MAPPING CRIME
MAPPING CRIME
CONTENTS
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2 BRIEF 3 TESTING > HULME 8 RECORD > STOKE-ON-TRENT 9 CONTEXT > TUNSTALL 11 TUNSTALL > DATA RESEARCH STRATEGY 12 > POLICE INTERVIEW 14 > POLICE DATA 17 > MYTUNSTALL 19 CRIME PREVENTION > CONTEXT 20 > TOWN CENTRE 22 > D3 24 > E5 26 > F4 28 ELEVATION ANALYSIS > TOWN CENTRE 34 > GRID SQUARES 38 > COMPARISON 40 DATA VISUALISATION 45 DATA INTEGRATION > STRATEGY 46 DATA MANIFESTATION > QR 48 > IMPLEMENTING 50 DATA INTEGRATION > APP 52 INSTALLATION > QR
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DIGITAL
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> [RE_MAP] FILM
SAMUEL HIGGINS [ R E _ M A P ] 2012
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Brief PART (): DATA DEFINITION WITHIN THE DERIVE:
METHOD. PRACTICE. RECORD. TRANSLATE. CONFIGURE.
Investigate the archectural ramifications of “wandering” in the city and landscape. Record and translate experiments into form with a geo-spacial context. MAP / RECORD / DOCUMENT Develop taxonomies of research to subvert, question, utilise and expose gaps in the data obtained - to allow the uncovering of latent opportunities to be exploited. Reading & Precedents
Situationists; Art, Politics, Urbanism
Game of Life
Fear & Space
Situationist theories influence the ideology of free movement through space with the object of collecting latent data.
As a grid based, autonomous principle, Conway’s Game of Life is taken as a precedent for organising and understanding the area of investigation as a gridded system.
Barber’s section of the book is taken as the main prededent of how to map and represent latent crime data.
John Conway. 1970
Xavier Costa, Libero Ardreotti, M Bandini, T. Levin, T. McDonough, G. Agamben. 1997
Benjamin Barber, Moritz Kung, Jacob Voorthuis, Mark Pimlott. 2005
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TESTING METHODOLOGIES
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Hulme
Site
CRIME The investigation focuses on the latent nature of crime and its relationship with the urban environment. The project aims to understand: _How undetermined derives are represented with GPS and mobile technologies. _How anti-crime manifestations, and their position / presence in space can be appropriately mapped. _Where recorded desktop crime data correlates to real world space and features. _The relationship between spacial information and recorded electronic data relating to crime. _How information and mapping can be used to influence routes and behaviours with the activation of latent data. Hulme, Manchester was chosen as a site to test methodologies for mapping the latent data and spacial implications associated with crime. The methodologies were adjusted and developed before they were employed on the main project site.
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HULME > TESTING METHODOLOGIES Derive / Recording A grid was established across the study area of Hulme based on OS grid increments. A group derive was undertaken to explore the extents of the area, covering all accessible routes.
Derive Route > Hand recorded map translation. Whilst walking, the journey details were recorded and translated to the OS grid map upon return.
Derive Route > GPS translation. Whilst walking, a smart phone with GPS software was used to record the journey details. The accuracy of this technology is limited as this representation of the route is a long way from the actual journey.
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Anti-crime Surveillance cameras and the frequency of recorded police crime data were compared as an initial method for understanding any relationship between anti-crime and recorded crime.
Recorded Crime > data.police.co.uk The data for a 3 month period in Hulme was overlaid onto the grid map. The data is generalised by street, so the accuracy is relatively poor.
Surveillance > Position and Splays. The GPS position and camera type were photographically recorded.The grid square frequency was assesed to give an indication of highly surveilled zones. The splays of the cameras were crudely assumed based on the camera model.
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HULME > TESTING METHODOLOGIES Representation Collected data from the police website was taken as a test set for representation. Different methods of information display were trialled.
