An automatic approach for rill network extraction to measure rill erosion by terrestrial and low-cost unmanned aerial vehicle photogrammetry

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Abstract

For an erosion event (October 2016) occurred at the Sparacia experimental area (Southern Italy), both terrestrial and low-altitude aerial surveys were carried out by consumer grade camera and quadcopter (low-cost unmanned aerial vehicle [UAV]) to measure rill erosion on two plots with steepness of 22% and 26%. Applying the structure from motion (SfM) technique, the three-dimensional digital terrain models (3D-DTMs) and the quasi three-dimensional models (2.5D-digital elevation model [DEM]) were obtained by the two surveys. Furthermore, 3D-DTM and DEM were built using the available aerial photographs (166) and adding 40 terrestrial photographs. For the first time, the convergence index was applied to high-resolution rill data for extracting the rill network, and a subsequent separation into contributing and non-contributing rills was carried out. The comparison among the three surveys (terrestrial, UAV, and UAV + terrestrial) was developed using two morphometric parameters of the rill network (drainage density and drainage frequency). Moreover, using as reference the weight of sediment stored on the tanks located downstream of the plots, the reliability of soil loss measurement by 3D models was tested. For both contributing and non-contributing rills, the morphometric parameters were higher for the terrestrial than for UAV and UAV + terrestrial surveys. For both plots, SfM always provided reliable soil loss measurements, which were affected by errors ranging from −8% to 13%. Although the applied technique used a low-cost UAV and a consumer grade camera, the obtained results demonstrated that a reliable estimate of rill erosion can be obtained in an area of interest.
Original languageEnglish
Pages (from-to)1883-1895
Number of pages13
JournalHydrological Processes
Volume33
Publication statusPublished - 2019

All Science Journal Classification (ASJC) codes

  • Water Science and Technology

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