• Title of article

    Urban sprawl scatterplots for Urban Morphological Zones data

  • Author/Authors

    Altieri، نويسنده , , Linda and Cocchi، نويسنده , , Daniela and Pezzi، نويسنده , , Giovanna and Scott، نويسنده , , E. Marian and Ventrucci، نويسنده , , Massimo، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2014
  • Pages
    9
  • From page
    315
  • To page
    323
  • Abstract
    Urban sprawl is defined as an inefficient urban development often linked to sparse building density over rural areas. Routinely available remote sensing data on land cover are useful to study such phenomena, focus is on large raster maps of Urban Morphological Zones (UMZ) produced by the CORINE Land Cover programme of the European Environmental Agency. We present statistical indices to investigate changes in urban size and morphology between sub-regions within a predefined study area and show their implementation with raster data representing UMZ. Urban size is measured by urban land proportion, while morphology is quantified by Moranʹs I spatial correlation index. These two area-proportionately additive measures allow comparisons between urban size and morphology in sub-regions of different size to be performed. An urban sprawl scatterplot displaying Moranʹs I vs. urban land proportion is proposed as a tool to compare the urban sprawl level in pre-defined sub-regions with respect to a global average level. This scatterplot allows urban sprawled regions within a map to be identified and also an assessment of whether sprawl is due to augmented urban size or decreased urban compactness. An example of the methods is given for Bologna province, Northern Italy, where the interest is in detecting types of urban sprawl at several spatial scales, i.e. municipalities and unions of municipalities, within the whole province.
  • Keywords
    Urban sprawl , Moranיs I , CORINE land cover , Area-proportionately additive , Landscape metrics , fragmentation , Northern Italy
  • Journal title
    Ecological Indicators
  • Serial Year
    2014
  • Journal title
    Ecological Indicators
  • Record number

    2093414