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Mapping the Greenscape and Environmental Equity in Montreal: An Application of Remote Sensing and GIS

  • Thi-Thanh-Hiên Pham
  • Philippe Apparicio
  • Anne-Marie Séguin
  • Martin Gagnon
Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Vegetation and green spaces provide multiple benefits for urban life but they are not always evenly distributed throughout cities. Recent studies have shown that deprived and ethnic populations have less access to vegetation, which is a form of environmental inequity. The goal of this study is to map the vegetation cover and to spatially depict the problematic areas in terms of environmental inequity in Montreal. We carry out an object-oriented classification in eCognition from Quickbird images (at a resolution of 60cm) to identify two categories of vegetation: trees/shrub and grass. We then compute 12 vegetation indicators representing the proportion of vegetation, trees/shrub and grass in streets, alleys and residential yards. Finally, statistical analyses are undertaken to reveal the link between the vegetation indicators and the proportion of immigrants, visible minorities and low income individuals. Our results show that the proportion of vegetation varies significantly across the boroughs. About 30% of the areas exhibiting an elevated proportion of the three groups are identified as very high inequity whereas 10 to 14% are identified as areas with high green benefits. Environmental inequity with respect to the three populations also expresses differently depending on the type of green spaces (street and alleys for immigrants and visible minorities while all the three types of green spaces for the low income population). This study may interest city planners and local governments as the findings could better inform decisions regarding greening programs.

Keywords

Remote Sensing Green Space Geographically Weighted Regression Dissemination Area Visible Minority 
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-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Thi-Thanh-Hiên Pham
    • 1
  • Philippe Apparicio
    • 1
  • Anne-Marie Séguin
    • 1
  • Martin Gagnon
    • 1
    • 2
  1. 1.Institut national de la recherche scientifique - Urbanisation Culture SociétéMontréalCanada
  2. 2.Institut d’urbanismeUniversité de MontréalMontréalCanada

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