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Urban area extent extraction in spaceborne HR and VHR data using multi-resolution features

Articolo
Data di Pubblicazione:
2014
Abstract:
Detection of urban area extents by means of remotely sensed data is a difficult task, especially because of the multiple, diverse definitions of what an ―urban area‖ is. The models of urban areas listed in technical literature are based on the combination of spectral information with spatial patterns, possibly at different spatial resolutions. Starting from the same data set, ―urban area‖ extraction may thus lead to multiple outputs. If this is done in a well-structured framework, however, this may be considered as an advantage rather than an issue. This paper proposes a novel framework for urban area extent extraction from multispectral Earth Observation (EO) data. The key is to compute and combine spectral and multi-scale spatial features. By selecting the most adequate features, and combining them with proper logical rules, the approach allows matching multiple urban area models. Experimental results for different locations in Brazil and Kenya using High-Resolution (HR) data prove the usefulness and flexibility of the framework. © 2014 by the authors; licensee MDPI, Basel, Switzerland.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
remote sensing, mapping, multi-scale, multi-spectral, spatial features, urban areas,
Elenco autori:
Iannelli, GIANNI CRISTIAN; Lisini, Gianni; Dell'Acqua, Fabio; Feitosa, R. Q.; da Costa, G. A. O. P.; Gamba, PAOLO ETTORE
Autori di Ateneo:
DELL'ACQUA FABIO
GAMBA PAOLO ETTORE
Link alla scheda completa:
https://iris.unipv.it/handle/11571/1183003
Pubblicato in:
SENSORS
Journal
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URL

http://www.mdpi.com/1424-8220/14/10/18337
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