Spectral unmixing analysis of urban land cover fractions from landsat data

N. T. Son, C. F. Chen, C. R. Chen, L. Y. Chang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Geographic information of urban land-cover types is important for urban planning. This study explored the use of Landsat ETM imagery for mapping urban land-cover types in Ho Chi Minh City (HCMC) in 2010. Spectral unmixing model estimates abundance fractions of surface targets at sub-pixel level was used for urban-land cover mapping. This model was trained using endmembers extracted from the original image using minimum noise fraction (MNF) method. The mapping results was assessed using ground-verification data. The comparison results between classification map and ground-truth data revealed the overall accuracy of 89.6% and Kappa coefficient of 0.86. The results achieved from this study could be useful to assist local authorities in urban planning.

Original languageEnglish
Title of host publication32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Pages1654-1658
Number of pages5
StatePublished - 2011
Event32nd Asian Conference on Remote Sensing 2011, ACRS 2011 - Tapei, Taiwan
Duration: 3 Oct 20117 Oct 2011

Publication series

Name32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Volume3

Conference

Conference32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Country/TerritoryTaiwan
CityTapei
Period3/10/117/10/11

Keywords

  • Land cover
  • Landsat
  • Spectral unmixing analysis

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