Combining field monitoring and aerial imagery to evaluate the role of gully erosion in a Mediterranean catchment (Tunisia)

Slimane, Abir Ben; Raclot, Damien; Rebai, H.; Bissonnais, Yves Le; Planchon, Olivier; Bouksila, Fethi

doi:10.1016/j.catena.2018.05.044

Cited by 26 publications

(10 citation statements)

References 42 publications

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“…In this research, a new scientific approach was developed to provide a gully erosion sensitivity map that does not require the location of gullies. This is very useful for areas that lack accurate data [81,82]. For this purpose, we confirmed that VIKOR MCDM models could be used and improved its efficiency and accuracy if the IoE bivariate model is integrated with it without comparing gullies data with each other.…”

Section: Discussionsupporting

confidence: 61%

Proposing a Novel Predictive Technique for Gully Erosion Susceptibility Mapping in Arid and Semi-arid Regions (Iran)

et al. 2019

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Gully erosion is considered to be one of the main causes of land degradation in arid and semi-arid territories around the world. In this research, gully erosion susceptibility mapping was carried out in Semnan province (Iran) as a case study in which we tested the efficiency of the index of entropy (IoE), the Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, and their combination. Remote sensing and geographic information system (GIS) were used to reduce the time and costs needed for rapid assessment of gully erosion. Firstly, a gully erosion inventory map (GEIM) with 206 gully locations was obtained from various sources and randomly divided into two groups: A training dataset (70% of the data) and a validation dataset (30% of the data). Fifteen gully-related conditioning factors (GRCFs) including elevation, slope, aspect, plan curvature, stream power index, topographical wetness index, rainfall, soil type, drainage density, distance to river, distance to road, distance to fault, lithology, land use/land cover, and soil type, were used for modeling. The advanced land observing satellite (ALOS) digital elevation model with a spatial resolution of 30 m was used for the extraction of the above-mentioned topographic factors. The tolerance (TOL) and variance inflation factor (VIF) were also included for checking the multicollinearity among the GRCFs. Based on IoE, we concluded that soil type, lithology, and elevation were the most significant in terms of gully formation. Validation results using the area under the receiver operating characteristic curve (AUROC) showed that IoE (0.941) reached a higher prediction accuracy than VIKOR (0.857) and VIKOR-IoE (0.868). Based on our results, the combination of statistical (IoE) models along with remote sensing and GIS can convert the multi-criteria decision-making (MCDM) models into efficient and powerful tools for gully erosion prediction. We strongly suggest that decision-makers and managers should use these kinds of results to develop more consistent solutions to achieve sustainable development on degraded lands such as in the Semnan province.

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Section: Discussionsupporting

confidence: 61%

Proposing a Novel Predictive Technique for Gully Erosion Susceptibility Mapping in Arid and Semi-arid Regions (Iran)

et al. 2019

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“…In contrast to previous gully erosion studies (Prosser and Slade, 1994;Inoubli et al, 2016;Ben Slimane et al, 2018), sediment generation in the studied gully was predominantly by the mass displacement process due to the erosion of the gully side walls. These results are similar to those found by De Rose et al (1998) and Betts et al (2003).…”

Section: Source Of Sediments In the Gullycontrasting

confidence: 91%

“…Traditional methods such as pins (Desir and Marín, 2007), microtopographic profiles (Casalí et al, 2006), surveys with total stations (Ehiorobo and Audu, 2012) and poles are being replaced by techniques based on high-resolution photogrammetry (Castillo et al, 2012). Several studies have quantified gully erosion through photogrammetry associated with three-dimensional soil surface reconstruction methods, such as structure-from-motion/multiview-stereo (SfM-MVS) (Castillo et al, 2012;Gómez-Gutiérrez et al, 2014;Kaiser et al, 2014;Di Stefano et al, 2017;Ben Slimane et al, 2018;Siqueira Junior et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Sediment source and volume of soil erosion in a gully system using UAV photogrammetry

Cândido¹,

James²,

Quinton³

et al. 2020

Revista Brasileira De Ciência Do Solo

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“…( a ) The relationship between image resolution and minimal identifiable gully width, which were collected from following literature: [3,11,26,30,35,39,41,62,63,64]. ( b ) The width range of gullies that were accurately and inaccurately delineated from Pleiades image, respectively, which were divided according to the standard determined in Section 4.1.…”

Section: Figurementioning

confidence: 99%

Accuracy Assessment of the Planar Morphology of Valley Bank Gullies Extracted with High Resolution Remote Sensing Imagery on the Loess Plateau, China

Chen

Jiao

Wei

et al. 2019

IJERPH

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Gully erosion is a serious environmental problem worldwide, causing soil loss, land degradation, silting up of reservoirs and even catastrophic flooding. Mapping gully features from remote sensing imagery is crucial for assisting in understanding gully erosion mechanisms, predicting its development processes and assessing its environmental and socio-economic effects over large areas, especially under the increasing global climate extremes and intensive human activities. However, the potential of using increasingly available high-resolution remote sensing imagery to detect and delineate gullies has been less evaluated. Hence, 130 gullies occurred along a transect were selected from a typical watershed in the hilly and gully region of the Chinese Loess Plateau, and visually interpreted from a Pleiades-1B satellite image (panchromatic-sharpened image at 0.5 m resolution fused with 2.0 m multi-spectral bands). The interpreted gullies were compared with their measured data obtained in the field using a differential global positioning system (GPS). Results showed that gullies could generally be accurately interpreted from the image, with an average relative error of gully area and gully perimeter being 11.1% and 8.9%, respectively, and 74.2% and 82.3% of the relative errors for gully area and gully perimeter were within 15%. But involving field measurements of gullies in present imagery-based gully studies is still recommended. To judge whether gullies were mapped accurately further, a standard adopting one-pixel tolerance along the mapped gully edges was proposed and proved to be practical. Correlation analysis indicated that larger gullies could be interpreted more accurately but increasing gully shape complexity would decrease interpreting accuracy. Overall lower vegetation coverage in winter due to the withering and falling of vegetation rarely affected gully interpreting. Furthermore, gully detectability on remote sensing imagery in this region was lower than the other places of the world, due to the overall broken topography in the Loess Plateau, thus images with higher resolution than normally perceived are needed when mapping erosion features here. Taking these influencing factors (gully dimension and shape complexity, vegetation coverage, topography) into account will be favorable to select appropriate imagery and gullies (as study objects) in future imagery-based gully studies. Finally, two linear regression models were built to correct gully area (Aip, m2) and gully perimeter (Pip, m) visually extracted, by connecting them with the measured area (Ams, m2) and perimeter (Pms, m). The correction models were Ams=1.021Aip+0.139 and Pms=0.949Pip+ 0.722, respectively. These models could be helpful for improving the accuracy of interpreting results, and further accurately estimating gully development and developing more effective automated gully extraction methods on the Loess Plateau of China.

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Combining field monitoring and aerial imagery to evaluate the role of gully erosion in a Mediterranean catchment (Tunisia)

Cited by 26 publications

References 42 publications

Proposing a Novel Predictive Technique for Gully Erosion Susceptibility Mapping in Arid and Semi-arid Regions (Iran)

Proposing a Novel Predictive Technique for Gully Erosion Susceptibility Mapping in Arid and Semi-arid Regions (Iran)

Sediment source and volume of soil erosion in a gully system using UAV photogrammetry

Accuracy Assessment of the Planar Morphology of Valley Bank Gullies Extracted with High Resolution Remote Sensing Imagery on the Loess Plateau, China

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