The requested URL was not found on this server. That's all we know. You could try using the Front Page or do a Search or read the most current stories below. © 2017 All Rights Reserved.Soil erosion is a serious environmental problem which causes high economic costs [1]. Many approaches have been proposed for monitoring and predicting soil erosion at different scales [2,3,4,5]. Gully erosion, the main type of soil erosion by water, is a major land degradation process that adversely affects land management and agriculture [6]. In the past century, an increasing number of researches focus on the gully erosion due to its ubiquity and severity [7]. Evaluation of gully-affected areas is the basis for control and monitoring of gully erosion; as such, detection of these areas has become a growing interest in gully erosion community [8,9,10].Gully extraction method depends on the development of geographic data acquisition. Field investigation is the most traditional method. In the early stage, tapes, rulers, and micro-topographic profilers are commonly used [11,12].

Recently, latest measurement technologies, such as terrestrial laser scanning (TLS) [13], airborne laser scanning (ALS) [14], 3D photo-reconstruction [15], and total station [16], are adopted. Both TLS and ALS are able to efficiently acquire high resolution dataset for erosion monitoring and related fluvial geomorphology studies [3,17,18]. Recent experiments in different regions including Australia, Peru, and England prove that the TLS gains more adoption than ALS for catchment-scale studies because it is more flexible and accurate [19,20,21]. However, the heavy fieldwork complicates the application of such method for a large region [18].With a large number of earth observation satellites launched, abundant imagery can be used to assess gully erosion [22]. Optical satellite sensors, including the medium-resolution imagery (e.g., Landsat and Spot) and high-resolution imagery (e.g., IKONOS and Quick Bird), are increasingly available. The current frequently used imageries in geoscience are Worldview-3 and Pleiades [23,24], with a ground sampling distance in panchromatic mode of 0.31 and 0.5 m, and 1.00 and 2.00 m in multispectral mode, respectively.

Remote sensing based method for extracting gully features shows two advantages over field investigation. On the one hand, multi-temporal and multi-resolution geographic data covering almost the world are easily obtained [25,26,27]. On the other hand, remote sensing not only provides spectrum and texture information but also generates the digital elevation models (DEMs) when the satellite possesses stereoscopic capabilities [28,29]. Remote sensing is mainly carried out on satellite or manned aircraft, which are good options for regional-scale data acquisition because of their wide coverage and stable performance [30]. Nevertheless, the application of conventional platforms is limited for the increasing demanding of environmental modeling at catchment scale because of their high cost, low flexibility, and poor spatial and temporal resolution [31].The use of unmanned aerial vehicle (UAV) can bridge the gap between field investigation and satellite and aircraft-based remote sensing [32]. UAV-based remote sensing is suitable for catchment-scale surveys, which is more flexible than traditional remote sensing.

Recently, many publications prove that UAV can be regarded as a credible tool for monitoring soil erosion [33], coastal area [34], precision agriculture [35], glacier dynamic [36], and landslide [37], in which the created high-resolution DEM and ortho-image mosaics can provide further detailed information.ar drone flight recorder qgroundcontrolAs the method for data acquisition transfers from the field investigation to remote sensing, the extraction method also improves greatly. parrot ar drone mk1In the early stage, visual interpretation, which is based on the spectrum difference and interpreter’s knowledge, is the main choice [38,39]. parrot ar drone szervízHowever, manual interpretation is restricted to low efficiency and uncertainty which has been replaced by automatic method. ar drone 2 hepsiburada

Pixel and object-based are two kinds of automatic method for gully feature extraction. Although, the pixel-based method has been applied in many studies [40,41], the object-based method is proven to be more advanced because it can integrate the spectral, shape, and textural information instead of spectral information only [42,43]. parrot ar drone napoliThe recent papers show that object-based method is the mainstream in processing high-resolution imagery [44,45,46,47].parrot ar drone segunda manoAlthough UAV shows potential in gully features extraction at catchment scale, existing studies are conducted in limited regions, such as Morocco [32] and Saxon loess province [33]. According to experiments all over the world, the contribution of gully erosion to overall soil loss rates and sediment production rates by water erosion range from 10% to 94% [6].

Significant differences in gully erosion conditions lead to varying gully sizes, shapes, and densities in different regions. Thus, further studies are needed to investigate UAV-based method for gully feature extraction in other typical areas.The Chinese Loess Plateau is known for its serious soil erosion and land degradation, which are caused by both natural and anthropogenic factors [48]. Gully erosion in this region accounts for 60%–70% of the total soil loess [49], with a large number of developed gullies shaping the distinct loess landform [50]. The Loess shoulder-lines divide the total area into upland and gully-affected areas with totally different topographic signatures, land use, and types of soil erosion [51]. Gullies in this region can be divided into three types: floor, bank and hillslope gullies [52]. Although some studies have discussed the extraction of gully features in Chinese Loess Plateau, specifically on catchment scale [53,54,55], the use of UAV is currently limited.