Classification of artificial light sources in the Yamal Peninsula, Western Siberia

DOI

This dataset and code are related to artificial light emissions in the arctic area. They are a supplement to the report "Capabilities and limitations of advanced optical satellite missions for snow, vegetation, and artificial light source applications in Arctic areas". Dataset: The Radiance Light Trends app was used to identify artificial light sources on the Yamal Peninsula in Russia. In order to determine whether a location was lit, a threshold of 5 nW/cm² sr (displayed in yellow in the Radiance Light Trends app) was defined. Visible band daytime imagery from Google Maps and Bing Maps was then used to identify what type of human activity was responsible for the light. The positions of the 78 lit areas and their light source classification are provided in a csv table and kmz file. The classes are defined as: industry, industry / flare, community, ship/ airport, road, water and unknown. This data publication includes the artificial light sources on the Yamal Penninsula (Western Siberia) in .csv and .kmz formats. Code: The data publication includes the python code "Arctic light pollution clustering script", which identifies areas with bright light emissions in the arctic. The script requires the monthly composite images from the Day/Night Band of the Visible Infrared Imaging Radiometer Suite produced by the Earth Observation Group as an input. These data are currently available here: https://eogdata.mines.edu/download_dnb_composites.html

Licence for the "Arctic light pollution clustering script": MIT LicenceCopyright (2020) Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Identifier
DOI https://doi.org/10.5880/GFZ.1.4.2019.007
Related Identifier https://doi.org/10.2312/gfz.1.4.2020.001
Metadata Access http://doidb.wdc-terra.org/oaip/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:doidb.wdc-terra.org:6825
Provenance
Creator Coesfeld, Jacqueline; Kyba, Christopher ORCID logo
Publisher GFZ Data Services
Contributor Coesfeld, Jacqueline; Kyba, Christopher
Publication Year 2020
Funding Reference Horizon 2020 Framework Programme, 689443
Rights Data: CC BY 4.0; Code: MIT Licence; http://creativecommons.org/licenses/by/4.0/; https://opensource.org/licenses/MIT
OpenAccess true
Representation
Language English
Resource Type Dataset
Format application/octet-stream
Size 2 Files
Discipline Geosciences
Spatial Coverage (65.846W, 66.819S, 74.108E, 73.623N); Yamal Peninsula, 2016