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Illegal Waste Detection in Remote Sensing Images: A Case Study

Environmental crime is the third largest criminal activity worldwide, with significant revenues coming from illegal management of solid waste. Thanks to the increasing availability and the decreasing cost of Very High Resolution Remote Sensing (VHR RS) images, the fight against environmental crime can nowadays rely on modern image-analysis tools to support photo-interpretation for scanning vast territories in search of illegal waste disposal sites. This paper illustrates a semi-automatic waste detection pipeline, developed in collaboration with a regional environmental protection agency, for detecting candidate illegal dumping sites in VHR RS images. To optimize the effectiveness of the waste detector, extensive experiments evaluate such design choices as the network architecture, the ground resolution and geographic span of the input images, as well as the pretraining procedures. The best model attains remarkable performance, achieving 92.02% F1-Score and 94.56% Accuracy. A generalization study assesses the performance variation when the detector processes images from a territory substantially different from the one used during training, incurring only a moderate performance loss, i.e., 6.5% decrease in the F1-Score. Finally, an exercise in which photo interpreters compare the territory scanning effort with and without the support of the waste detector assesses the concrete benefit of using a computer-aided image analysis tool in a professional environment protection agency. Results show that a reduction up to 30% of the time spent for waste site detection can be attained.

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