Remote sensing detection techniques for brownfield identification and monitoring by GIS tools

Abstract

This paper examines remote sensing detection techniques for data integration in GIS to be employed in brownfield monitoring. Brownfields are frequently associated with urban wastes, mostly from building demolition. The hazard increases when dangerous materials are used. In order to allow us to perform a detailed classification of the land and to identify a wide range of the brownfields, the Laboratory of CNR (LARA) detects environmental data by means of the airborne MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) sensor. Moreover, GIS tools correlate the relevant data in order to evaluate the extension and derivative parameters of the same brownfields. These parameters are then used to elaborate indicators that can be used within the framework of a sustainable planning and development.