Assessment of Structural Differences in a Low-Stature Mediterranean-Type Shrubland Using Structure-From-Motion (SfM)
Structural traits of vegetation, derived from the three-dimensional distribution of plant elements, are closely linked to ecosystem functions such as productivity and habitat provision. While extensively studied in forest ecosystems, these traits remain understudied in low-stature systems such as Mediterranean-type shrublands. In this study we explore the use of structural metrics derived from small unmanned aerial system (UAS)-based 3D point clouds, generated using the structure-from-motion (SfM) photogrammetry technique, to assess post-fire vegetation structure and biodiversity in the fynbos biome of the Cape Floristic Region (CFR), South Africa. Fynbos is a fire-adapted shrubland that represents nearly 80% of plant species in the CFR, making post-disturbance monitoring critical for conservation. We extracted three structural metrics—canopy height, top rugosity, and surface gap ratio—and achieved ~85% accuracy in classifying 5 × 5 m subplots by burn year using a Multi-Layer Perceptron (MLP), with canopy height as the strongest predictor. Additionally, top rugosity and gap ratio significantly contributed to modeling percentage cover-based species diversity. Our findings demonstrate that UAS-derived structural metrics provide valuable information for characterizing vegetation recovery and biodiversity patterns in low-stature, fire-prone ecosystems. This approach can support ecological monitoring and inform conservation strategies in Mediterranean-type shrublands.
Authors
- Manisha Das Chaity (ORCID: https://orcid.org/0000-0002-7558-1474)
- Robert Chancia (ORCID: https://orcid.org/0000-0002-7867-7674)
- Jasper A. Slingsby (ORCID: https://orcid.org/0000-0003-1246-1181)
- Glenn R. Moncrieff (ORCID: https://orcid.org/0000-0002-0066-4371)
- Jan van Aardt (ORCID: https://orcid.org/0000-0002-3036-0088)
- Ramesh Bhatta (ORCID: https://orcid.org/0009-0005-2994-4915)
Institutions
- The Nature Conservancy (US)
- Rochester Institute of Technology (US)
- University of Cape Town (ZA)
- South African Environmental Observation Network (ZA)
Publication Details
- Journal
- Remote Sensing
- Published
- 2025-08-11
- DOI
- https://doi.org/10.3390/rs17162784
- Primary Topic
- Remote Sensing and LiDAR Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Aeronautics and Space Administration