Measuring rill erosion using structure from motion: A plot experiment

Stefano, Costanza Di; Ferro, Vito; Palmeri, Vincenzo; Pampalone, Vincenzo

doi:10.1016/j.catena.2017.04.023

Cited by 64 publications

(35 citation statements)

References 39 publications

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“…Each plot was filled with a clay soil (73% clay, 22.5% silt, and 4.5% sand). Further details of the experimental installation are reported in Di Stefano et al ().…”

Section: Methodsmentioning

confidence: 99%

“…An image‐based technique was applied for carrying out the ground measurements of rill cross‐sectional area, wetted perimeter, and channel slope. Using a set of oblique photographs (Figure ) of the rilled surface (Di Stefano et al, ; Frankl et al, ), this technique creates a digital terrain model (Gómez‐Gutiérrez, Schnabel, Berenguer‐Sempere, Lavado‐Contador, & Rubio‐Delgado, ; Westoby, Brasington, Glasser, Hambrey, & Reynolds, ; Figure ). Camera model parameters and scene geometry are simultaneously solved (James & Robson, ) using redundant information coming from oblique photographs.…”

Section: Methodsmentioning

confidence: 99%

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Testing slope effect on flow resistance equation for mobile bed rills

Stefano

Ferro

Palmeri

et al. 2018

Hydrological Processes

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In this paper, a recently theoretically deduced rill flow resistance equation, based on a power‐velocity profile, is tested experimentally on plots of varying slopes in which mobile bed rills are incised. Initially, measurements of flow velocity, water depth, cross‐sectional area, wetted perimeter and bed slope conducted in 106 reaches of rills incised on an experimental plot having a slope of 14% were used to calibrate the flow resistance equation. Then, the relationship between the velocity profile parameter Γ, the channel slope, and the flow Froude number, which was calibrated using the 106 rill reach data, was tested using measurements carried out in plots having slopes of 22% and 9%. The measurements carried out in the latter slope conditions confirmed that (a) the Darcy–Weisbach friction factor can be accurately estimated using the proposed theoretical approach, and (b) the data were supportive of the slope independence hypothesis of rill velocity stated by Govers.

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“…Each plot was filled with a clay soil (73% clay, 22.5% silt, and 4.5% sand). Further details of the experimental installation are reported in Di Stefano et al ().…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Testing slope effect on flow resistance equation for mobile bed rills

Stefano

Ferro

Palmeri

et al. 2018

Hydrological Processes

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“…The advent of low-cost UAS platforms and concomitantly lightweight camera systems in the visible, near-infrared (NIR), and thermal spectral range has motivated their increased use in the remote-sensing community, e.g. precision agriculture applications (Berni et al 2009; Brosy et al 2017; Zhang and Kovacs 2012; Candiago et al 2015; Reineman et al 2013; Link, Senner, and Claupein 2013; Lelong et al 2008; Turner et al 2014; Stefano et al 2017; Vázquez-Tarrío et al 2017). However, studies using UAS-based TIR sensors to map LST and subsequently derive surface turbulent heat fluxes are still rare (Hoffmann et al 2016b; Ortega-Farías et al 2017; Ortega-Farías et al 2016; Brenner et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Brenner

Zeeman

Bernhardt

et al. 2018

International Journal of Remote Sensing

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Spatially distributed high-resolution data of land surface temperature (LST) and evapotranspiration (ET) are important information for crop water management and other applications in the agricultural sector. While satellite data can provide LST high-resolution data of 100 m, the current development of unmanned aerial systems (UAS) and affordable low-weight thermal cameras allows LST and subsequent ET to be derived at resolutions down to centimetre scale.In this study, UAS-based images in the thermal infrared (TIR) and visible spectral range were collected over a managed temperate grassland in July 2016 at the Terrestrial Environmental Observatories Networks TERENO preAlpine observatory site at Fendt, Germany. The UAS set-up included a lightweight thermal camera (Optris Pi Lightweight) and a regular digital camera (Sony α 6000) that allowed for the acquisition of thermal and optical images with a ground resolution of 5 cm and 1 cm, respectively. Three TIR-based ET models of different complexity were applied and the resulting ET estimates were compared to the Eddy covariance (EC) observations of turbulent energy fluxes and also to the evaporative fraction. While the Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature (DATTUTDUT) model and the Triangle Method belong to the group of simpler contextual models, the Two-Source Energy Balance (TSEB) model incorporates a more physically based formulation of the surface energy balance. In addition to the comparison of UAS-based estimates of latent heat fluxes to EC observations, the effect of the spatial resolution of the model imagery input on the modelled results was analysed by running the models with imagery from the native resolution of the acquired images to resolutions that were aggregated up to 30 m.The results show that both contextual models are sensitive to the input image resolution and that the agreement with the EC observations improves with increasing image resolution. The TSEB model assumes that LST pixels represent a mixed signal of the soil and canopy components, thus an image resolution coarse enough to ensure this assumption should be chosen. However, with the exception of the native image resolution of 5 cm, we found no effect of image resolution on the spatially weighted mean TSEB estimates.For the studied grassland, the comparison of model estimates with EC observations indicates that all three models are able to reproduce observed energy fluxes with comparable accuracy with mean absolute errors of ET between 20 and 40 W m−2. The TSEB model showed larger deviations from the reference observations under cloudy conditions with rapid fluctuations of LST within the 30 min averaging period for EC. The two contextual models yielded similar results for most of the flights. The good performance of the DATTUTDUT model, which had the lowest input requirements of the three models, is especially promising in view of the application of UAS for routine near-real-time ET monitoring.

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“…The used image processing software Agisoft PhotoScan Professional (Agisoft LLC, Petersburg, Russia) includes all of the steps for model creation, from the raw data (the photographs) to 3D point clouds, 3D triangulated meshes, 2.5D models (DEMs), and orthophotos with a workflow that is simple and user‐friendly. For UAV, TS, and UAV + TS, the 3D models were obtained by an automatic process that couples SfM and MVS techniques (Di Stefano, Ferro, Palmeri, & Pampalone, , Di Stefano, Ferro, Palmeri, Pampalone, & Agnello, ; Kaiser et al, ). Then, using the point clouds of the 3D models, DEMs were generated to carry out the subsequent hydrological and morphological analyses for extracting rill network.…”

Section: Methodsmentioning

confidence: 99%

“…Di Stefano, Ferro, Palmeri, and Pampalone () applied terrestrial photogrammetry for measuring rill erosion at plot scale. Soil losses were measured by 3D models and compared with the actual weight of the sediment stored into the tank downstream of the plot.…”

Section: Introductionmentioning

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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Measuring rill erosion using structure from motion: A plot experiment

Cited by 64 publications

References 39 publications

Testing slope effect on flow resistance equation for mobile bed rills

Testing slope effect on flow resistance equation for mobile bed rills

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

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

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