Using spatial autocorrelation techniques and multi-temporal satellite data for analyzing urban sprawl

摘要: Satellite time series offer great potential for a quantitative assessment of urban expansion, sprawl and monitoring land use changes soil consumption. This study deals with the spatial characterization expansion areas by using autocorrelation techniques applied to multi-date Thematic Mapper (TM) satellite images. The investigation focused on several very small towns close Bari. Urban were extracted from NASA Landsat images acquired in 1976, 1999 2009, respectively. To cope fact that have be captured TM multi-temporal data sets, we adopted spectral indices emphasize occurring changes, reveal patterns. analyzed both global local indexes. approach enables pattern features area it improves change estimation. obtained results showed significant coupled an increase irregularity degree border modifications 1976 2009.