Data of: a global time series of traffic volumes on extra-urban roads
Traffic on roads outside of urban areas (i.e. extra-urban roads) can have major ecological and environmental impacts on agricultural and natural areas. Yet, data on extra-urban traffic volumes is lacking in many regions. To address this data gap, we produced a global time-series of traffic volumes (...
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ETH Zurich
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ftethz:oai:www.research-collection.ethz.ch:20.500.11850/666313 2024-04-28T08:02:01+00:00 Data of: a global time series of traffic volumes on extra-urban roads van Strien, Maarten J. id_orcid:0 000-0002-4311-0926 Grêt-Regamey, Adrienne id_orcid:0 000-0001-8156-9503 van Strien, Maarten J. 2024-03-27 application/application/zip application/text/plain application/application/x-shapefile application/application/vnd.openxmlformats-officedocument.spreadsheetml.sheet application/application/xml application/application/dbase https://hdl.handle.net/20.500.11850/666313 https://doi.org/10.3929/ethz-b-000666313 en eng ETH Zurich info:eu-repo/grantAgreement/SNF/Projekte MINT/192018 http://hdl.handle.net/20.500.11850/666313 doi:10.3929/ethz-b-000666313 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International TRAFFIC ANALYSIS (TRANSPORTATION AND TRAFFIC) TRAFFIC FLOW (TRANSPORTATION AND TRAFFIC) info:eu-repo/semantics/other Dataset 2024 ftethz https://doi.org/20.500.11850/66631310.3929/ethz-b-000666313 2024-04-09T23:36:49Z Traffic on roads outside of urban areas (i.e. extra-urban roads) can have major ecological and environmental impacts on agricultural and natural areas. Yet, data on extra-urban traffic volumes is lacking in many regions. To address this data gap, we produced a global time-series of traffic volumes (Annual Average Daily Traffic; AADT) on all extra-urban highways, primary roads, and secondary roads for the years 1975, 1990, 2000 and 2015. We constructed time series of road networks from existing global datasets on roads, population density, and socio-economic indicators, and combined these with a large collection of empirical AADT data from all continents except Antarctica. We used quantile regression forests to predict the median and 5 % and 95 % prediction intervals of AADT on each road section. The validation accuracy of the model was high (pseudo-R2 = 0.7407) and AADT predictions from 1975 were also accurate. The resulting map series provides standardised and fine-scaled information on the development of extra-urban road traffic and has a wide variety of practical and scientific applications. ArcGIS Pro 2.9.5, Python and R Dataset Antarc* Antarctica ETH Zürich Research Collection |
institution |
Open Polar |
collection |
ETH Zürich Research Collection |
op_collection_id |
ftethz |
language |
English |
topic |
TRAFFIC ANALYSIS (TRANSPORTATION AND TRAFFIC) TRAFFIC FLOW (TRANSPORTATION AND TRAFFIC) |
spellingShingle |
TRAFFIC ANALYSIS (TRANSPORTATION AND TRAFFIC) TRAFFIC FLOW (TRANSPORTATION AND TRAFFIC) van Strien, Maarten J. id_orcid:0 000-0002-4311-0926 Grêt-Regamey, Adrienne id_orcid:0 000-0001-8156-9503 Data of: a global time series of traffic volumes on extra-urban roads |
topic_facet |
TRAFFIC ANALYSIS (TRANSPORTATION AND TRAFFIC) TRAFFIC FLOW (TRANSPORTATION AND TRAFFIC) |
description |
Traffic on roads outside of urban areas (i.e. extra-urban roads) can have major ecological and environmental impacts on agricultural and natural areas. Yet, data on extra-urban traffic volumes is lacking in many regions. To address this data gap, we produced a global time-series of traffic volumes (Annual Average Daily Traffic; AADT) on all extra-urban highways, primary roads, and secondary roads for the years 1975, 1990, 2000 and 2015. We constructed time series of road networks from existing global datasets on roads, population density, and socio-economic indicators, and combined these with a large collection of empirical AADT data from all continents except Antarctica. We used quantile regression forests to predict the median and 5 % and 95 % prediction intervals of AADT on each road section. The validation accuracy of the model was high (pseudo-R2 = 0.7407) and AADT predictions from 1975 were also accurate. The resulting map series provides standardised and fine-scaled information on the development of extra-urban road traffic and has a wide variety of practical and scientific applications. ArcGIS Pro 2.9.5, Python and R |
author2 |
van Strien, Maarten J. |
format |
Dataset |
author |
van Strien, Maarten J. id_orcid:0 000-0002-4311-0926 Grêt-Regamey, Adrienne id_orcid:0 000-0001-8156-9503 |
author_facet |
van Strien, Maarten J. id_orcid:0 000-0002-4311-0926 Grêt-Regamey, Adrienne id_orcid:0 000-0001-8156-9503 |
author_sort |
van Strien, Maarten J. |
title |
Data of: a global time series of traffic volumes on extra-urban roads |
title_short |
Data of: a global time series of traffic volumes on extra-urban roads |
title_full |
Data of: a global time series of traffic volumes on extra-urban roads |
title_fullStr |
Data of: a global time series of traffic volumes on extra-urban roads |
title_full_unstemmed |
Data of: a global time series of traffic volumes on extra-urban roads |
title_sort |
data of: a global time series of traffic volumes on extra-urban roads |
publisher |
ETH Zurich |
publishDate |
2024 |
url |
https://hdl.handle.net/20.500.11850/666313 https://doi.org/10.3929/ethz-b-000666313 |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
info:eu-repo/grantAgreement/SNF/Projekte MINT/192018 http://hdl.handle.net/20.500.11850/666313 doi:10.3929/ethz-b-000666313 |
op_rights |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International |
op_doi |
https://doi.org/20.500.11850/66631310.3929/ethz-b-000666313 |
_version_ |
1797573514384900096 |