Weather Conditions, Weather Information and Car Crashes
Road traffic safety is the result of a complex interaction of factors, and causes behind road vehicle crashes require different measures to reduce their impacts. This study assesses how strongly the variation in daily winter crash rates associates with weather conditions in Finland. This is done by...
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doaj-8918adaa7fb3484093d9691a8b3727802020-11-24T23:20:09ZengMDPI AGISPRS International Journal of Geo-Information2220-99642015-11-01442681270310.3390/ijgi4042681ijgi4042681Weather Conditions, Weather Information and Car CrashesAdriaan Perrels0Athanasios Votsis1Väinö Nurmi2Karoliina Pilli-Sihvola3Finnish Meteorological Institute, P.O: Box 503, Helsinki 00101, FinlandFinnish Meteorological Institute, P.O: Box 503, Helsinki 00101, FinlandFinnish Meteorological Institute, P.O: Box 503, Helsinki 00101, FinlandFinnish Meteorological Institute, P.O: Box 503, Helsinki 00101, FinlandRoad traffic safety is the result of a complex interaction of factors, and causes behind road vehicle crashes require different measures to reduce their impacts. This study assesses how strongly the variation in daily winter crash rates associates with weather conditions in Finland. This is done by illustrating trends and spatiotemporal variation in the crash rates, by showing how a GIS application can evidence the association between temporary rises in regional crash rates and the occurrence of bad weather, and with a regression model on crash rate sensitivity to adverse weather conditions. The analysis indicates that a base rate of crashes depending on non-weather factors exists, and some combinations of extreme weather conditions are able to substantially push up crash rates on days with bad weather. Some spatial causation factors, such as variation of geophysical characteristics causing systematic differences in the distributions of weather variables, exist. Yet, even in winter, non-spatial factors are normally more significant. GIS data can support optimal deployment of rescue services and enhance in-depth quantitative analysis by helping to identify the most appropriate spatial and temporal resolutions. However, the supportive role of GIS should not be inferred as existence of highly significant spatial causation.http://www.mdpi.com/2220-9964/4/4/2681responsivenessroad vehicle crashestraffic safetyearly warningweather conditions |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Adriaan Perrels Athanasios Votsis Väinö Nurmi Karoliina Pilli-Sihvola |
spellingShingle |
Adriaan Perrels Athanasios Votsis Väinö Nurmi Karoliina Pilli-Sihvola Weather Conditions, Weather Information and Car Crashes ISPRS International Journal of Geo-Information responsiveness road vehicle crashes traffic safety early warning weather conditions |
author_facet |
Adriaan Perrels Athanasios Votsis Väinö Nurmi Karoliina Pilli-Sihvola |
author_sort |
Adriaan Perrels |
title |
Weather Conditions, Weather Information and Car Crashes |
title_short |
Weather Conditions, Weather Information and Car Crashes |
title_full |
Weather Conditions, Weather Information and Car Crashes |
title_fullStr |
Weather Conditions, Weather Information and Car Crashes |
title_full_unstemmed |
Weather Conditions, Weather Information and Car Crashes |
title_sort |
weather conditions, weather information and car crashes |
publisher |
MDPI AG |
series |
ISPRS International Journal of Geo-Information |
issn |
2220-9964 |
publishDate |
2015-11-01 |
description |
Road traffic safety is the result of a complex interaction of factors, and causes behind road vehicle crashes require different measures to reduce their impacts. This study assesses how strongly the variation in daily winter crash rates associates with weather conditions in Finland. This is done by illustrating trends and spatiotemporal variation in the crash rates, by showing how a GIS application can evidence the association between temporary rises in regional crash rates and the occurrence of bad weather, and with a regression model on crash rate sensitivity to adverse weather conditions. The analysis indicates that a base rate of crashes depending on non-weather factors exists, and some combinations of extreme weather conditions are able to substantially push up crash rates on days with bad weather. Some spatial causation factors, such as variation of geophysical characteristics causing systematic differences in the distributions of weather variables, exist. Yet, even in winter, non-spatial factors are normally more significant. GIS data can support optimal deployment of rescue services and enhance in-depth quantitative analysis by helping to identify the most appropriate spatial and temporal resolutions. However, the supportive role of GIS should not be inferred as existence of highly significant spatial causation. |
topic |
responsiveness road vehicle crashes traffic safety early warning weather conditions |
url |
http://www.mdpi.com/2220-9964/4/4/2681 |
work_keys_str_mv |
AT adriaanperrels weatherconditionsweatherinformationandcarcrashes AT athanasiosvotsis weatherconditionsweatherinformationandcarcrashes AT vainonurmi weatherconditionsweatherinformationandcarcrashes AT karoliinapillisihvola weatherconditionsweatherinformationandcarcrashes |
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