Multispectral airborne imagery and associated classifications, training data and validation data, for mapping nectar-rich floral resources for pollinators, Northamptonshire, UK 2020
Data presented here include imagery with ground-sampling distances of 3 cm and 7 cm for March 2019, May 2019 and July 2019. Also included are the corresponding ground-truth training and verification data presented as shapefiles, as well as the classification output and other data relevant to the project such as the width of floral units. The imagery was acquired by Spectrum Aviation using A6D-100c (50mm) Hasselblad cameras with bayer filters, mounted on a Sky Arrow 650 manned aircraft. Ground-truth data for training maximum likelihood classifications and for verifying the accuracy of classifications were gathered within eight days of imagery acquisition. Ground-truth data were acquired from sown field margins and hedgerow surrounding one study field. This dataset was acquired from March to July 2019 at a farm in Northamptonshire, UK. Data were acquired as part of a NERC funded iCASE PhD studentship (NERC grant NE/N014472/1) based at the University of East Anglia and in collaboration with Hutchinsons Ltd. The aim of the research was to map the floral units of five nectar-rich flowering plant species using very high resolution multispectral imagery. Each species constitutes an important food resource for pollinators. The plant species in question were Prunus spinosa, Crataegus monogyna, Silene dioica, Centaurea nigra and Rubus fruticosus. Full details about this dataset can be found at https://doi.org/10.5285/cf68be0c-e969-4190-8ec6-abeedb51b42c
dataset
https://data-package.ceh.ac.uk/sd/cf68be0c-e969-4190-8ec6-abeedb51b42c.zip
name: Supporting information
description: Supporting information available to assist in re-use of this dataset
function: information
https://catalogue.ceh.ac.uk/datastore/eidchub/cf68be0c-e969-4190-8ec6-abeedb51b42c
name: Download the data
description: Download a copy of this data
function: download
https://catalogue.ceh.ac.uk/id/cf68be0c-e969-4190-8ec6-abeedb51b42c
doi:
eng
biota
environment
Land Cover
Habitats and Biotopes
publication
2008-06-01
creation
2012-10-29
DeWALT laser beam measure
semi-automatic classification
SCP plugin
QGIS version 3.4.15
red campion
hawthorn
bramble
blackthorn
common knapweed
hardhead
-0.8240000000000001
-0.711
52.308
52.245
2019-05-15
2020-07-08
publication
2021-07-26
notPlanned
Multispectral data were acquired across red, green, blue and near-infrared bands on 28 March, 15 May and 4 July. Prior to imagery acquisition, 40X60cm boards that were visible within the imagery were established within the margins surrounding one field at our study farm. These were used as ground-control points to locate clusters of floral units within the margins. Ground-truth data (i.e. the locations of floral units) were gathered within 8 days of imagery acquisition. The company that acquired the multispectral data (Spectrum Aviation) carried out orthorectification and stitched individual images together into an orthomosaic. Data values were kept in a raw digital number format. Between July 2019 and February 2021, further image processing, e.g. clipping of the image and removal of irrelevant spectral bands was carried out in QGIS. During the same timeframe, ground-truth data were divided into data to be used for training the classifications and for carrying out independent accuracy assessments. The maximum likelihood classifications were applied to the imagery with different iterations applied each time, i.e. the training sets were tweaked to increase classification accuracies.
publication
2010-12-08
Comma-separated values (CSV)
While the classifications, training and accuracy assessment data, floral unit data and edited imagery all come under the UEA and University of Cambridge IPR, PhD partner Hutchinsons acquired the original 3cm and 7cm images and should be acknowledged accordingly.
If you reuse this data, you should cite: Barnsley, S.B., Lovett, A.A., Dicks, L.V. (2021). Multispectral airborne imagery and associated classifications, training data and validation data, for mapping nectar-rich floral resources for pollinators, Northamptonshire, UK 2020. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/cf68be0c-e969-4190-8ec6-abeedb51b42c
University of East Anglia
author
University of East Anglia
author
University of Cambridge
author
University of East Anglia
pointOfContact
NERC EDS Environmental Information Data Centre
custodian
NERC EDS Environmental Information Data Centre
publisher
University of East Anglia
owner
University of Cambridge
owner
Environmental Information Data Centre
Lancaster Environment Centre, Library Avenue, Bailrigg
Lancaster
LA1 4AP
UK
pointOfContact
2023-02-09T11:08:54