Roughness measurements over an agricultural soil surface with Structure from Motion

Snapir, Boris; Hobbs, Stephen; Waine, Toby

doi:10.1016/j.isprsjprs.2014.07.010

Cited by 47 publications

(47 citation statements)

References 37 publications

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“…This concerned the study of Dietrich (2016) due to a very large scale of an investigated river reach (excluded from Figs. 4a and 5a-b), the study of Snapir et al (2014) due to a very high reference accuracy of Lego bricks (excluded from Figs. 4c and 5b), and the study of Frankl et al (2015) due to a high measured error as the study focus was rather on feasibility than accuracy (excluded from Fig.…”

Section: Error Assessment Of Sfm Photogrammetry In Geoscientific Applmentioning

confidence: 99%

Image-based surface reconstruction in geomorphometry – merits, limits and developments

et al. 2016

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Abstract. Photogrammetry and geosciences have been closely linked since the late 19th century due to the acquisition of high-quality 3-D data sets of the environment, but it has so far been restricted to a limited range of remote sensing specialists because of the considerable cost of metric systems for the acquisition and treatment of airborne imagery. Today, a wide range of commercial and open-source software tools enable the generation of 3-D and 4-D models of complex geomorphological features by geoscientists and other non-experts users. In addition, very recent rapid developments in unmanned aerial vehicle (UAV) technology allow for the flexible generation of high-quality aerial surveying and ortho-photography at a relatively low cost.The increasing computing capabilities during the last decade, together with the development of highperformance digital sensors and the important software innovations developed by computer-based vision and visual perception research fields, have extended the rigorous processing of stereoscopic image data to a 3-D point cloud generation from a series of non-calibrated images. Structure-from-motion (SfM) workflows are based upon algorithms for efficient and automatic orientation of large image sets without further data acquisition information, examples including robust feature detectors like the scale-invariant feature transform for 2-D imagery. Nevertheless, the importance of carrying out well-established fieldwork strategies, using proper camera settings, ground control points and ground truth for understanding the different sources of errors, still needs to be adapted in the common scientific practice.This review intends not only to summarise the current state of the art on using SfM workflows in geomorphometry but also to give an overview of terms and fields of application. Furthermore, this article aims to quantify already achieved accuracies and used scales, using different strategies in order to evaluate possible stagnations of current developments and to identify key future challenges. It is our belief that some lessons learned from former articles, scientific reports and book chapters concerning the identification of common errors or "bad practices" and some other valuable information may help in guiding the future use of SfM photogrammetry in geosciences.

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Section: Error Assessment Of Sfm Photogrammetry In Geoscientific Applmentioning

confidence: 99%

Image-based surface reconstruction in geomorphometry – merits, limits and developments

et al. 2016

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“…This is important, since recently-developed methods involving close range techniques, such as stereo-photogrammetric systems (see for instance [21]), Structure from Motion [22] or Terrestrial Laser Scanning [17] are more suitable for multitemporal studies rather than for multisite surveys due to the need for setting up of reference targets on ground, for each site measurement. Moreover, in this sort of techniques the sampling interval depends on the particular experimental set-up chosen, mainly the distance between the camera and the soil patch.…”

Section: Introductionmentioning

confidence: 99%

Effects of Spatial Sampling Interval on Roughness Parameters and Microwave Backscatter over Agricultural Soil Surfaces

et al. 2016

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Abstract:The spatial sampling interval, as related to the ability to digitize a soil profile with a certain number of features per unit length, depends on the profiling technique itself. From a variety of profiling techniques, roughness parameters are estimated at different sampling intervals. Since soil profiles have continuous spectral components, it is clear that roughness parameters are influenced by the sampling interval of the measurement device employed. In this work, we contributed to answer which sampling interval the profiles needed to be measured at to accurately account for the microwave response of agricultural surfaces. For this purpose, a 2-D laser profiler was built and used to measure surface soil roughness at field scale over agricultural sites in Argentina. Sampling intervals ranged from large (50 mm) to small ones (1 mm), with several intermediate values.Large-and intermediate-sampling-interval profiles were synthetically derived from nominal, 1 mm ones. With these data, the effect of sampling-interval-dependent roughness parameters on backscatter response was assessed using the theoretical backscatter model IEM2M. Simulations demonstrated that variations of roughness parameters depended on the working wavelength and was less important at L-band than at C-or X-band. In any case, an underestimation of the backscattering coefficient of about 1-4 dB was observed at larger sampling intervals. As a general rule a sampling interval of 15 mm can be recommended for L-band and 5 mm for C-band.

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“…These studies use laser scanners for either micro-scale surface imaging (Schmid et al, 2004;Barneveld et al, 2013) or measuring crack apertures (Sanchez et al, 2013). In addition, photogrammetry and structure from motion (SfM) methods are now being developed to analyse soil surfaces (Snapir et al, 2014). This paper shows that monitoring the changes at the millimetre scale to examine soil surface changes and erosion is now possible.…”

Section: Discussionmentioning

confidence: 99%

Erosion processes in black marl soils at the millimetre scale: preliminary insights from an analogous model

Bechet

Duc

Jaboyedoff

et al. 2015

Hydrol. Earth Syst. Sci.

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Abstract.To investigate the millimetre-scale surface processes caused by natural rainfall, an undisturbed sample of badlands soil (1 m long, 0.5 m wide and 0.15 m thick) was carefully extracted. The sample is composed of black marl soil from a badlands area of the Draix Observatory (SE France). After extraction, the undisturbed sample was placed at the same slope angle (45 • ) as its original orientation and was then monitored for several processes via a terrestrial laser scanner (TLS) with millimetre-scale accuracy and resolution. This experiment identified several surface processes interpreted as micro-landslides, swelling of the black marl material and lateral expansion that closed desiccation cracks. These micro-processes illustrate the complexity of the surface micro-topography changes that control erosion and infiltration rates over time.

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Roughness measurements over an agricultural soil surface with Structure from Motion

Cited by 47 publications

References 37 publications

Image-based surface reconstruction in geomorphometry – merits, limits and developments

Image-based surface reconstruction in geomorphometry – merits, limits and developments

Effects of Spatial Sampling Interval on Roughness Parameters and Microwave Backscatter over Agricultural Soil Surfaces

Erosion processes in black marl soils at the millimetre scale: preliminary insights from an analogous model

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