Comparing the Accuracy of Several Field Methods for Measuring Gully Erosion

Abstract

Most field erosion studies in agricultural areas provide little information on the probable errors involved. Here, for the first time, we compare the accuracy, time and cost of conventional and new methodologies for gully surveying, and provide a model to estimate the effort required to achieve a specified accuracy. Using a terrestrial LiDAR survey of a 7.1-m-long guliy reach as a benchmark data set, the accuracies of different measurement methods (a new 3D photo-reconstruction technique, total station, laser profilemeter, and pole) are assessed for estimating gully erosion at a reach scale. Based on further field measurements performed over nine gullies (>100 m long), a simulation approach is derived to model the expected volume errors when 2D methods are used at the gully scale. All gullies considered were located near Cordoba, Spain. At the reach scale, the field measurements using 3D photo-reconstruction and total station techniques produced cross-sectional area error values smaller than 4%, with other 2D methods exceeding 10%. For volume estimation, photo-reconstruction proved similar to LiDAR data, but 2D methods generated large negative volume error (E^) values (<-13% for laser profilemeter and pole). We show that the proposed error expressions derived from the model are in line with the reach-scale field results. A measurement distance factor (MDF) is defined that represents the ratio between cross-section distance and the gully length, and thus reflects relative survey effort. We calculate the required MDF for specified values of f^, illustrating how MDF decreases with increasing gully length and sinuosity.Abbreviations: A, cross sectional area (m^); D, distance between adjacent cross sections (m); DEM, digital elevation model; E^, relative area measurement error (%); E'-, relative length error (%); E^, relative volume measurement error (m-^); L, Gully length (m); i.g^,, distance between the extremes of the gully (m); i-gj-t-sm' distance between the extremes of a 5 m reach (m); L^, polyline length defined by cross section distance (m); /. ,, length of the polyline that fits coarsely the gully thalweg following knickpoints (m); ¿real-5m' real length of a 5 m reach (m); MDF, measurement distance factor (%); n, number of subreaches; N^^, total number of 5-m reaches within a gully; S^'^¡^^^¡, local sinousity; 5 II , gully sinuosity; SE, sinuosity factor; o^^ standard deviation of the volume error drstribution (%); V, volume of eroded soil within the gully (m^).

SF3M software: 3-D photo-reconstruction for non-expert users and its application to a gully network

“…When compared with previous studies on gully erosion assessment through SfM photo-reconstruction (Castillo et al, 2012a(Castillo et al, , 2014Gómez-Gutiérrez et al, 2014;Kaiser et al, 2014) in terms of unitary efficiency (field effort per meter of gully), this work showed larger errors (roughly 2 times the average errors in those studies) but at a lower survey intensity (images per meter of gully) and at 1 order of magnitude lower time requirements (Table 3).…”

“…3-D PR has been used for gully erosion assessment at the gully reach or headcut scale (Castillo et al, 2012a;Kaiser et al, 2014;Gómez-Gutiérrez et al, 2014) and ephemeral gullies (Castillo et al, 2014a), usually not more than a few metres extent. However, the full characterization of gully erosion requires the assessment of entire gully networks to understand their geometry and dynamics and this brings several challenges for terrestrial PR:…”

Gully Erosion Mapping and Monitoring at Multiple Scales Based on Multi-Source Remote Sensing Data of the Sancha River Catchment, Northeast China

“…Various techniques have been applied for measuring, mapping and monitoring gully erosion accordingly. Compared with conventional techniques (e.g., ruler, tape, microtopographic profilers [13], poles, total stations [14], pins [15] and differential GPS [16,17]), which are time-consuming for achieving high accuracy in field surveys at a small scale, the development of remote sensing techniques has provided an efficient method to obtain spatially continuous gully information over large scales for different time periods. Classical aerial photography has been effectively employed for large-scale areas and long-term investigations, but with low spatial and temporal resolution [18,19].…”

“…Compared with laser scanners and rigorous photogrammetric methods, Structure-from-motion (SfM) and multi-view-stereo (MVS) algorithms, which are the generally proposed reconstruction methods, just use consumer-grade cameras and require less expertise [36,37]. Previous work has compared 3D photo-reconstruction with existing 2-D and 3-D field methods (e.g., LiDAR, laser profilometer, total station) for assessing gully erosion with regard to cost, accuracy and effectiveness, revealing the superiority of 3D photo-reconstruction [14,38]. By adopting 3D photo-reconstruction techniques, numerous researchers used images derived from UAV to generate high resolution topographic data and ortho-image for monitoring gully erosion [34,39].…”

Elaboración de modelos 3D de diferentes morfologías y escalas utilizando técnicas Structure-from-Motion y fotografías terrestres

“…Los estudios más relevantes han dado lugar a modelos 3D de alta resolución de cár-cavas (Castillo et al, 2012;Gómez-Gutiérrez et al, 2014b), badlands (Nadal-Romero et al, 2015;Smith y Vericat, 2015) y glaciares (Gó-mez-Gutiérrez et al, 2014a;Gómez-Gutiérrez et al, 2015). Es decir, se han centrado en formas ciertamente dinámicas.…”