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What do the outputs of accessibility analysis show you?
To develop effective evidence you have to have a firm understanding of the data it's based upon and be able to interpret and present results appropriately. The key to meaningful analysis, therefore, lies in understanding the scope of the data you have available, what it describes and what it can be used to show. This may be visually represented as a table, a graph or a map, or be presented as conclusions in text form.
The results of accessibility analysis should provide an insight into the types of facilities people have difficulty accessing, the sub-groups of the populations that are affected and the reasons why they are not able to access services. These reasons may be directly related to the public transport system—that there isn’t a suitable bus service, for example - or may be down to reasons such as cost or personal security fears.
Remember: accessibility analysis on its own can't tell you anything about actual travel patterns or levels of demand for these particular locations or services; it's only concerned with the potential to access them.
The table below sets out some typical forms of accessibility analysis and offers an example of the kind of issue the results could help identify.
| What accessibility analysis can show | What this helps to identify |
| The number of people within a certain travel time of a location or facility | Areas and populations with poor accessibility to particular facilities |
| The views/perceptions of the population regarding which facilities or locations they find difficult to access | Population groups with poor access, the locations they find difficult to access, and why. This may be due to perceptions caused by short ‘travel horizons', lack of information, etc |
| The number and size of facilities that are reachable within a certain travel time from a location (usually from a residential area or new housing development) | Destinations and facilities that people in a particular location have difficulty reaching |
| Variations in crime levels across an area | Areas/population groups to target for further analysis, to see if fear of crime and personal safety are issues for them |
| How far different population groups are willing to travel to reach particular locations/types of facilities | Helps determine thresholds and how these vary by population group/time period/location |
| The characteristics of the population – e.g. how many people are long-term unemployed? | Areas with high numbers of people in ‘at-risk’ population groups (e.g. long-term unemployed) with poor accessibility to particular locations or facilities |
| The characteristics of locations or facilities – e.g. how many facilities are there, their size/capacity, the services they offer, etc | Areas with poor accessibility to certain types of facilities |
| How accessible one location is in comparison to another | Areas that are particularly inaccessible compared to the overall area or region |
| Public perception of crime and personal safety | Areas, population groups and/or time periods where accessibility is being affected by personal safety fears or fear of crime |
| The level of access that a particular sub-group of the population has, compared to the population as a whole | Sub-groups of the population that have worse accessibility than the population as a whole |
| How accessibility has changed over time | Whether accessibility has improved or worsened over time, and by how much |
| The overall accessibility of an area to a variety of different facilities | Areas with poor accessibility to a combination of facility types, e.g. areas which have poor access to health, education, employment and shops |
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