Estimation of small-scale soil erosion in laboratory experiments with Structure from Motion photogrammetry

Balaguer-Puig, M.; Marqués-Mateu, Ángel; Lerma, José Luis; Ibáñez-Asensio, Sara

doi:10.1016/j.geomorph.2017.04.035

Cited by 49 publications

(32 citation statements)

References 59 publications

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“…Kasprak et al, 2015;Guo et al, 2016;Balaguer-Puig et al, 2017), and sequences of DEMs produced by models (e.g. Kasprak et al, 2015;Guo et al, 2016;Balaguer-Puig et al, 2017), and sequences of DEMs produced by models (e.g.…”

Section: Discussionmentioning

confidence: 99%

“…The effect of budget compensation by alternating erosion and deposition and its dependence on the length of the inter-survey period has been previously investigated (e.g. Lindsay and Ashmore, 2002;Milan et al, 2007;Balaguer-Puig et al, 2017). Due to these issues, accErosion represents a minimum estimate, and therefore the resulting SDR is a maximum estimate.…”

Section: Sediment Delivery Ratio (Sdr)mentioning

confidence: 99%

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Computing spatially distributed sediment delivery ratios: inferring functional sediment connectivity from repeat high‐resolution digital elevation models

Heckmann

Vericat

2018

Earth Surf Processes Landf

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High‐resolution digital elevation models (DEMs) from repeat LiDAR (light detection and ranging) or SfM (structure from motion) surveys have become an important tool in process geomorphology. The spatial pattern of negative and positive changes of surface elevation on raster DEMs of difference (DoD) can be interpreted in terms of geomorphic processes, and has been used for morphological budgeting. We show how the application of flow routing algorithms and flow accumulation opens new opportunities for the analysis of DoD. By accumulating the values of the DoD along downslope flowpaths delineated on a DEM, these algorithms lend themselves to computing the net balance, i.e. sediment yield (SY), for the contributing area of each cell. Doing the same for the negative subset of the DoD yields a minimum estimate of erosion (E) within the contributing area. The division of SY by E yields (a maximum estimate of) the sediment delivery ratio (SDR), that is the proportion of material eroded within the contributing area of each cell that has been exported from that area. The resulting SDR is a spatially distributed measure of functional sediment connectivity. In this letter, we develop the computationally simple approach by means of an example DoD from a lateral moraine section in the Upper Kaunertal Valley, Austrian Central Alps. We also discuss advantages, assumptions and limitations, and outline potential applications to connectivity research using field‐, laboratory‐, and model‐based DoD. Copyright © 2018 John Wiley & Sons, Ltd.

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Section: Discussionmentioning

confidence: 99%

Section: Sediment Delivery Ratio (Sdr)mentioning

confidence: 99%

Computing spatially distributed sediment delivery ratios: inferring functional sediment connectivity from repeat high‐resolution digital elevation models

Heckmann

Vericat

2018

Earth Surf Processes Landf

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“…In this section, we briefly describe a case study that supports the laboratory procedure proposal. All the pictures and data were collected in a previous experiment conducted by Balaguer‐Puig et al (), even though the pictures were completely reprocessed to obtain the results presented in this paper.…”

Section: Methodsmentioning

confidence: 99%

“…In the last years, the applications of SfM with multi-view stereo (MVS) at different scales have considerably increased in the geosciences Fonstad, Dietrich, Courville, Jensen, & Carbonneau, 2013;James & Robson, 2012;Micheletti, Chandler, & Lane, 2015;Westoby, Brasington, Glasser, Hambrey, & Reynolds, 2012). SfM photogrammetry has been evaluated at micro-scale, confirming that this technique can provide high precision DEMs (e.g., Kasprak, Wheaton, Ashmore, Hensleigh, & Peirce, 2015;Micheletti, Chandler, & Lane, 2014;Nouwakpo et al, 2014) and, indeed, it is being used in recent GCD-based soil erosion research (e.g., Balaguer-Puig, Marqués-Mateu, Lerma, & Ibáñez-Asensio, 2017;Guo et al, 2016;Hänsel, Schindewolf, Eltner, Kaiser, & Schmidt, 2016;Prosdocimi et al, 2017;Vinci, Todisco, Brigante, Mannocchi, & Radicioni, 2017). Validation of the erosion estimates obtained with the morphologic method is done by comparison with the actual sediments collected during the experiment.…”

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confidence: 98%

Quantifying small‐magnitude soil erosion: Geomorphic change detection at plot scale

et al. 2017

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Soil erosion is a big concern in bare soils from burnt areas and agricultural lands that lack a vegetation cover. In those unprotected soils, intense rain episodes, typical in Mediterranean climate, cause severe soil erosion processes that have been well studied previously using a number of procedures, such as the geomorphic change detection (GCD) method. This method uses digital elevation models (DEMs) of the soil surface and determines the morphological changes in terms of both erosion and deposition by DEMs of difference (DoDs). However, some types of soil erosion, such as diffuse and sheet erosion, may have a small magnitude, at a millimetre scale, and their determination requires methods adapted to that scale. In this paper, we analyse the suitability of the GCD method to account for small magnitude soil erosion. We present a laboratory procedure and setup to represent and quantify sediment budget in small experimental soil plots through differences of DEMs obtained from images using photogrammetric structure from motion. This study explores several key aspects of the technique: establishment of a common reference system for DEMs; determination of errors in the generation of DEMs; selection of appropriate criteria to obtain reliable changes in DoDs; error propagation using Monte Carlo simulation; and validation of the procedure by comparing the results with actual sediments collected during the experiment. Results showed an overestimation of 13% in accumulated soil loss and confirmed that GCD approach with structure from motion‐based DoDs is a suitable method to quantify small‐magnitude erosion events.

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“…For evaluating the accuracy of the photogrammetric project, RMSE on independent check points (CPs) has to be calculated. This RMSE value is also useful for establishing the minimum level of detection when geomorphic change is determined by difference of models (3D point clouds, DEMs; Prosdocimi, Calligaro, Sofia, Dalla Fontana, & Tarolli, 2015;Balaguer-Puig, Marqués-Mateu, Lerma, & Ibáñez-Asensio, 2017;Hänsel, Schindewolf, Eltner, Kaiser, & Schmidt, 2016;Vinci, Todisco, Brigante, Mannocchi, & Radicioni, 2017).…”

mentioning

confidence: 99%

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

Stefano

Palmeri

Pampalone

2019

Hydrological Processes

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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.

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Estimation of small-scale soil erosion in laboratory experiments with Structure from Motion photogrammetry

Cited by 49 publications

References 59 publications

Computing spatially distributed sediment delivery ratios: inferring functional sediment connectivity from repeat high‐resolution digital elevation models

Computing spatially distributed sediment delivery ratios: inferring functional sediment connectivity from repeat high‐resolution digital elevation models

Quantifying small‐magnitude soil erosion: Geomorphic change detection at plot scale

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

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