Structure from Motion with Multi-View Stereo photogrammetry (SfM-MVS) is increasingly used in geoscience investigations, but has not been thoroughly tested in gullied savanna systems. The aim of this study was to test the accuracy of topographic models derived from aerial (via Unmanned Aerial Vehicle, ‘UAV’) and ground-based (via handheld digital camera, ‘ground’) SfM-MVS in modelling hillslope gully systems in a dry-tropical savanna, and to assess the strengths and limitations of the approach at a hillslope scale and an individual gully scale. UAV surveys covered three separate hillslope gully systems (with areas of 0.412–0.715 km2), while ground surveys assessed individual gullies within the broader systems (with areas of 350–750 m2). SfM-MVS topographic models, including Digital Surface Models (DSM) and dense point clouds, were compared against RTK-GPS point data and a pre-existing airborne LiDAR Digital Elevation Model (DEM). Results indicate that UAV SfM-MVS can deliver topographic models with a resolution and accuracy suitable to define gully systems at a hillslope scale (e.g., approximately 0.1 m resolution with 0.4–1.2 m elevation error), while ground-based SfM-MVS is more capable of quantifying gully morphology (e.g., approximately 0.01 m resolution with 0.04–0.1 m elevation error). Despite difficulties in reconstructing vegetated surfaces, uncertainty as to optimal survey and processing designs, and high computational demands, this study has demonstrated great potential for SfM-MVS to be used as a cost-effective tool to aid in the mapping, modelling and management of hillslope gully systems at different scales, in savanna landscapes and elsewhere.

Structure from Motion with Multi-View Stereo photogrammetry (SfM) is increasingly utilised in geoscience investigations as a cost-effective method of acquiring high resolution (sub-meter) topographic data, but has not been thoroughly tested in gullied savanna systems. The aim of this study was to test the accuracy of topographic models derived from aerial (via an Unmanned Aerial Vehicle, ‘UAV’) and ground-based (via a handheld digital camera, ‘Ground’) SfM in modelling a hillslope gully system in dry-tropical savanna, and to assess the strengths and limitations of the approach at different scales. A UAV survey covered an entire hillslope gully system (0.715 km2), whereas a Ground survey covered a single gully within the broader system (650 m2). SfM topographic models, including Digital Surface Models (DSM) and dense point clouds, were compared against RTK-GPS point data and a pre-existing airborne LiDAR Digital Elevation Model (DEM). Results indicate UAV SfM can deliver topographic models with a resolution and accuracy suitable to define gully systems at a hillslope scale (e.g., 0.1 m resolution with ~ 0.5 – 1.3 m elevation error), while ground-based SfM is more capable of quantifying gully morphology (e.g., 0.01 m resolution with ~ 0.1 m elevation error). Key strengths of SfM for these applications include: the production of high resolution 3D topographic models and ortho-photo mosaics, low survey instrument costs (< $AUD 3,000); and rapid survey time (4 and 2 hours for UAV and Ground survey respectively). Current limitations of SfM include: difficulties in reconstructing vegetated surfaces; uncertainty as to optimal survey and processing designs; and high computational demands. Overall, this study has demonstrated great potential for SfM to be used as a cost-effective tool to aid in the mapping, modelling and management of hillslope gully systems at different scales, in tropical savanna landscapes and elsewhere.

In tropical dairy production systems, where high rates of urea fertiliser are applied, little is known about nitrogen (N) fertiliser response, fertiliser-use efficiency and losses to the environment. This study aimed to determine the effects of N fertiliser (urea) application rate and a nitrification inhibitor (3, 4-dimethylpyrazole phosphate, DMPP) on pasture yield and N losses in a dairy production system in North Queensland, Australia. The experiment was a factorial design with two fertiliser rates (industry standard per application 57 kg N ha–1 or half that, applied ~3-weekly), two DMPP rates (0 or 4.86 g kg–1 urea) and four replicates, completed over 1 year. Urea applied at half the industry standard rate, together with DMPP, provided annual dry matter pasture yields (11 462 kg ha–1) not significantly different from those when urea was applied at the higher rate, with or without DMPP (10 691 and 11 156 kg ha–1, respectively). The low rate of urea without DMPP had the lowest annual dry matter yield (8386 kg ha–1). Most of the fertiliser N lost from the system appeared to be via leaching, with loss in surface runoff minimal. During the ryegrass phase, an experiment with 15N labelling showed that, 3 months after application, 27–39% of the applied N had been taken up by the pasture, 23–45% was recovered in the soil, and 18–40% had been lost. Emission of N2O peaked within a day of fertiliser application, and DMPP did not reduce emissions during that period. The findings indicate good potential for farmers to use DMPP-treated urea as a means of reducing N fertiliser rates without loss of productivity and with less loss of N to the environment.