Reference : Quantifying intra-urban morphology of the Greater Dublin area with spatial metrics deriv...
Scientific congresses and symposiums : Paper published in a book
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
http://hdl.handle.net/2268/15024
Quantifying intra-urban morphology of the Greater Dublin area with spatial metrics derived from medium resolution remote sensing data
English
Van de Voorde, Tim mailto [Vrij Universiteit Brussel - VUB > geografie > Cartography and GIS Research Unit (CGIS) > >]
van der Kwast, Johannes mailto [Vlaamse Instelling voor Technologisch Onderzoek - VITO > > > >]
Engelen, Guy mailto [Vlaamse Instelling voor Technologisch Onderzoek - VITO > > > >]
Binard, Marc mailto [Université de Liège - ULg > Département de géographie > Laboratoire SURFACES - Unité de Géomatique - Geomatics Unit > >]
Cornet, Yves mailto [Université de Liège - ULg > Département de géographie > Laboratoire SURFACES - Unité de Géomatique - Geomatics Unit > >]
Canters, Frank mailto [Vrij Universiteit Brussel - VUB > geografie > Cartography and GIS Research Unit (CGIS) > >]
2009
IEEE Proceedings of the 7th International Urban Remote Sensing Conference : Shanghai, May 20-22, 2009
IEEE
No
International
978-1-4244-3461-9
7th international Urban Remote Sensing conference (URS 2009)
du 20 mai 2009 au 22 mai 2009
IEEE
Shanghai
China
[en] Urban remote sensing ; satellite imagery ; Spatial metrics ; sub-pixel classification
[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.
Laboratoire SURFACES
Politique Scientifique Fédérale (Belgique) = Belgian Federal Science Policy
MAMUD
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/15024
also: http://hdl.handle.net/2268/93640
http://www.mamud.be/

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