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Revealing the Fuzzy Geography of an Urban Locality
- 1. Revealing the Fuzzy Geography of an Urban Locality Richard Flemmings Department of Geography, Environment and Development Studies Birkbeck College, University of London E: richflemmings@gmail.com GISRUK2010
Notes de l'éditeur
- Part Time PHD Technical Manager at Blom UK – Mapping and Acquisition Organisation based in Somerset.
- Urban localities are a hidden geography . They have no officially defined boundary . They are subjective due to different peoples perceptions of space and place – one persons perception of the limits qualities and characteristics of an urban locality will be different to others. This inherent fuzziness is unavoidable, but can be given definition . The Urban locality is an important concept for estate agents who require knowledge of the location of a property in order to apply a value . The perceived location of a property is an essential factor in its sale – an estate agent can manipulate a location in order to raise value . By defining a specific relevant Urban Locality the extent to which a property is or is not within an area can be ascertained. This has benefits for both estate agent and client who can establish perceived as well as actual locations.
- As opposed to the crisp results of Boolean representation of space (space is either 0 or 1) – Instead fuzzy sets are classes without sharp boundaries. They show a gradual transition between membership and non-membership. A fuzzy set is characterised by the degree of membership – usually from 0 meaning no membership to 1 meaning full membership. The fact that a geographical entity can partially belong to a class is an essential improvement in representing geographical information. Fuzzy sets bridge the gap between the gradual variability of the real world and the lack of flexibility of well defined GIS data models. From this view point, fuzzy sets are suitable for representing urban geographies where perceptions and interpretations of phenomena can be vague.
- Vernacular geography, and specifically defining vernacular place names has been investigated in several other settings recently. The SPIRIT project attempted to create a method for defining vague place names. The SPIRIT project (Spatially Aware Information Retrieval on the Internet) was designed to create a geographical and location based search engine tool. Part of the project was to develop techniques to construct footprints for imprecise regions for which no exact boundary exists . The work of Twaroch et al (2009) has considered several methods of using a variety of internet sources to define vernacular places. For example, the online listing resource Gumtree was mined for location information in order to define the places where items were listed. Rattenbury and Naaman (2009) and Hollenstein and Purves (2009) have used tags from the photo sharing website Flickr to define locations. Holenstein and Purves state that “the specification of the location provided by users seems sufficiently accurate to assist in the investigation of smaller scale geographic places such as urban neighbourhoods” (pp.11).
- As part of the initial data collection for this study, 9 estate agents offices were visited, and employees were informally interviewed. The aim was to ascertain the factors that influence property valuation; specifically the location factors. Responses to questions indicated that several factors that are not specific to an individual property are used for valuation. (specific, intrinsic factors are also used, but are tied to an individual property and so not relevant here). The “name” of the area was predominantly mentioned in all interviews. The “name” of the area fits well with the purpose of the study and defining an urban locality. So this has led to the questions: If the “name” is a factor, how is the “name” defined by an estate agent? Can this “name” be verified?
- Clifton used as the example The area contains substantial period property and green space, and four of the Ward’s 7 super output areas are ranked in the top 20% in Bristol’s Index of Multiple Deprivation (Source: Bristol City Council Ward Profile). The area contains many prosperous young professionals living in flats (Source: http://www.upmystreet.com). These factors make Clifton a desirable place to live. A method was used to verify the “name”. This is detailed in subsequent slides.
- 4 steps were used to Geo-tag Internet Searches. 1. Trigger phrases are created by using words that place locations into a geographical context. They are a group of words together that in this case include a reference to the location of Clifton. This helps to create more geographically focused queries, rather than merely entering the word “Clifton”. The * Wildcard symbol was used in several trigger phrases – by combining this with a geographical trigger phrase, the aim is to give results that are in a geographical location. For example, the phrase “Clifton in *” is designed to search for all locations that contain Clifton. 2. The first 100 matched “snippets” were extracted from the trigger phrase Clifton in Bristol. Snippet text is the initial 2 lines of text that are displayed following a search within Google. – Snippet text was used rather than full text due to ease of retrieval and manageable handling.
