• DocumentCode
    2705711
  • Title

    Identification for building surface material based on hyperspectral remote sensing

  • Author

    Zhu, Jun ; Zhou, Lifan ; Zhang, Dengrong

  • Author_Institution
    Inst. of Spatial Inf. Tech., Zhejiang Univ., Hangzhou, China
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In contrast with traditional remote sensing, hyperspectral remote sensing has the characteristics of high spectral resolution, combination of graph and spectrum, and large quantity of imaging bands. It has been used in many fields. According to the research results of other scholars, building surface has become a thermal active surface which has an important effect for forming city three-dimensional climate. In the 863 research project of relieving and analyzing of city heat island, based on summarizing now available spectrum identification methods, we selected frequently-used spectral angle match (SAM) identification method for the research, then we realized a program of identifying building surface material with IDL, and we did a simulation experiment for the program by using an AVIRIS image. Finally, we got a good result. It is proved that identifying building surface material based on hyperspectral remote sensing is feasible. So it makes a solid basis for further research.
  • Keywords
    building; civil engineering computing; geophysics computing; remote sensing; AVIRIS image; building surface material; city heat island; frequently-used spectral angle match identification method; high spectral resolution; hyperspectral remote sensing; spectrum identification; thermal active surface; Buildings; Cities and towns; Correlation; Hyperspectral imaging; Materials; Spectral Angle Match (SAM); building surface material; hyperspectral remote sensing; spectral identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics, 2011 19th International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2161-024X
  • Print_ISBN
    978-1-61284-849-5
  • Type

    conf

  • DOI
    10.1109/GeoInformatics.2011.5980687
  • Filename
    5980687