Author: Tonje Holm, Asplan Viak Stavanger as

Using GIS in Mobility and Accessibility Analysis

Abstract
In urban planning tasks, access to information about the location of companies with different characteristics, is of great importance. The Dutch urban planning concept, the ABC-concept, aim to describe the mobility profile of a company. This description is important in urban planning efforts. 

According to this, there is also a need for information about the accessibility to one zone from all other zones within a defined planning area, and how the accessibility changes with an alteration in land use and public transport services.

Asplan Viak Stavanger as, in cooperation with the Norwegian Public Road Administration Rogaland, has developed a PC-based method of analysis and visualization of mobility and accessibility to be used in urban planning.

To be used in mobility analysis, a company database is established, containing characteristics in accordance with the ABC-concept. To be used in accessibility analysis, car and public transport time-matrixes and population statistics from the complex traffic model TRIPS, are combined.

The paper is supposed to highlight the use of a PC-based method of supporting urban planning efforts as well as the sophisticated combination of Arc-software, Microsoft Office software and complex traffic models.

Software: ArcInfo, ArcView, Access, Excel, Gauss

Introduction
The Dutch urban planning concept, the ABC-concept, has the main issue: The right business in the right place. The ABC-concept rely on the terms mobility and accessibility.

Businesses and services attract traffic. The site («location») of an office or service facility is an important factor influencing traffic going to and coming away from it. An office situated next to a railway station will, for example, more readily attract commuters by train, while an office located next to a motorway will encourage car usage. Physical planning can influence the location of new offices; planning regulations also contribute to the «guiding» of traffic and mobility.

The increasing growth in the use of motorized transport is giving rise to numerous problems, and government policy is therefore aimed at cutting down on the avoidable use of cars and at stimulating public transport and the use of bicycles. One way of doing so is by means of the location policy: siting new businesses and services as far as possible in locations which can easily be reached by public transport or bicycle, and not only by car.

Of course, each company has different transport needs. A university must in the first instance be reachable by public transport and bicycle, while a distribution centre should above all be properly accessible to freight vehicles. For this reason, so called mobility profiles are drawn up for various types of companies. Locations are classified according to their accessibility profiles.

Terms
An accessibility profile indicates the quality of the accessibility of a location by public transport and by car. An accessibility profile is an account of a locations proximity of halts for public transport, its situation with regard to major arterial routes and parking facilities or limitations. Three types of locations are distinguished, concentrating on their accessibility by public transport (A-locations), by public transport and by car (B-locations) and primarily by car (C-locations).


«Accessibility»

The mobility profile is an account of the properties of businesses and services which are of importance to transport and traffic, both of people and goods. The mobility profile is the counterpart of the accessibility profile; their relation to one another is one of supply and demand. Companies with a certain mobility profile must be fitted into a location with a matching accessibility profile. The mobility profile should indicate what the opportunities are for a suitable location. In drawing up a mobility profile, attention is paid to the number of employees in a company in comparison to its surface area, its dependency on motorized transport in conducting its business, the number of visitors and its reliance on road haulage. In other words, the factors which determines its transport needs.

The Right Business In The Right Place
What type of business should occupy which location? Which mobility profile belongs to which accessibility profile?

A-locations are accessible chiefly by public transport; thus they are principally suitable for businesses to which many people come. In other words, for businesses and services with the following mobility profile:


The presence of a large number of employees creates opportunities for public transport in terms of commuter travel. A location with good public transport facilities will also persuade visitors to opt for public transport in the first instance.

B-locations are reachable both by car and by public transport. Mobility profile of suitable businesses is as follows:

 
C-locations are easily accessible by car. Suitable for businesses with the following mobility profile:


Services which attract large numbers of the public (hospitals, for example) are not suitable for C-locations; they are regarded as qualifying pre-eminently for A- and B-locations.

Mobility Analysis
The first step in mobility analysis, is the allocation of business/service groups according to accessibility profiles.

A-locations are labour intensive and/or visitor intensive business and services, like industry (administrative office activities), building (administrative office activities), service industries (public-oriented and administrative office activities), retail trade (urban district level or higher), commercial service sector (public-orientated and administrative office activities, not or only moderately car-dependent), catering industry (hotels etc.), government administration (public-orientated and administrative office activities), communication companies (public-orientated office activities), public utility companies (public orientated office activities), socio-cultural institutions, higher education, schools (primary and secondary education) serving a wider than local function, medical and veterinary services, and social services (administrative office activities).

B-locations are businesses and services with a moderate labour and/or visitor intensity and a moderate car-dependency, like hire companies, instruments and optical industry, repair of consumer goods, wholesale trade (administrative office activities), commercial service sector (administrative office activities, high car-dependency), transport companies (administrative office activities), clothing industry, graphics industry, synthetic threads and fibres industry, communications companies (administrative office activities, processing and distribution), public utility companies (administrative office activities), sport and recreational facilities, and social services (accommodation, therapy).

