Analyzing urban sprawl applying spatial autocorrelation techniques to multi-temporal satellite data

In last decades industrialization and expansion of urban areas have caused strong and sharp land use changes with significant landscape transformations, which significantly impact environmental futures. Although urban growth is perceived as necessary for a sustainable economy, uncontrolled or sprawling urban growth can cause various problems, such as loss of open space, landscape alteration, environmental pollution, traffic congestion, infrastructure pressure, and other social and economical issues. Several programmes have been proposed and implemented in many European countries with the aim of reducing soil consumption. In such programmes it is fundamental to define methods, techniques and procedures to monitor the phenomenon. The aim of this paper is to propose an integration of free software (Linux Ubuntu, GRASS GIS and Quantum GIS, R) and data (Landsat) in order to quantify phenomenon evolution. In order to produce more reliable data, autocorrelation techniques have been implemented in open source software.