4)
  • 页码:264-271
  • 出版社:Copernicus Publications
  • 摘要:Increasing concern in recent years in India is on the issue of long-term prospects of irrigation and the consequences of continuing current water management practices on the sustainability of irrigation systems which have been created with huge financial investments. The selective studies mentioned in this paper describe the application of advanced technologies namely Remote Sensing and Geographic Information System, which has been demonstrated recently, in many irrigation systems in India to address the various issues relevant to sustainable management of irrigation systems. The primary agricultural information at disaggregated level derived from the analysis of high resolution satellite data has formed the basic input in all these studies. A set of indicators of agricultural situation over time and space were derived exclusively from satellite data analysis and validated at grass root level irrigation units in Bhakra irrigation system, Haryana state. Indicators of irrigation system performance such as irrigation intensity, principal crop intensity, equity in water distribution and agricultural production per unit volume of water were developed and applied in Bhadra command area, Karnataka state. Thus, the geo information derived from remote sensing and data analysis tools like GIS provide excellent opportunities to measure the spatio-temporal changes in land and water productivity and to achieve sustainable management of irrigation systems. The demonstrated capabilities would hopefully lead to more wide spread and operational use of these advanced technologies in India and elsewhere, in the world
  • 关键词:Remote sensing; Performance analysis; Sustainable; Multi spectral; Spatial data
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