C-locations are businesses and services with a low labour and/or visitor intensity and a high rate of car-dependency and/or a high dependency on road haulage of goods, like petroleum industry, wood and furniture industry, chemical industry, base metals industry, paper industry, textile industry, metal products industry, leather industry etc., electrotechnical industry, machine industry, rubber and synthetics processing industry, food and luxury items industry, transport industry, wholesale trade (other goods), building materials etc., transport companies (workshop, depot, garage), wholesale trade (bulk goods), building (workshop, storage depot), service companies (production activities), and public utility companies (production).

 The allocation was established as a digital table by using the database management program Access.

 The second step is classification of companies. The digital table was then connected to a company database named «Geographic Informationsystem for Trade and Employment in Nord-Jæren». The informationsystem is established by Asplan Viak Stavanger, and contains company data, as the location of each company, business/service group, and accumulated employment data. The companies in the informationsystem are all geocoded. By connecting the digital table with the GIS for Trade and Employment in Nord-Jæren, each company was classified as an A-, B- or C-location.

 The next step is defining of zone relation of each company. The mobility analysis are supposed to describe the present situation of a zone, and determine whether it is a typical A-, B- or C-location zone. The result will occur differently by using different zone levels. Three different zone levels were tested:

The GIS for Trade and Employment in Nord-Jæren was added zone information by using ArcView. The operation was done by joining the company database with each zone level, which identified each company within a certain TRIPS-zone, ward and square. This operation is unique for a GIS, and require that the zone information is digital and geocoded. The square net was made in ArcInfo.

 The next step is transformation to table of zones. The GIS for Trade and Employment in Nord-Jæren, containing the classification of companies and the zone information was next handled in Excel. By use of the Pivot-function, the company database, with the single company as the information-attached unit, was converted to a table of zones, where the number of employees per A-/B-/C-category per zone unit was summarized. A table of zones, with the single zone as the information-attached unit, was produced for each zone level; TRIPS-zones, wards and square net.

 The single zone was classified as an A-, B- ,C- or X-category by logical expressions by the following criterias:


A: [Number of employees in A-locations] > 50%
B: [Number of employees in B-locations] > 50%
C: [Number of employees in C-locations] > 50%
X: [Number of employees in A-/B-/C-locations] =< 50%

Similarly, each zone was classified by employment intensity (0/1/2/3) by the following criterias with wards as the zone unit:


0: [Number of employees per km2] < 100
1: 100 < [Number of employees per km2] < 500
2: 500 < [Number of employees per km2] < 1000
3: [Number of employees per km2] > 1000

With square net as the zone unit each zone was classified by employment intensity (0/1/2/3/4/5) by the following criterias:


1: 0 < [Number of employees] < 10
2: 10 < [Number of employees] < 50
3: 50 < [Number of employees] < 100
4: 100 < [Number of employees] < 200
5: [Number of employees] > 200

Finally, the table of zones was imported to ArcView for visualization on maps. Each category was given different colors. A was given red and C was given blue, and B was given pink to illustrate the link between A: red and C: blue. Category X, which is a mix zone, was given grey which describes its neutrality. The employment intensity was visualized by color scale. Strong color represents high employment intensity and weak colors represents low employment intensity.

«Mobility

«Mobility

Accessibility Analysis
The first step in accessibility analysis is to calculate the accessibility of car and public transport. The calculation of accessibility describes the accessibility to a zone from all other zones within the study area. By calculating accessibility, travel time is used, including walking and waiting time, weighted by population data, and the result is average travel time to a single zone from all other zones.

The Norwegian Public Road Administration Rogaland are using the traffic model TRIPS. The accessibility analysis in Nord-Jæren are based on travel time data, population data and zone units from TRIPS.

The next step is classification of zones. Intervals of accessibility of car and public transport was defined as high, medium and low.

Accessibility

Car

Public transport

High

< 15 min.

< 80 min.

Medium

15 - 25 min.

80 - 100 min.

Low

> 25 min.

> 100 min.

Based on this, the ABC-matrix was used to classify each zone as an A-, B-, C-, D- or E-zone. The D- and E-zone was added to handle the situation where a zone has respectively low and high accessibility of both public transport and car.

 «ABC-matrix»

The calculation of accessibility of car and public transport was done by using the matrix management program Gauss.

The result of the calculations was imported to ArcView for visualization on maps. Each category was given different colors. A-categories in the areas with high public transport accessibility and low car accessibility was given red to illustrate the relation with A-locations in the mobility analysis. Similarly, the C-categories in the areas with low public transport accessibility and high car accessibility was given blue to illustrate the relation with C-locations in the mobility analysis. Category B, medium car- and public transport accessibility, was given pink to illustrate the link between A: red and B: blue. Category D, low car- and public transport accessibility, was given a green color which should give associations to nature and non-urban areas. Category E, high car- and public transport accessibility, was given strong yellow to be separated as the locations with high accessibility in general.

The accessibility analysis for Nord-Jæren was made for the present situation and a situation with enhanced public transport offer.

«Accessibility

«Accessibility

Author Information

Name: Tonje Holm
Title: Civil Engineer M.Sc.
Organization: Asplan Viak Stavanger as
Address: Ostervaag 7, N-4013 Stavanger, Norway
Telephone: +47 51 89 10 19
Fax number: +47 51 89 47 89
E-mail address: tonje.holm@asplanviak.no