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Quantifying and Qualifying Urban Green by Integrating Remote Sensing, GIS, and Social Science Method

  • Stefan Lang
  • Elisabeth Schöpfer
  • Daniel Hölbling
  • Thomas Blaschke
  • Matthias Moeller
  • Thomas Jekel
  • Elisabeth Kloyber
Part of the NATO Science for Peace and Security Series C: Environmental Security book series (NAPSC)

Sustainable urban planning in growing urban agglomerations encompasses the active development of urban green spaces. The loss of urban green not only threatens urban climate and ecosystems, but may also affect a city’s image and the residential satisfaction in general. Quantifiable information about green structures and the amount and distribution of green spaces is essential for sustainable planning. Monitoring tools for outlining differences in urban green space are required, which – more than merely measuring the overall percentage of green – may reflect the different importance of green areas in specific environments. This implies both spatial explicit characterizations of green areas and the consideration of relative importance of certain green structures from a citizen’s perspective. In this chapter we will present two approaches for advanced urban green mapping in the Phoenix Metropolitan Area, Arizona, USA (PHX-US), and Salzburg, Austria, Europe (SBG-AT). The approaches discussed were designed for monitoring urban green development in a repeatable and transferable manner by using (1) proxies derived from remotely sensed data, (2) spatial concepts and spatially explicit measures for spatial characterization, and (3) subjective, social science data reflecting the perception of urban green and therefore, the quality of some aspects of urban life and residential satisfaction.

Keywords: Urban green structures; monitoring; fraction of surrounding vegetation; weighted green index; environmental perception.

Keywords

Normalize Difference Vegetation Index Green Space Urban Green Space Residential Satisfaction Urban Green 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer 2008

Authors and Affiliations

  • Stefan Lang
    • 1
  • Elisabeth Schöpfer
    • 1
  • Daniel Hölbling
    • 1
  • Thomas Blaschke
    • 1
  • Matthias Moeller
    • 2
  • Thomas Jekel
    • 3
  • Elisabeth Kloyber
    • 4
  1. 1.Centre for Geoinformatics (Z_GIS)Salzburg UniversitySalzburgAustria
  2. 2.Global Institute of SustainabilityArizona State UniversityTempeUSA
  3. 3.GIScienceAustrian Academy of SciencesAustria
  4. 4.Institut für integrative Stadt- und Regionalentwicklung (IISR)Austria

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