Studies regarding the use of remote sensing satellite data for the identification of heavy metal pollution in agricultural fields

Abstract

Heavy metal pollution in agricultural fields can be identified using several remote sensing image processing methods. The study aims at the identification of the optimal algorithms and the development of a validated processing work flow in order to detect the contaminated agricultural fields based on remote sensing satellite images. The investigation is performed on data acquired between the years of 2007 and 2011 over a test area - Copsa Mica - previously known as one of the most polluted towns in Europe due to the local industrial activity. The study is conducted on Landsat and SPOT images and the results are validated using ground truth data.