Crime Distribution > Relative frequency. The data was displayed as concentric rings of frequency, then assigned to each grid square. The QR barcode was brought in at this representational stage as a means of conveying and making live the sources of our data sets.
Crime Distribution > Relative frequency. The same data is represented as a percentage of the whole grid square to highlight the most prominent crime types. The QR code had a representational colour scheme overlayed to graphically and digitally display the latent grid information simultaneously
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Ancillary Data Collection Other general data sets were collected relating to the area to give a view of some of the architectural actors which affected the urban domain. Due to their very indirect relationship with crime / anti-crime, these were not taken further than the initial methodological testing.
Recorded Crime > data.police.co.uk The data for a 3 month period in Hulme was overlaid onto the grid map. The data is generalised by street, so the accuracy is relatively poor.
House Prices > Location and Amount. Data from zoopla.com was assessed to indicate the areas where houses were selling in the 3 months around the investigation (red dots). The average sale price per grid is shown (left).
Planning Applications > Location and Frequency. Data from the Planning Portal was analysed to show areas where new build planning applications in the previous 3 years had been permitted (right). This highlighted areas of (re)development activity (letf).
Green Space > Total area per grid square. The green circles represent the relative proporation of the grid square which constitutes green space.
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RECORD > STOKE - ON - TRENT Context
Practice Analysis The data collected in Hulme was integral to developing the way the Stoke site was assessed. The derive in Hulme had an element of preconception because some of the group knew the area; it was chosen because of assumptions made about its percieved historical association with crime. In Stoke, the site had to be initially seen in situationist style to get a true sense of the space as a newcomer, unfamiliar with the area, and importantly to see how crime was percieved from this view point. The collection of data in Hulme was thorough, yet did not comprise a unified study which could be holistically analysed to review the impact of percieved crime / anti-crime / real crime in the area. A better system for the taxonomy of these spacial / mental conditions was required for the Stoke site to be analysed successfully. Percieved, reported and physical manifestations of crime / anti-crime had to be cross-compared to give a view of the extent of crime in the area. Stoke The six constituent regions of Stoke-on-Trent were divided amongst groups in the unit. This project deals with Tunstall, the northern-most area in Stoke.
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CONTEXT
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Tunstall
Grid
The transecting OS grid maps of Tunstall were divided into 250m increments to give a suitable scaled breakdown of the site for analysis.
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TUNSTALL > DATA RESEARCH STRATEGY Total Crime In order to represent the latent crime data in Tunstall, a strategy had to be developed which incorporated all facets and instances of crime / anti-crime and its associated perception / manifestation. If any one data set was seen as authoritative, this would skew the project’s findings. Each of the assessed data sets which contributed to the project had to be seen in context, with biases exposed and skews analysed, for the project to constitute a thorough assessment of the latent crime / anti-crime in the area.
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TUNSTALL > POLICE INTERVIEW 111014 Interview PC Clark Tunstall Police Station Present: Paul Westwell, Simon Bellamy, PC Paul Clarke. Name: Rank: Area: Time working SoT North: Background:
Paul Clarke Sergeant on the Neighbourhood Policing Team Stoke-on-Trent North 6 Months Police officer for 27 years, Tunstall first stationing, moved around Stoke-on-Trent. 6 Months CID in Leek. Moorlands, Hanley, Burslem and Tunstall the rest of the time.
“Police numbers decrease, crime falls.”
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“20 years ago, there would be about 6 - 7 burglaries a day in Tunstall... Whereas now we probably get 1 burglary every 2 to 3 days in the whole of Stoke.” “It’s probably about half a dozen individuals at any one time who are committing 80-90% of all the crime.”
