Literature DB >> 21232843

The repeatability of vegetation classification and mapping.

S M Hearn1, J R Healey, M A McDonald, A J Turner, J L G Wong, G B Stewart.   

Abstract

The mapping of habitats as defined by plant communities is a common component of the planning and monitoring of conservation management. However, there are major concerns about the subjectivity and risk of observer bias in most commonly used plant community mapping protocols. This study provides the first test of the consistency of habitat maps based on the mapping units defined by the National Vegetation Classification (NVC), the most widely used classification of plant communities used for habitat mapping on conservation sites in the UK. Seven surveyors mapped the same upland site within five weeks in summer 2008 and the spatial correspondence of the resulting maps was assessed. The NVC is a hierarchical classification and pair-wise spatial agreement between maps decreased with lower levels of sub-classification. The average area of agreement between maps was 77.6% at the habitat level, 34.2% at the community level and 18.5% at the sub-community level. Spatial disparity in the location of mapped boundaries between vegetation types only made a small contribution to overall differences; the majority of variation between maps was due to discrepancies in classification, with vegetation types containing similar species composition most often confused. Factors relating to surveyor effort (cost, time taken and length of route) were not able to explain the substantial differences between maps. However, the methods used to assign areas to vegetation type did seem to have an effect, with surveyors who relied primarily on their own experience having the highest levels of mean agreement with other maps. The study raises serious concerns with current practice of using the NVC for site description and monitoring/surveillance. Since this is just a single case study, we recommend that further work is carried out with the aim of determining the degree and source of variation between surveyors and how consistency can be increased.
Copyright © 2010 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2011        PMID: 21232843     DOI: 10.1016/j.jenvman.2010.11.021

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  2 in total

1.  Remotely sensing the German Wadden Sea-a new approach to address national and international environmental legislation.

Authors:  Gabriele Müller; Kerstin Stelzer; Susan Smollich; Martin Gade; Winny Adolph; Sabrina Melchionna; Linnea Kemme; Jasmin Geißler; Gerald Millat; Hans-Christian Reimers; Jörn Kohlus; Kai Eskildsen
Journal:  Environ Monit Assess       Date:  2016-09-28       Impact factor: 2.513

2.  Classifying grass-dominated habitats from remotely sensed data: The influence of spectral resolution, acquisition time and the vegetation classification system on accuracy and thematic resolution.

Authors:  Ute Bradter; Jerome O'Connell; William E Kunin; Caroline W H Boffey; Richard J Ellis; Tim G Benton
Journal:  Sci Total Environ       Date:  2019-11-03       Impact factor: 7.963

  2 in total

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