NASA Socioeconomic Data and Applications Center (SEDAC) – Hosted by CIESIN at Columbia University

Urban Landsat

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Research

A primary objective of urban remote sensing is to develop physically consistent representations of the physical properties of the urban, suburban and periurban environments. In addition to enabling urban mapping and monitoring, a consistent physical classification of urban reflectance properties provides inputs for urban microclimate and air quality models. A consistent classification that represents the diversity of the urban mosaic provides a basis for quantitative comparison of urban morphology and satellite montioring of urban growth.

Spectral Mixture Analysis of urban reflectance at different spatial and spectral resolutions suggests that spectrally diverse urban areas can be described as combinations of spectral endmembers within a spectral mixing space. Further details are available at Lamont-Doherty's Urban Reflectance Website.

Comparative analyses of diverse urban environments at different spatial scales provide a basis for quantitative remote sensing of urban physical properties. Further details are available within the publications listed.

Publications

Urban Landsat:

  • Christopher Small. (2005). A global analysis of urban reflectance. International Journal of Remote Sensing. Volume 26, Number 4, pp. 661-681.

Urban Ikonos:

  • Christopher Small. (2003). High spatial resolution spectral mixture analysis of urban reflectance.Remote Sensing of Environment. Volume 88, Issues 1-2, pp. 170-186.

Urban Vegetation:

  • Christopher Small, Jacqueline W.T. Lu. (2006). Estimation and vicarious validation of urban vegetation abundance by spectral mixture analysis.Remote Sensing of Environment. Volume 100, Issue 4, pp. 441-456.
  • Christopher Small. (2001). Estimation of urban vegetation abundance by spectral mixture analysis.International Journal of Remote Sensing. Volume 22, Number 7, pp. 1305-1334.

Urban Thermal Environment:

  • Christopher Small. (2006). Comparative Analysis of Urban Reflectance and Surface Temperature.Remote Sensing of Environment. In press, corrected proof, available online 11 July 2006.

Urban Night Lights:

  • Christopher Small, Francesca Pozzi, C.D. Elvidge. (2005). Spatial analysis of global urban extent from DMSP-OLS night lights. Remote Sensing of Environment. Volume 96, Issues 3-4, 277-291.