Bradter, U, O'Connell, J, Kunin, WE orcid.org/0000-0002-9812-2326 et al. (3 more authors) (2020) Field spectroscopy data from non-arable, grass-dominated objects in an intensively used agricultural landscape in East Anglia, UK. Data in Brief, 28. 104888. ISSN 2352-3409
Abstract
Remote sensing of vegetation provides important information for ecological applications and environmental assessments. The association between vegetation composition and structure with its spectral signal can most fully be assessed with hyperspectral data. Particularly field spectroscopy data can improve such understanding as the spectral data can be linked with the vegetation under consideration without the geographic registration uncertainties of aerial or satellite imagery. The data provided in this article contain field spectroscopy measurements from non-arable, grass-dominated objects on four farms in an intensively used agricultural landscape in the South-East of the UK. Detailed data on the plant species composition of the objects are also supplied with this article to support further analysis. Reuse potential includes linking the vegetation data with the spectral response using spectral unmixing techniques to map certain plant species or including the field spectroscopy data in a larger study with data from a wider area. This data article is related to the paper ‘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’ (Bradter et al., 2019) in which the ability to classify the recorded vegetation from the field spectroscopy data was analysed.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2019 The Author(s). Published by Elsevier Inc. This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/) |
Keywords: | Classification; Hyperspectral; National vegetation classification (NVC); Plant species composition; Spectral; Vegetation |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Biology (Leeds) |
Funding Information: | Funder Grant number BBSRC (Biotechnology & Biological Sciences Research Council) BB/J005851/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 07 Jan 2020 14:12 |
Last Modified: | 07 Jan 2020 14:12 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.dib.2019.104888 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:155242 |