Details
| Original language | English |
|---|---|
| Title of host publication | XXIV ISPRS Congress “Imaging today, foreseeing tomorrow”, Commission IV |
| Pages | 125-132 |
| Number of pages | 8 |
| Publication status | Published - 1 Jun 2022 |
| Event | 2022 24th ISPRS Congress on Imaging Today, Foreseeing Tomorrow, Commission IV - Nice, France Duration: 6 Jun 2022 → 11 Jun 2022 |
Publication series
| Name | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
|---|---|
| Publisher | International Society for Photogrammetry and Remote Sensing |
| Volume | XLIII-B4-2022 |
| ISSN (Print) | 1682-1750 |
Abstract
In this article traffic accidents in Germany are investigated based on different environmental impacting factors. These factors are related to the accident surrounding like road characteristics, weather information, population density as well as POIs. For this purpose different open data source are used, like OpenStreetMap and an open weather API. These input data sources are processed in order to generate different categories of features, describing the on-site situation of an accident. Using the k-means clustering, six clusters were identified. In a consecutive investigation, each cluster is not only described with respect to the feature space but also in regards to their spatial distribution. Based on these findings, a regional comparison is done across the state boarders of Germany.
Keywords
- Environmental context, External influences, Machine learning, Open data, Traffic accidents
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems
- Social Sciences(all)
- Geography, Planning and Development
Sustainable Development Goals
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XXIV ISPRS Congress “Imaging today, foreseeing tomorrow”, Commission IV. 2022. p. 125-132 (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives; Vol. XLIII-B4-2022).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - SPATIAL ANALYSIS OF EXTERNAL INFLUENCES ON TRAFFIC ACCIDENTS USING OPEN DATA
AU - Golze, J.
AU - Feuerhake, U.
AU - Sester, M.
PY - 2022/6/1
Y1 - 2022/6/1
N2 - In this article traffic accidents in Germany are investigated based on different environmental impacting factors. These factors are related to the accident surrounding like road characteristics, weather information, population density as well as POIs. For this purpose different open data source are used, like OpenStreetMap and an open weather API. These input data sources are processed in order to generate different categories of features, describing the on-site situation of an accident. Using the k-means clustering, six clusters were identified. In a consecutive investigation, each cluster is not only described with respect to the feature space but also in regards to their spatial distribution. Based on these findings, a regional comparison is done across the state boarders of Germany.
AB - In this article traffic accidents in Germany are investigated based on different environmental impacting factors. These factors are related to the accident surrounding like road characteristics, weather information, population density as well as POIs. For this purpose different open data source are used, like OpenStreetMap and an open weather API. These input data sources are processed in order to generate different categories of features, describing the on-site situation of an accident. Using the k-means clustering, six clusters were identified. In a consecutive investigation, each cluster is not only described with respect to the feature space but also in regards to their spatial distribution. Based on these findings, a regional comparison is done across the state boarders of Germany.
KW - Environmental context
KW - External influences
KW - Machine learning
KW - Open data
KW - Traffic accidents
UR - http://www.scopus.com/inward/record.url?scp=85132146307&partnerID=8YFLogxK
U2 - 10.5194/isprs-archives-XLIII-B4-2022-125-2022
DO - 10.5194/isprs-archives-XLIII-B4-2022-125-2022
M3 - Conference contribution
AN - SCOPUS:85132146307
T3 - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
SP - 125
EP - 132
BT - XXIV ISPRS Congress “Imaging today, foreseeing tomorrow”, Commission IV
T2 - 2022 24th ISPRS Congress on Imaging Today, Foreseeing Tomorrow, Commission IV
Y2 - 6 June 2022 through 11 June 2022
ER -