The use of remote-sensing images is becoming common practice in the fight against environmental crimes. However, the challenge of exploiting the complementary information provided by radar and optical data, and by more conventional sources encoded in geographic information systems, is still open. In this work, we propose a new workflow for the detection of potentially hazardous cattle-breeding facilities, exploiting both synthetic aperture radar and optical multitemporal data together with geospatial analyses in the geographic information system environment. The data fusion is performed at a feature-based level. Experiments on data available for the area of Caserta, in southern Italy, show that the proposed technique provides very high detection capability, up to 95%, with a very low false alarm rate. A fast and easy-to-use system has been realized based on this approach, which is a useful tool in the hand of agencies engaged in the protection of territory

This study introduces new methods and applications for detecting, evaluating, and tracking signs of environmental contamination using a variety of advanced aerial platforms, a suite of advanced sensors, and new detection software. Aerial platform examples include: manned aircraft and helicopters, unmanned fixed wing aircraft (UAV), and unmanned rotorcraft. The onboard sensors include an array of multispectral and electro-optical infrared cameras. The developed system, which is being used by the Italian Coast Guard, is ideal for detecting illegal and unauthorized sewer and storm-drain environmental policy violations. The methods presented here were developed to detect pollution in rivers and the sea. The results of these current studies show that: (1) infrared thermography is an ideal tool to detect environmental contamination, (2) a variety of aerial platforms ranging from manned aircraft to small unmanned rotorcraft should be used to first globally scan the region and then locally focus on the suspected site, and (3) the measured high resolution database accurately defines the current state of the region which provides a benchmark for future investigations.

When Italian law enforcement investigates illegal environmental dumping, data must be carefully compiled, analyzed, and validated in order to...

Every year in Italy, hundreds of illegal dumping activities are detected but it is believed that there could be up to 10 times more, where the...

In this paper we propose a GIS-based methodology, using optical and SAR remote sensing data, together with more conventional sources, for the detection of small cattle breeding areas, potentially responsible of hazardous littering. This specific environmental problem is very relevant for the Caserta area, in southern Italy, where many small buffalo breeding farms exist which are not even known to the productive activity register, and are not easily monitored and surveyed. Experiments on a test area, with available specific ground truth, prove that the proposed systems is characterized by very large detection probability and negligible false alarm rate