Abstract
<p>In semi-arid to arid South-west Morocco, the endemic argan tree (<em>Argania spinosa</em>) forms open woodlands that are the basis of a traditional agroforestry system involving rain-fed agriculture, pasturing of goats, sheep and camels, and oil production. Due to the high grazing pressure, the trees show various morphological traits and growth forms that are strongly related to browsing intensity. The overall appearance of <em>Argania spinosa</em> ranges from trees with a large, round crown and single trunk, over multi-stem, umbrella-shaped and hourglass-shaped trees to heavily condensed cone-shaped cushions.</p><p>30 test sites of 1 ha each in argan woodlands of different degradation stages were surveyed with an unmanned aerial vehicle (UAV) and RGB optical camera using a dedicated flight scheme for capturing full 3D tree shape at approx. 1 cm resolution. Structure-from-Motion (SfM)-photogrammetric processing yielded dense 3D point clouds as well as ultra-high resolution (1.5 cm) digital surface models (DSMs), terrain models (DTMs), crown-height models (CHMs) and orthophoto mosaics. Tree height and crown size were extracted from the CHMs, and 3D point-cloud characteristics (point density, profile shape/layer structure) and canopy structures were analysed within a geographical information system (GIS). Using field-based reference data on tree architecture and browsing features of 2494 trees, we were able to assign characteristic combinations of the GIS-derived structural parameters to three browsing-intensity classes and thus classify each argan tree via the architectural shape captured in its UAV-based 3D point cloud. We found that the majority of argan trees at the study sites are characterised by high browsing intensities. The small percentage of trees in the minimum browsing class are mostly inaccessible to grazing livestock. We conclude that UAV-based remote sensing has a high potential for mapping structural indicators of tree degradation by herbivore browsing in open woodland environments.</p>
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