A method for the remote sensing identification of uncontrolled landfills: formulation and validation

Abstract

The identification of uncontrolled landfills is a central environmental problem in all developed and developing countries, where several illegal waste deposits exist as a result of rapid industrial growth over the past century. Remote sensing can potentially provide crucial information for the identification of contaminated sites, but surprisingly there is a marked lack of rigorously validated approaches. In this paper we introduce and validate a method that uses remotely sensed information and a geographic information system (GIS) to identify unknown landfills over large areas. The method is applied to a study area located in NE Italy (part of the Venice lagoon watershed) using IKONOS satellite data. Soil contamination effects on the radiometric properties of vegetation, calibrated using spectral signatures of stressed vegetation from known illegal landfill sites, were used to define numerous candidate sites that are most likely to host waste materials. Distributed geographical information, such as the position of the road network, the population density, and historical aerial photographs, have then been used to select the most likely contaminated sites among the candidates identified through remote sensing. The importance of the integration of GIS and remote sensing is highlighted and represents a key instrument for environmental management and for the spatially distributed characterization of possible uncontrolled landfill sites.

Acknowledgements

This research was funded by the Veneto Region (Deliberaz. Giunta Regionale n. 2455, 8 August 2003) in collaboration with the Magistrato alle Acque di Venezia. We thank Roberto Rosselli, Giancarlo Biotto, Lucia Gobbo, Silvia Rampazzo, Sonia Valenti, Elisa Furlan, Vincenzo Nicoletti and the other collaborators of the Servizio Infromativo – MAV for their help with GIS and databases. We also thank the military, public and local authorities (ARPAV, Province, Comuni, Guardia di Finanza, Corpo Forestale dello Stato) that provided all the information currently available on legal and illegal landfills located in the study area. Finally we thank Luigi Alberotanza of CNR, Venice, for providing us the sun‐photometer data collected within the AERONET framework.