Journal
GISCIENCE & REMOTE SENSING
Volume 50, Issue 2, Pages 231-250Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/15481603.2013.795307
Keywords
land cover; R; urban planning; supervised classification; pixel-based classification
Categories
Funding
- MIT-Portugal Program
- Fundacao para a Ciencia e Tecnologia [SFRH/BD/42964/2008]
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available