Satellite images of medium resolution are cheap, widely available and are often part of extensive historic archives,which makes them ideally suited to study urban growth. Their lower resolution, on the other hand, hampers studying urban morphology and change processes at a more detailed, intra-urban level. In this paper, we develop spatial metrics for use on continuous sealed surface data produced by a sub-pixel classification of Landsat TM and ETM+ imagery. Three approaches are compared to derive the sealed surface fractions at sub-pixel level: linear regression analysis, linear spectral mixture analysis and a multi-layer perceptron (MLP). The metrics represent the shape of the cumulative frequency distribution of the estimated sub-pixel fractions within each spatial unit by fitting a
transformed logistic function with a nonlinear least-squares approach. A MLP classifier is then used to relate the metric variables to combined urban land-use classes selected from the European MOLAND topology. In combination with density information derived from the sealed surface maps, our approach allows producing maps that show changes in urban morphology.
Original languageEnglish
Title of host publicationProceedings of the fifth international workshop on the analysis of multi-temporal remote sensing images - MULTITEMP2009, July 28-30, Groton, CT, USA
EditorsDaniel L. Civco
PublisherUniversity of Connecticut
Number of pages9
ISBN (Print)978-1-4244-3461-9
Publication statusPublished - 30 Jul 2009
EventFinds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet - Stockholm, Sweden
Duration: 21 Sep 200925 Sep 2009


ConferenceFinds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet

    Research areas

  • urban remote sensing, multi-layer perceptrons, multi-temporal remote sensing images

ID: 1844558