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  • 标题:Development of digital spectral library and classification of rice crop using compressed ASTER L1 B satellite data
  • 本地全文:下载
  • 作者:Shwetank¹ ; Kamal Jain² ; Karamjit Bhatia³
  • 期刊名称:Oriental Journal of Computer Science and Technology
  • 印刷版ISSN:0974-6471
  • 出版年度:2010
  • 卷号:3
  • 期号:1
  • 页码:13-20
  • 出版社:Oriental Scientific Publishing Company
  • 摘要:In the present study Multispectral Image Processing (MIP) technique is applied on ASTER(Advance Spaceborne Thermal Emission and Reflection Radiometer) L1 B high resolution (15 m/pixel) satellite data. A comprehensive spectral library of rice crop varieties : Hybrid-6129 (IET 18815),Pant Dhan-19 (IET 17544), Pusa Basmati-1 (IET-18990) and Pant Dhan-18 (IET-17920) has beendeveloped with Blue (0.56 nm), Red (0.66 nm) and NIR (0.81 nm) spectral bands. The PCA (PrincipalComponent Analysis) transformation with correlation matrix is applied for feature extraction to selectan optimum subset of data in term of classification accuracy. Four PC (Principal Component) imagesselected for conventional spectral and integrated image classification. The integrated image Spectral/NDVI (Normalized Difference Vegetation Index) is developed using Spectral and NDVI bands classifiedusing ML (Maximum Likelihood) classifier. The conventional spectral classification accuracy for ricemapping is 79.5%, which improves up to 84.5% with Spectra/NDVI imagery data
  • 关键词:Multispectral Image Processing (MIP); NDVI; PCA and ML (Maximum Likelihood).
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