Transport data resources

According to the survey, 83% of councils indicated they held RAMM data. Data relating to traffic volumes and the maintenance standard of various roads is contained in RAMM. Road centreline data is an essential dataset for accessibility assessment and is the base of other datasets such as public transport, walking and cycling routes. Road centreline data is available at a national scale from a number of sources.

Road hierarchy information is a common part of council datasets with 81% of councils indicating they hold road hierarchy data. In many cases, this information is simply an attribute of the road centreline data, so entering road hierarchy data is a simple and inexpensive task once the hierarchy policy has been determined.

Where public transport services are provided by local councils, data relating to bus routes has a high capture rate. There is limited capture of associated public transport data such as fare sections, timetable information and bus stop facilities or public transport provided by private operators. Public transport data is traditionally held by regional councils as opposed to local councils, although often common sense defines which organisation holds and maintains this data.

Public bus data is generally updated as needed and data quality is guided by the quality of the road centreline data. GPS is often used along routes as a validation method. Real-time provision of bus information in 2008 was only provided in Christchurch; although at that time there were plans to implement this in Auckland and Wellington. Those other cities are in various stages of implementing real-time information.

Ferry service data is held by most councils that provide commuter ferry transport. This includes ferry routes, port locations and timetable information, and the data is updated as required.

Public commuter train data is not common as very few locations have commuter train services. Where they are in operation, commuter train data is held. The data held is high quality and is accompanied by train station point data and timetable information.

Cycle network data is held by councils that serve larger towns and cities. Off-road cycle networks have been captured by the majority of councils who hold cycle network data although other related information such as whether there are cycle racks on buses, cycle friendly intersections and bicycle travel times are not well captured.

The question regarding pedestrian access was not understood by many respondents of the survey. Despite this, 23% of councils indicated they hold pedestrian access data, with 13% indicating they hold off-road pedestrian access data. Several comments were made that pedestrian access data was assumed to be footpath information, which is held in RAMM databases. Related information such as road crossings, rest points and travel time are not well captured. Overall, walking data is not a common dataset among councils, and of those who do hold pedestrian access data, the datasets are not complete.

Thirty percent of councils indicated they model their transportation networks. Of this group, the majority model their own town or city. Most respondents run one large model rather than several small transport models and there is no clear preference between three step and four step models. The validation year for the models was generally 2001 or 2006 to coincide with census demographic data. Of those who run future forecasting transport models, the years used are generally 2011, 2016 and 2021, again coinciding with expected census years.

Transport modelling is carried out on all roads by the majority of those who undertake modelling. There were very few responses which indicated that only major or strategic roads are modelled. The majority of responses indicated a meshblock or a similar sized zone model is used. Very few responses indicated the use of area units or larger zones in transport models. This illustrates a preference for undertaking transport modelling at a high level of detail.