Exploring the influence of road network structure on the spatial behaviour of cyclists using crowdsourced data (Record no. 11658)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02398nab a2200253 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20210416125617.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr aa aaaaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 210416b ||||| |||| 00| 0 eng d |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Orellana, Daniel |
| 9 (RLIN) | 45979 |
| 245 ## - TITLE STATEMENT | |
| Title | Exploring the influence of road network structure on the spatial behaviour of cyclists using crowdsourced data |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher, distributor, etc | Sage, |
| Date of publication, distribution, etc | 2019. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | Vol 46, Issue 7, 2019,(1314-1330 p.) |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This study explores the effect of the spatial configuration of street networks on movement patterns of users of a cycling monitoring app, employing crowdsourced information from OpenStreetMap and Strava Metro. Choice and Integration measures from Space Syntax were used to analyse the street network’s configuration for different radiuses. Multiple linear regression models were fitted to explore the influence of these measures on cycling activity at the street segment level after controlling other variables such as land use, household density, socio-economic status, and cycling infrastructure. The variation of such influence for different time periods (weekday vs. weekend) and trip purposes (commuting vs. sports) was also analysed. The results show a positive significant association between normalised angular choice (NACH) and cycling activity. Although the final regression model explained 5.5% of the log-likelihood of the intercept model, it represents an important improvement compared with the base (control-only) model (3.8%). The incidence rate ratio of NACH’s Z scores was 1.63, implying that for an increase of one standard deviation of NACH, there is an expected increment of about 63% in the total cyclist counts while keeping all other variables the same. These results are of interest for researchers, practitioners, and urban planners, since the inclusion of Space Syntax measures derived from available public data can improve movement behaviour modelling and cycling infrastructure planning and design. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Urban morphology, |
| 9 (RLIN) | 45980 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Big Data, |
| 9 (RLIN) | 42128 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | cycling movement, |
| 9 (RLIN) | 37551 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Space Syntax, |
| 9 (RLIN) | 45981 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | OpenStreetMap |
| 9 (RLIN) | 45982 |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Guerrero, Maria L |
| 9 (RLIN) | 45983 |
| 773 0# - HOST ITEM ENTRY | |
| Host Biblionumber | 11590 |
| Host Itemnumber | 15512 |
| Place, publisher, and date of publication | Sage 2019. |
| Title | Environment and Planning B: Urban Analytics and City Science |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1177/2399808319863810 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Articles |
No items available.