Zumpano, V.; Pisano, L.; Parise, M.; Parise, M., 2019, An integrated framework to identify and analyze karst sinkholes, Geomorphology (Amst.) 332 (2019): 213–225. doi_10.1016/j.geomorph.2019.02.013,
URL: http://www.cnr.it/prodotto/i/402083

Sinkholes are the most typical surface feature of karst landscapes. Their correct mapping is of great importance for a proper assessment of the possible occurrence of new events, and the likely effects they could have on the anthropogenic environment. In this work we compare and discuss different ways to map sinkholes, including heuristic approach, automatic mapping through different resolution DTMs, and digital aerial photo interpretation, aimed at highlighting advantages and drawbacks of the multiple approaches. For our purpose we use a study area in the Murge of Apulia, SE Italy, where many sinkholes of several typologies are present to characterize the landscape. To evaluate the reliability of the sinkhole mapping, we set up a conceptual methodology that integrates a semi-automatic method with the heuristic approach, with a special focus on the importance of incorporating digital stereoscopic interpretation. In detail, we used as input two DTMs at different resolution, aimed to test the robustness of the automatic method in different circumstances. Comparison of the data produced by the different approaches illustrated how the number, density and boundaries of the sinkholes may vary as a function of the input data. The automated mapping provides reliable results in terms of number, dimensions, and morphometric attributes of sinkholes, and appears to be particularly useful when large areas must be analyzed. Within the whole process, we stress the role of the expert geomorphologist who must determine the accuracy of the product obtained with the automated mapping by correcting/eliminating features not attributable to karst processes. The presented approach highlights the potential of digital stereoscopy in substantially decreasing the errors encountered with traditional analog mapping, simultaneously reducing the working time significantly.

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