• Title of article

    Quantification of impervious surface in the Snohomish Water Resources Inventory Area of Western Washington from 1972–2006

  • Author/Authors

    Powell، نويسنده , , Scott L. and Cohen، نويسنده , , Warren B. and Yang، نويسنده , , Zhiqiang and Pierce، نويسنده , , John D. and Alberti، نويسنده , , Marina، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2008
  • Pages
    14
  • From page
    1895
  • To page
    1908
  • Abstract
    A 34 year time series (1972–2006) of Landsat imagery for a portion of Snohomish and King Counties, Washington (the Snohomish Water Resource Inventory Area (WRIA)) was analyzed to estimate the amount of land that was converted into impervious surface as a result of urban and residential development. Spectral unmixing was used to determine the fractional composition of vegetation, open, and shadow for each pixel. Unsupervised and supervised classification techniques were then used to derive preliminary land cover maps for each time period. Digital orthophotos were used to create agricultural, forest management, high elevation, and riparian masks. In conjunction with established Urban Growth Areas (UGAs), these masks were utilized for the application of spatial rules that identified impervious surface as a surrogate for urban and residential development. Temporal rules, that minimized classification error, were developed based on each pixelʹs classified trajectory over the time series of imagery. Overall cross-date classification accuracy for impervious v. non-impervious surface was 95%. The results of the analysis indicate that the area of impervious surface in the Snohomish WRIA increased by 255% over 34 years, from 3285 ha in 1972 to 11,652 ha in 2006. This approach demonstrates the unique value of the 35 year Landsat archive for monitoring impervious surface trends in rapidly urbanizing areas.
  • Keywords
    Impervious Surface , Change detection , Urban sprawl , Washington State , Spectral unmixing , Landsat , multitemporal
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2008
  • Journal title
    Remote Sensing of Environment
  • Record number

    1575402