[en] Spatial metrics derived from satellite imagery are useful measures to quantify structural characteristics of expanding cities, and can provide indications of functional land use types. Images of medium resolution are cheap, widely available and are often part of extensive historic archives. Their lower resolution, on the other hand, inhibits studying urban morphology and change processes at a more detailed, intra-urban level. In this study, we develop spatial metrics for use on continuous sealed surface data produced by a sub-pixel classification of Landsat ETM+ imagery. The metrics characterise the shape of the cumulative frequency distribution of the estimated sub-pixel fractions within a building block by fitting an exponential and a sigmoid function with a least-squares approach. A classification tree is then used to relate the metric variables to urban land-use classes selected from the European MOLAND topology. This approach shows promising results, but still needs improvement which may be achieved by including spatially explicit metrics in the analysis.
Research Center/Unit :
Laboratoire SURFACES
Disciplines :
Earth sciences & physical geography
Author, co-author :
Van de Voorde, Tim; Vrij Universiteit Brussel - VUB > geografie > Cartography and GIS Research Unit (CGIS)
van der Kwast, Johannes; Vlaamse Instelling voor Technologisch Onderzoek - VITO
Engelen, Guy; Vlaamse Instelling voor Technologisch Onderzoek - VITO
Binard, Marc ; Université de Liège - ULiège > Département de géographie > Laboratoire SURFACES - Unité de Géomatique - Geomatics Unit
Cornet, Yves ; Université de Liège - ULiège > Département de géographie > Laboratoire SURFACES - Unité de Géomatique - Geomatics Unit
Canters, Frank; Vrij Universiteit Brussel - VUB > geografie > Cartography and GIS Research Unit (CGIS)
Language :
English
Title :
Quantifying intra-urban morphology of the Greater Dublin area with spatial metrics derived from medium resolution remote sensing data
Publication date :
2009
Event name :
7th international Urban Remote Sensing conference (URS 2009)
Event organizer :
IEEE
Event place :
Shanghai, China
Event date :
du 20 mai 2009 au 22 mai 2009
Audience :
International
Main work title :
IEEE Proceedings of the 7th International Urban Remote Sensing Conference : Shanghai, May 20-22, 2009
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