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  • 标题:SPECTRAL VEGETATION INDICES AND ITS RESPONSE TO IN-SITU MEASURED LEAF AREA INDEX OF COTTON
  • 本地全文:下载
  • 作者:M.H. Kalubarme ; M. Yadav ; G.P. Saroha
  • 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:2006
  • 卷号:XXXVI Part 4
  • 出版社:Copernicus Publications
  • 摘要:The major objective of this study was to develop site-specific spectral vegetation index-LAI relationship for two cotton varieties cultivated in the Central State Farm (CSF) Hisar, using multi-date radiometric and LAI measurements as well as digital data of LISS- III onboard Indian Remote Sen sing Satellite (IRS). The field-level LAI was measured using LAI-2000 Plant Canopy Analyser and Aerosol optical thickness (AOT) and water vapour content were measured using hand-held Microtops-II Sunphotometer. The radiometric measurements were carried out using Ground Truth Rad iometer (GTR). The results of linear regression analysis indicated that among various SVIs, the NIR – SWIR based indices performed slightly better as compared to NIR - Red based indices. However, there was not much variation among different SVIs with relatively high R 2 in most cases. The relationship developed between LAI and NDVI of cotton varieties was used to predict LAI, which resulted in R 2 of 0.82, however most of the predicted LAI values were underestimated by 8.4 percent. This relationship was used to generate LAI map of cotton areas in the Hisar district. The results of exponential relationship between IRS LISS-III derived NDVI and yields in the farmer's fields resulted in R 2 of 0.73 and between LAI and cotton yields resulted in R 2 of 0.79. These results are encouraging in terms of their utility in retrieving LAI from IRS LISS-III derived NDVI and indirectly to estimate cotton yields at the regional scale using LAI and yield relationships
  • 关键词:Spectral Vegetation Indices (SVIs); Leaf Area Index (LAI); Canopy Analyzer; Crop Cutting Experiments; Short ; Wave Infrared Indices; Supervised Classification; LAI Retrieval
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