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Library Land cover and impervious surface extraction using parametric and non-parametric algorithms from the open-source software R: an application to sustainable urban planning in Sicily

Land cover and impervious surface extraction using parametric and non-parametric algorithms from the open-source software R: an application to sustainable urban planning in Sicily

Land cover and impervious surface extraction using parametric and non-parametric algorithms from the open-source software R: an application to sustainable urban planning in Sicily

Resource information

Date of publication
december 2013
Resource Language
ISBN / Resource ID
AGRIS:US201500210916
Pages
231-250

Detailed urban land-cover maps are essential information for sustainable planning. Land-cover maps assist planners in designing strategies for the optimisation of urban ecosystem services and climate change adaptation. In this study, the statistical software R was applied to land cover analysis for the Catania metropolitan area in Sicily, Italy. Six land cover classes were extracted from high-resolution orthophotos. Five different classification algorithms were compared. Texture and contextual layers were tested in different combinations as ancillary data. Classification accuracies of 89% were achieved for two of the tested algorithms.

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Authors and Publishers

Author(s), editor(s), contributor(s)

La Rosa, Daniele
Wiesmann, Daniel

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Data Provider
Geographical focus