nerc.ac.uk

Can digital image classification be used as a standardised method for surveying peatland vegetation cover?

Baxendale, Catherine L.; Ostle, Nick J.; Wood, Claire M.; Oakley, Simon; Ward, Susan E.. 2016 Can digital image classification be used as a standardised method for surveying peatland vegetation cover? [in special issue: Assessing ecosystem resilience through long term ecosystem research: observations from the first twenty years of the UK Environmental Change Network] Ecological Indicators, 68. 150-156. https://doi.org/10.1016/j.ecolind.2015.11.035

Before downloading, please read NORA policies.
[img]
Preview
Text
N512208PP.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0.

Download (446kB) | Preview

Abstract/Summary

The ability to carry out systematic, accurate and repeatable vegetation surveys is an essential part of long-term scientific studies into ecosystem biodiversity and functioning. However, current widely used traditional survey techniques such as destructive harvests, pin frame quadrats and visual cover estimates can be very time consuming and are prone to subjective variations. We investigated the use of digital image techniques as an alternative way of recording vegetation cover to plant functional type level on a peatland ecosystem. Using an established plant manipulation experimental site at Moor House NNR (an Environmental Change Network site), we compared visual cover estimates of peatland vegetation with cover estimates using digital image classification methods, from 0.5 m × 0.5 m field plots. Our results show that digital image classification of photographs taken with a standard digital camera can be used successfully to estimate dwarf-shrub and graminoid vegetation cover at a comparable level to field visual cover estimates, although the methods were less effective for lower plants such as mosses and lichens. Our study illustrates the novel application of digital image techniques to provide a new way of measuring and monitoring peatland vegetation to the plant functional group level, which is less vulnerable to surveyor bias than are visual field surveys. Furthermore, as such digital techniques are highly repeatable, we suggest that they have potential for use in long-term monitoring studies, at both plot and landscape scales.

Item Type: Publication - Article
Digital Object Identifier (DOI): https://doi.org/10.1016/j.ecolind.2015.11.035
CEH Sections/Science Areas: CEH Fellows
Parr
Shore
ISSN: 1470-160X
Additional Keywords: digital imaging, peatlands, vegetation survey, plant functional type, long-term monitoring, Moor House NNR
NORA Subject Terms: Ecology and Environment
Computer Science
Date made live: 16 Dec 2015 11:41 +0 (UTC)
URI: http://nora.nerc.ac.uk/id/eprint/512208

Actions (login required)

View Item View Item

Document Downloads

Downloads for past 30 days

Downloads per month over past year

More statistics for this item...