A SMAP Supervised Classification of Landsat Images for Urban Sprawl Evaluation
AbstractThe negative impacts of land take on natural components and economic resources affect planning choices and territorial policies. The importance of land take monitoring, in Italy, has been only recently considered, but despite this awareness, in the great part of the country, effective monitoring and containment measures have not been started, yet. This research proposes a methodology to map and monitor land use changes. To this end, a time series from 1985–2010, based on the multi-temporal Landsat data Thematic Mapper (TM), has been analyzed in the Vulture Alto-Bradano area, a mountain zone of the Basilicata region (Southern Italy). Results confirm a double potentiality of using these data: on the one hand, the use of multi-temporal Landsat data allows going very back in time, producing accurate datasets that provide a phenomenon trend over time; on the other hand, these data can be considered a first experience of open data in the field of spatial information. The proposed methodology provides agencies, local authorities and practitioners with a valuable tool to implement monitoring actions. This represents the first step to pursue territorial governance methods based on sustainability, limiting the land take. View Full-Text
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Di Palma, F.; Amato, F.; Nolè, G.; Martellozzo, F.; Murgante, B. A SMAP Supervised Classification of Landsat Images for Urban Sprawl Evaluation. ISPRS Int. J. Geo-Inf. 2016, 5, 109.
Di Palma F, Amato F, Nolè G, Martellozzo F, Murgante B. A SMAP Supervised Classification of Landsat Images for Urban Sprawl Evaluation. ISPRS International Journal of Geo-Information. 2016; 5(7):109.Chicago/Turabian Style
Di Palma, Flavia; Amato, Federico; Nolè, Gabriele; Martellozzo, Federico; Murgante, Beniamino. 2016. "A SMAP Supervised Classification of Landsat Images for Urban Sprawl Evaluation." ISPRS Int. J. Geo-Inf. 5, no. 7: 109.