Cite this dataset as
Morrell, S.A.F., Hatchell, J., Wordingham, F., Bennie, J., Inston, M.J., Gaston, K.J. (2024). Model code to simulate animal behaviour in response to light. NERC EDS Environmental Information Data Centre. (Model). https://doi.org/10.5285/1b64b008-8c20-4dd4-bf54-bf1894767a56
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This model code is available under the terms of the Open Government Licence
Model code to simulate animal behaviour in response to light
Formats
R
Comma-separated values (CSV)
JSON
Text (TXT)
Python scripts
Shell scripts
TOML
EULUMDAT (.ldt)
OBJ
IES
Spatial information
- Study area
-
Provenance & quality
The geometry was generated using the Defra National LIDAR 2020 1m DTM and DSM products, in tandem with the Ordnance Survey VectorMap Local product for buildings. These meshes are checked for watertightness and correct orientation of normals.
The emission spectra are assembled from the LICA-UCM spectral catalogue, and the spectral reflectances are taken from version 7 of the USGS Spectral Library.
Citations
Correspondence/contact details
Authors
Other contacts
- Rights holder
-
University of Exeter
- Custodian
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NERC EDS Environmental Information Data Centreinfo@eidc.ac.uk
- Publisher
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NERC EDS Environmental Information Data Centreinfo@eidc.ac.uk
Additional metadata
- Topic categories
- biota
- Keywords
- ALAN , animal behaviour , Animal behaviour , ecology , Exeter , light , light pollution , model , Modelling , monte carlo radiative transfer
- Funding
- Natural Environment Research Council Award: NE/V000497/1
- Last updated
- 27 March 2024 15:48
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By accessing or using this dataset, you agree to the terms of the relevant licence agreement(s). You will ensure that this dataset is cited in any publication that describes research in which the data have been used.
This model code is available under the terms of the Open Government Licence
CITE AS: Morrell, S.A.F.; Hatchell, J.; Wordingham, F.; Bennie, J.; Inston, M.J.; Gaston, K.J. (2024). Model code to simulate animal behaviour in response to light. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/1b64b008-8c20-4dd4-bf54-bf1894767a56