Mapping and spatial‐temporal assessment of gully density in the Middle Volga region, Russia

Abstract

A large‐scale mapping of gully density was carried out for the Middle Volga region of the Russian Plain (188 000 km2) based on the interpretation of aerial photographs (scale 1:17 000; surveys undertaken during 1956–1970). In addition, spatial‐temporal dynamic of gully density were assessed for some parts of the study area (the Udmurt Republic and the Mesha and Ulema River basins of Tatarstan), based on the interpretation of aerial photographs (survey 1986–1991) and high resolution satellite images (2012–2015). Information on factors potentially controlling gully formation and development were collected and a geographic information system (GIS) analysis was conducted. Results show the strong development of gullies in the study area over the 1956–1970 period with an average gully density of 0.21 km km−2. For the Udmurt region, we found that gully densities varied little in the period 1956–1986, during which the total active gully length reduced with only 2%. This period was characterized by low variable climatic conditions and a stable fraction of arable land with a relatively continuous crop rotation system. However, gully dynamics seems to have changed more strongly during recent decades. We found a strong (order of magnitude) reduction in active gully density for the period 2010–2015 as compared to 1986–1991. The main reason for this is likely the increasing winter air temperatures. This leads to a significant reduction in surface runoff during spring as a result of snowmelt. Nonetheless, in some regions (i.e. the Udmurt Republic in the taiga zone), the abandonment of arable land after 1991 likely plays a significant role. Likewise, a decline in the frequency of extreme rainfall events (> 50 mm) may have played a role. All of these factors contribute to a reduction of surface runoff to the gullies and their subsequent stabilization. © 2018 John Wiley & Sons, Ltd.

Spatial differentiation of gully clusters based on the regional scale: an example from northeastern China

“…Based on the high-resolution images by Google Earth attained in recent five years with spatial resolution of less than 2.0 m, the visual interpretations of gullies were conducted in ArcGIS software (version 10.4). An interpretation mark was created based on image tone, veins, contours, morphology, direction, topography, and vegetation status ( Golosov et al, 2018 ; Okwu-Delunzu et al, 2013 ; Wang et al, 2016 ). The gully thalwegs were digitized as polyline feature (linear elements) in ArcGIS ( Fig.…”

“…The spatial distribution of gullies is mostly characterized by gully density ( Golosov et al, 2018 ; Gurbanov & Ganieva, 2017 ; Guyassa et al, 2018 ; Li et al, 2007 ; Litvin et al, 2003 ), with an administrative area or watershed usually taken as the evaluation unit. Density mapping can express the spatial distribution of gullies ( Arabameri et al, 2018 ; Golosov et al, 2018 ). Gully density has characteristics of horizontal differentiation, vertical (elevation) differentiation, and slope and slope direction differentiation ( Li et al, 2017 ; Litvin et al, 2003 ; Wang et al, 2008 ; Xu et al, 2014 ).…”

Gully erosion processes, disciplinary fragmentation, and technological innovation

“…Many causes of gully erosion have been identified, and these include natural and human-induced soil erosion processes (Poesen et al, 2003;Valentin et al, 2005). Near-term global climate change, shifting land use, and increased population will potentially affect soil resources, aggravate gully erosion processes, and threaten agricultural productivity (Valentin et al, 2005;Golosov et al, 2018;Marzolff and Pani, 2018;Nichols et al, 2018;Poesen, 2018). These external drivers strengthen the importance of and increase the urgency for gully erosion research and the combined efforts of monitoring, modeling, and managing soil loss processes and landscape degradation (Poesen, 2018).…”

Mapping Cropland Abandonment in Mountainous Areas Using an Annual Land-Use Trajectory Approach

“…In general, aerial photographs have higher spatial resolutions than those of satellite images. When identifying the abandoned cropland in topographically variable areas, such as gullies [32] and terraces [33,34], aerial photographs have been adopted. For ultra-high resolution tasks, aerial photographs are very useful for identifying detailed information regarding abandoned cropland, such as the height of succession vegetation after land abandonment [35] and the forest transition from deforestation to afforestation [36].…”