2.2 Drone survey and geospatial analysis
To develop a topographic digital surface model (DSM) of the study area using photogrammetry, a drone photographic survey was undertaken using a Phantom Potensic T25 drone equipped with internal GPS and a 1080p GPS digital RGB camera with an optimized 120° wide-angle lens. The flightpath was set to take photographs from an altitude of 400m, reduced to 150 m over hill top areas that were obscured by cloud cover. The flightpath was set so that images had greater than 65% overlap. Twelve ground-based GPS reference points were made along the boundaries of the designated area to permit vertical alignment of relative elevations derived from the drone survey. A Digital Elevation Model (DEM) was created using photogrammetric routines within Agisoft Metashape whereby building and tree interference was removed from the DSM by excluding points that had a steep (>80°) angle with adjacent point.
The red, green and blue bands of a compile orthomosaic aerial image of the study area were used as the input for a maximum likelihood classification using the QGIS 3.4 saga tool Supervised Classification for Grids’. Training data were generated through heads up digitisation of that aerial photograph. The output of this process successfully differentiated gullies and rills from other forms of ground cover but could not distinguish between the different vegetation communities present within the catchment. This high-resolution mapping of soil erosion features was therefore supplemented with a conventional aerial photograph interpretation exercise carried out at a scale of 1:3000. In addition to the classification of broad land cover types within the study area, cultivated land use was subject to a further level of classification according to the direction of cultivation. This categorisation was undertaken as a simple aerial image interpretation (at a scale 1:500) with discontinuities in land management practices being recorded as separate features (land parcels) within the GIS layer.
The 1m DEM of the site was analysed in QGIS 3.10 to produce a model of potential surface flow, slope aspect and slope degree. In order to simplify subsequent analyses, the aspect of each 1m pixel within the elevation model were categorised into one of the 8 cardinal directions (N, NE, E, SE, S, SW, W, NW) These DEM derivatives were used as inputs in the following analyses. Mean slope degree and modal aspect were calculated for each parcel of cultivated land identified in the aerial photograph interpretation using QGis’s Zonal statistics tool. The direction of cultivation recorded in the aerial imagery interpretation was then compared with the modal aspect for each land use parcel and the relationship between the two described using these qualitative classes: cultivation along contours, cultivation with slope and intermediate cultivation – where the direction of cultivation had no strong relationship the aspect of the field. The modelled surface flow was used for two purposes, firstly to create a Strahler ordered model of potential overland flow convergence within the study area, and secondly to select those bare ground (interpreted as eroded) pixels within the landscape that were probably generated by surface flow i.e. rills and gully features (in the main visible in high resolution photography). The selected pixels were then converted into point data and their density expressed as area (m2) per m2calculated to derive an independent index of observed erosion feature density.