期刊
GISCIENCE & REMOTE SENSING
卷 50, 期 2, 页码 231-250出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/15481603.2013.795307
关键词
land cover; R; urban planning; supervised classification; pixel-based classification
资金
- MIT-Portugal Program
- Fundacao para a Ciencia e Tecnologia [SFRH/BD/42964/2008]
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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