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Satellite remote sensing allows for large scale monitoring with low cost and high revisit time. However, in some applications, it does not provide all the information needed by the analyst for the full characterization of the problem due to, as an example, insufficient resolution or lack of specific measurements. This can lead to inaccuracies in classification and/or detection tasks. Nevertheless, satellite data can be used to guide subsequent discovery, recognition and characterization actions, defining potential areas of interest of limited extension that can be furtherly investigated with on-site strategies. This work presents an innovative framework showing how to use incomplete and inaccurate information extracted by satellite images in order to address on-ground discovery actions aimed to the mapping and the characterization of illegal micro-dumps in Campania Region (Italy). In particular, high-resolution images up to 50 cm resolution are exploited to detect potential micro-dumps by means of a statistical learning method based on spatial features. The detection map is then used to create a priority map based on environmental risk considerations, such as the extension of the area interested by the dump and its proximity to urban settlements, and previous risk mitigation actions. This information is ingested by a planning system in order to allocate and calculate patrolling routes based on the available manpower and vehicles for on-site surveying. The survey is implemented by means of drones equipped with payloads and software allowing for real-time three-dimensional reconstruction of the scene and volumetric estimations. This provides further data to assess the real dangerousness of the site giving to decision makers essential information to plan remediation actions. The system is demonstrated through a case study showing all the stages of the decision process.

In some environmental applications, satellite acquisitions could not be able to provide all the information necessary to characterize the problem at hand due, for example, to limited spatial resolution or inadequate revisit time. However, in these cases, they can be used for preliminary investigation of the area of interest with the purpose to guide subsequent acquisitions with higher spatial resolution made by means of aerial sensing. This work presents an innovative application combining both satellite acquisitions and aerial close-range sensing implemented via drones in autonomous and coordinated flight. The case study concerns the discovery of illegal micro-dumps and other environmental hazards in Campania Region (Italy). The envisioned workflow includes the detection of target environmental criticalities in very high-resolution optical satellite images and a methodology to plan and adaptively re-plan a survey mission of a team of drones aimed at confirming the presence of a micro-dump and at its characterization. The processing of satellite images is validated on real data in a significative application context, while the performance of the acquisition strategy performed by the drone team are characterized trough simulations on a pre-analysed geographical area.

Illegal landfills are unfortunately a plague in some areas of Southern Italy and cause significant direct and indirect environmental issues, including contamination of aquifers and dioxin release in the atmosphere due to arson attacks, potentially dangerous for local populations. The Italian government, at both central and local scale, is by long time enforcing these crimes, but the surveillance of wide areas is difficult with traditional on-site methodologies, even because it is possible that landfills are located within private properties not accessible without formal authorization. Therefore, remote sensing technologies are a key to improve and make more efficient the and frequent the monitoring activities.Crowd for the Environment (C4E) is a project funded by the Italian Ministry of University and Research, aiming at the development of an innovative framework for the identification of illegal landfills using satellite and drone remote sensing in order to support decision makers in the organization of subsequent on-site actions. To this end, a new algorithm to detect possible polluted sites or sources of pollution has been developed. Specifically, the work has been focused on two particularly challenging and inter-related targets like micro-landfills and greenhouses.Micro-landfills are often the result of waste disposal processes from industrial or agricultural activities partially or totally clandestine. The corresponding unregistered industrial or agricultural plants are potential sources of pollution. The comparison of satellite detections with the database of legal activities allowed to determine whether or not a plant is registered and therefore potentially harmful. In the study area, located in the nearby of the city of Caserta, greenhouses are a typical example of unregistered agricultural infrastructures which could illegally dispose micro-dumps of their plastic cover after the use.Among the tested algorithms, those working on the spatial characterization of targets based on Scattering Transform were of particular interest. Such algorithms were used to extract textural features from images and their effectiveness was tested in comparison and in conjunction with spectral features within multi-class classifiers. The results obtained on very-high resolution Pleiades images with 50 cm spatial resolution showed that these features can significantly improve the detectors of both the identified targets. In the case of greenhouses, which are targets without significant spectral characteristics, due to their transparency and reflectivity, the features based on Scattering Transform, alone, allow to build very competitive detectors. In the case of micro-dumps, which are targets very difficult to detect from satellite, both for their size and for the heterogeneous spectral characteristics, the use of the Scattering Transform seems the most effective tool, while the combined use of spectral features does not provide particular added value.Ultimately, the use of the Scattering Transform seems to find an interesting application in the detection of environmental criticalities, also in relation to targets which are particularly difficult to be detected due to their high spectral ambiguity.