首页    期刊浏览 2024年09月19日 星期四
登录注册

文章基本信息

  • 标题:Assessment of the multiple endmember spectral mixture analysis (mesma) model applied to the HYPERION/EO-1 hyperspectral data of the coastal plain of Rio Grande do Sul, Brazil
  • 本地全文:下载
  • 作者:Rodrigo M. Linn ; Silvia Beatriz Alves Rolim ; Lênio Soares Galvão
  • 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:2010
  • 卷号:XXXVIII - Part 7A
  • 页码:134-138
  • 出版社:Copernicus Publications
  • 摘要:The objective of this work was to evaluate the potential use of the Multiple Endmember Spectral Mixture Analysis (MESMA) when applied to EO - 1 Hyperion hyperspectral data to discriminate land covers in the southern state of Rio Grande do Sul, Brazil. The methodology involved: (a) pre - processing and atmospheric corr ection of Hyperion data; (b) sequential use of the Minimum Noise Fraction (MNF), P ixel Purity Index (PP I) and n - Dimensional Visualizer techniques in the 454 - 2334 nm range for the initial selection of a general group of endmember candidates (first spectral library) and of another group of pixels to be used for model validation; (c) use of the Visualization and Image Processing for Environmental Rese arch Tools (VIPER Tools) to perform the final selection of endmembers based on the first spectral library and to obtain MESMA models; and (d) evaluation of resultant fraction images and root mean square error (RMSE) values to determine the optimal number of components of the MESMA model. Results showed that a four - endmember MESMA model (soil = dunes and dry fields; green vegetation = pinus, eucalyptus and grasslands; water = w ithout sediments, with sediments, and with chlorophyll; and shade) adequately described the diversity of the scene components, including that of materials within the same class (e.g., pinus and eucalyptus) and produced the largest fractions and the lowest RMSE values on a per - pixel basis. Results demonstrated the potential use of the MESMA with EO - 1 Hyperion hyperspectral data to discriminate land covers in the coastal plains of Rio Grande do Sul, even considering the low signal - to - noise rati o of the instrument, especially in the shortwave infrared range
  • 关键词:Land Cover;Radiometry;Classification;Processing;Pattern;Hyper spectral
国家哲学社会科学文献中心版权所有