- 3. Extracted Snippets were “annotated” using ANNIE. This is defined as A Nearly New Information Extraction System. Its part of the GATE software (General Architecture for Textual Engineering). ANNIE was used to match the Google search results with location names from the Ordnance Survey 1:50 000 scale gazetteer, as well as postcodes. The resulting Annotated text was exported from GATE software giving a list of Locations and Postcodes. Each Location and Postcode was then geo-tagged using the coordinate information from the Ordnance Survey 1:50 000 scale gazetteer and Code Point data. In other words, each incidence of a location in the top 100 search results was mapped to a point.
- ANNIE Annotations were geo-tagged. The results of Location annotations (using 1:50 000 Scale Gazetteer), show that the results were widely dispersed around the UK (left image). This dispersed result may be due to the “Definitive Name” field of the Gazetteer containing 21 different instances of “Clifton”. Of the 326 location annotations, 247 were for “Clifton”. It is unlikely that these were all in reference to Clifton, Bristol. In Contrast, 93% of Postcode Annotations were in the BS Postcode area which covers the region of Bristol. Postcodes are Less Ambiguous. Therefore, extracted postcode annotations were deemed more useful than locations for defining the Urban Locality.
- In order to be able to use the Annotated Postcode points in comparison with other factors, the points have been “rasterised”. A simple Kernel Density Estimation has been used. KDE has the advantage of assigning a point density to any location inside the study region (Bristol Local Authority) – NOT just locations where there is an event. The Density is estimated by counting the number of events in a region (kernel) centred at the location where the estimate is to be made. In this study a 10 metre sq. pixel size is used to output the resulting raster. A search radius of 500 metres was used. This is an arbitrary figure arrived at through trial and error. This is manifestation of the Modifiable Areal Unit Problem.
- KDE Results The image shows the Annotated Postcodes from Clifton in Bristol with the Clifton Ward boundary overlaid. This used the same parameters as Annotated Postcodes – 10 metres sq. with a 500 metre kernel radius. “ The Name” as a factor for property valuation has also been defined using the Ordnance Survey MasterMap cartographic Layer. Name labels have been output to poly-lines – 52 labels featuring Clifton in the Local Authority of Bristol – each depicts where on the map a name label is placed. Again, KDE was used to convert these to raster. The results can be seen on the Right. This used the same parameters as Annotated Postcodes – 10 metres sq. with a 500 metre kernel radius.
- KDE layers have been standardised. Standardisation of different factors is necessary as all factors have different attribute metrics for which a simple addition of component surfaces would not be suitable. Each raster was re-classified on an equal interval basis to give each cell within a value from 0 to 10. Very simplistic method of aggregating data. Equal Interval has the disadvantage of potentially missing important variations within certain aggregations. KDE layers combined to produce a composite surface of Urban Locality. This is a Local Operation within Tomlins Map Algebra – each cell within the output raster is a sum of the corresponding cells within the input rasters.
- It can be seen that regions have been given a membership. It can be seen that the Urban Locality does not correspond to the political boundary. The expansion to the East of the region, follows transport links. For example, “Clifton Down” railway station. The Avon Gorge to the West forms a natural boundary which seems to have halted the Urban locality from expanding in that direction.
- Back to the questionnaire that we asked at the beginning. YES an estate agent can define an area. And in the case of Clifton the answer is NO , it does not conform to the Political boundary. As well as questions regarding property valuation, Estate Agents were asked to define their perception of the boundary of Clifton. They were given a 1:25 000 scale topographic map that does not contain Council Ward or administrative boundaries. The results show most uncertainty in the South and East. The Index of Urban Locality has therefore been useful for giving definition to Clifton, particularly in this region.
- Summary Is the result of the study due to deliberate gerry-mandering by estate agents? Or is it a genuine perception that this is the “Actual” region of Clifton? Is the vernacular region of Clifton similar to other “non estate agents”? Web resources such as www.yourplacenames.com could help to answer this (Twaroch et al 2010).