Abstract Geographic information systems make it possible to obtain fine scale maps for environmental monitoring from airborne sensors on aerial platforms, such as unmanned aerial vehicles (UAVs), which offer products with low costs and high space-time resolution. The present study assessed the performance of an UAV in the evaluation of the seasonal behavior of five vegetation coverages: Coffea spp., Eucalyptus spp., Pinus spp. and two forest remnants. For this, vegetation indices (Excess Green and Excess Red minus Green), meteorological data and moisture of surface soils were used. In addition, Sentinel-2 satellite images were used to validate these results. The highest correlations with soil moisture were found in coffee and Forest Remnant 1. The Coffea spp. had the indices with the highest correlation to the studied soil properties. However, the UAV images also provided relevant results for understanding the dynamics of forest remnants. The Excess Green index (p = 0.96) had the highest correlation coefficients for Coffea spp., while the Excess Red minus Green index was the best index for forest remnants (p = 0.75). The results confirmed that low-cost UAVs have the potential to be used as a support tool for phenological studies and can also validate satellite-derived data.

ABSTRACT Gully erosion is a severe way of land degradation. Gullies threaten the sustainability of agro-ecosystems, causing quantitative and qualitative reduction of groundwater, farmland productivity, and waterways sedimentation. Since the gully development on the surface begins with water flow and sheet erosion, accurate monitoring of the erosive processes in a gully system and its quantification is key for the development of effective strategies to control soil erosion in gullies. Here, we demonstrate the first use of unmanned aerial vehicle (UAV) and structure-from-motion/multiview-stereo photogrammetry to evaluate the relative contribution of the different types of erosion (sheet, rill, and gully sidewall) in the gully development. A gully located at Lavras, Brazil, was surveyed using a UAV equipped with a RGB camera. The Precision Maps (PM) variant of the Multiscale Model to Model Cloud Compare (M3C2) algorithm was used to calculate spatial changes in the soil surface topography and to quantify the volumes of sediments lost and gained in the gully system. The point clouds showed root mean square errors of order ~ 3 mm on xyz on check points. The spatial variation of precision along the gully ranged from 0.006 to 0.276 m, considering the M3C2-PM uncertainty values. The results revealed that the main source of sediment in the gully studied was due to the mass movement processes. Rills and laminar erosions contributed 8 and 3 %, respectively, to the total sediment yield, while the mass movements corresponded with most of the sediment generation in the gully. Of the total sediment produced in the system, only 24 % was stored in the gully, indicating its high activity and instability. For the first time, the sediment sources of a gully were quantified remotely and with millimetric precision. The UAV photogrammetry generated high-resolution measurements, allowing evaluation of the contribution of sheet erosion in the generation of sediment of the gully. This opens up new possibilities in the studies involving the dynamics of gullies, since the understanding of the spatial and temporal behaviour of the erosive processes are important in the development of control strategies and monitoring of the evolution of a gullies complex.

ABSTRACT The use of Unmanned Aerial Vehicles (UAVs) and Structure from Motion (SfM) techniques can contribute to increase the accessibility, accuracy, and resolution of Digital Elevation Models (DEMs) used for soil erosion monitoring. This study aimed to evaluate the use of four DEMs obtained over a year to monitor erosion processes in an erosion-degraded area, with occurrence of rill and gully erosions, and its correlation with accumulated rainfall during the studied period. The DEMs of Geomorphic Change Detection (GCD) of horizontal and vertical resolutions of 0.10 and 0.06 m were obtained. It was possible to detect events of erosion and deposition volumes of the order of 2 m3, with a volumetric error of ∼50 %, in rills and gullies in the initial stage denominated R and GS-I, respectively. Events of the order of 100 m3, with a volumetric error around 14 % were found for advanced gullies, a segment denominated GS-II. In the three studied erosion situations, the deposition volume increased with the accumulated rainfall. The segments R and GS-I presented an inverse relationship between erosion volume and accumulated rainfall during the studied period. This behaviour can be explained by the dynamics of the deposition and erosion volumes during the erosion process. In the GS-II segment, erosion and deposition volumes were proportional and a direct relation with the cumulative rainfall over the studied period and a low percentage of volumetric error were found.