Global High Resolution Urban Data from LandsatFollow Us: Twitter Follow Us on Facebook YouTube Flickr | Share: Twitter Facebook
Urban Landsat: Cities from Space, v1 (
1999 – 2003)
Objectives of Urban Remote Sensing
Remote Sensing generally refers to the science, technology and physical processes involved in the detection, analysis and interpretation of information collected without coming into physical contact with the object of interest. In the context of our research and applications, urban remote sensing focuses primarily on understanding the physical properties and processes of urban environments and on the mapping and monitoring of urban land cover and spatial extent. These two objectives are related in the sense that it is necessary to understand the physical properties of the urban mosaic in order to rigorously define, map and monitor urban areas.
Characterizing the Physical Properties of the Urban Environment
The research presented here is primarily focused on the physical properties of a wide range of urban environments using passive measurement of optical reflectance and thermal emission as well as optical emission of nighttime lights. Comparative analyses of urban reflectance (visible and infrared color) and surface temperature allow us to develop robust criteria for distinguishing urban land cover from non-anthropogenic land covers. These analyses also provide important constraints on the physical properties that control mass and energy fluxes through the urban environment. These constraints are used as inputs to physical models of climatic, hydrologic and ecologic processes.
Mapping and Monitoring Urban Form and Growth
Characterizing the physical properties of urban land cover makes it possible to map the form and spatial extent of urban land use and to quantify changes in form and extent. This provides objective, physically-based metrics for comparative analyses of urban dynamics that cannot generally be obtained from administrative definitions of urban extent. Mapping provides static snapshots of the urban mosaic while monitoring allows us to quantify the spatiotemporal dynamics. Mapping urban extent with nightlights complements the information derived from optical reflectance.
Each city is linked to a jpeg image of a Landsat visible/IR composite collected by Landsat 5 (pre 1999) or Landsat 7. Most of the image areas are 30x30 km but a few are larger. All images are shown at full resolution (30 m pixel) so the scale (on screen) is equivalent. The jpeg compression causes significant loss of fine detail from the original image. Most of the images are about 200K. A few are significantly larger.
Research and Related Links
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 on the Lamont Doherty Earth Observatory (LDEO) Urban Remote Sensing 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.
- Small, C. 2005. A global analysis of urban reflectance. International Journal of Remote Sensing. 26 (4): pp. 661-681.
- Small, C. 2003. High spatial resolution spectral mixture analysis of urban reflectance. Remote Sensing of Environment. 88 (1-2): pp. 170-186.
- Small, C. and Lu. J. W.T. 2006. Estimation and vicarious validation of urban vegetation abundance by spectral mixture analysis. Remote Sensing of Environment. 100 (4): pp. 441-456.
- Small, C. 2001. Estimation of urban vegetation abundance by spectral mixture analysis. International Journal of Remote Sensing. 22 (7): pp. 1305-1334.
Urban Thermal Environment:
- Small, C. 2006. Comparative Analysis of Urban Reflectance and Surface Temperature. Remote Sensing of Environment. 104 (2), pp. 168-189.
Urban Night Lights:
- Small, C., Pozzi, F., and Elvidge, C. D. 2005. Spatial analysis of global urban extent from DMSP-OLS night lights. Remote Sensing of Environment. 96 (3-4): pp.277-291.
- Lamont Doherty Earth Observatory (LDEO) Urban Remote Sensing
- Urban Remote Sensing Publications
- Columbia University Remote Sensing Image Analysis Lab at LDEO
- NASA Landsat
- Landsat 7 Science Data Users Handbook
- Landsat 8 Data Users Handbook
- Global Rural Urban Mapping Project (GRUMP), v1
- CIESIN Thematic Guides, Social Science Applications of Remote Sensing