Mapping scrub vegetation cover from photogrammetric point clouds: a useful tool in reserve management

Vafidis, Jim, Lucksted, Isaac, Gall, Moyrah, Maxfield, Pete, Meakin, Kathy and Steer, Mark 2021. Mapping scrub vegetation cover from photogrammetric point clouds: a useful tool in reserve management. Ecology and Evolution 11 (11) , pp. 6789-6797. 10.1002/ece3.7527

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Abstract

Scrub vegetation is a valuable habitat and resource for wildlife, but if unmanaged can encroach and dominate adjacent habitats, reducing biodiversity value. A primary task in the management of terrestrial nature reserves in the UK is monitoring and controlling scrub. The methods used to monitor and assess scrub cover are often basic, relying on qualitative assessment. Inaccurate assessments may fail to inform appropriate management of the habitats and lead to loss or degradation of important ecological features. Scrub can be monitored using UAV or satellite-derived imagery, but it can be difficult to distinguish between other vegetation types without using high-cost hyperspectral sensors. An alternative method using high-resolution surface models from photogrammetric point clouds enables the isolation of vegetation types based on height. Scrub can be isolated from woodland, hedgerows, and tall ground vegetation. In this study, we calculate scrub cover using a photogrammetric point cloud modeling approach using UAVs. We illustrate the method with two case studies from the UK. The scrub cover at Daneway Banks, a calcareous grassland site in Gloucestershire, was calculated at 21.8% of the site. The scrub cover at Flat Holm Island, a maritime grassland in the Severn Estuary, was calculated at 7%. This approach enabled the scrub layer to be readily measured and if required, modeled to provide a visual guide of what a projected management objective would look like. This approach provides a new tool in reserve management, enabling habitat management strategies to be informed, and progress toward objectives monitored.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Biosciences
Publisher:	Wiley
ISSN:	2045-7758
Date of Acceptance:	19 March 2021
Last Modified:	06 Dec 2024 11:30
URI:	https://orca.cardiff.ac.uk/id/eprint/172844

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