“No particular online links apart from the (police) website, we’re not that technically advanced really.” “It is a bit harder to get a more personal level”
Overview The interview gave an insightful, if heavily biased view of the structure of crime and anti-crime in Tunstall. Although the data obtained was purely qualitative, it enabled the study to focus on areas of high and low percieved / recorded crime from the point of view of the authorities. It highlighted the issue of community feedback with the latent police crime data - a key driver in the final installation concept and realisation. The interview could have been more influencial to the project if it the content had been structured to provide qualitative, opinionated feedback relative to other sets of quantitative data. It could have been used to relate recorded crime figures, community crime identification, and physical anti-crime measures together from a police standpoint.
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TUNSTALL > POLICE DATA police.uk/data The recorded crime in Tunstall was assessed from the available police data over a 12 month period. This was set up as a live RSS feed into the data set such that future collation was an ongoing, automated process. The project broke the instances of crime down by street and by grid square, so that large (grid scale) analysis could be done and, importantly, justified by the micro-scale instances of crime at street level. When combined with the police interview, this analysis helped identify areas for detailed investigation. The data is recorded by street, therefore an incident can only be assigned to a nominal point on that street. This data operates at a more generalised scale than the rest of the project.
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Tunstall in Context From analysing the local (inter-Stoke) context of crime occurences, it is evident that crime is not atypically high in Tunstall. This data conflicts with some of the police interview and is at odds with the amount of information posted on a Tunstall based community website, MyTunstall. This stage of the anaysis did not take into consideration the per capita statistics for crime.
Types of crime - Tunstall
Types of crime - Stoke regions
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Further police crime data anaysis The crime data was extended to compare population and recorded crime figures in the local (inter-Stoke) and wider (UK) scale contexts. This enabled the Tunstall data set to viewed as a crime indicator by relative frequency. Despite the accuracy and recording problems associated with the data, the investigation proved extremely useful both to understand Tunstall in its relative contexts and to compare other data sets against for a holistic view of (recorded / percieved / manifested) crime / anti-crime. Crime rate and population - Stoke regions
Crime rate per person - Stoke regions
Types of crime in UK context
Crime rate and population - UK context
Crime rate per person - UK context
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TUNSTALL > MYTUNSTALL Community feedback The forum, MyTunstall, is integral to the community perception of crime in Tunstall and surrounding areas. This was fed into the project to analyse and interpret against the police data (qualitative and quantitative) and physical space manifestations of anti-crime to give a view of the perception of crime / anti-crime in the area.
The vast majority of information on the website relates to crime, most of that being minor anti-social behaviour and misdemeanor incidents. The police and community post their views on the site so that community awareness of crime is promoted as a key issue in the area. A data mine was created to constantly gather post information from the community forums. The RSS feed was directed into a live data set spreadsheet, which was grouped and sorted. Further input was required to create a taxonomy system so that the data could be filtered into useful categories. The vast amount of data initially seemed to be the definitive resource for community crime perception in the area. Data was collected from 80 pages of posts, with an average of 20-25 posts per page, covering appproximately 2 1/2 years of the site’s history.
Limitations From the data, it was clear that the majority of posts were submitted by a handful of users, and most of these related to the residents of a relatively affluent estate with a boundary park site between a council estate. This created a large skew of the data - towards that of Bankeyfields Estate - however the detailed data set represents a useful means of triangulating and rationalising other sets of crime information.
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TUNSTALL > CRIME PREVENTION Manifest crime / anti-crime Derives and data collection were carried out in a series of locations around Tunstall. These were selected by analysing data from the police and community resources - representing a large spread of percieved and actual areas of high and low crime. The studies aimed to document (within a rigid taxonomy) the manifestations of crime / anti-crime in physical space - which is key driver in the project.
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TUNSTALL > CRIME PREVENTION Tunstall town centre The initial study area was the town centre. Highlighted by the police data and interview as a varied zone, it was taken a test zone of typical crime instance to compare and contrast with other zones in the area. The large amount of retail / private business ownership in the area was assumed to contribute to the fact that there were large amounts of surveillance, private and regulated boundaries and lighting.
Street lighting zones
Surveilled zones
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Residual zones around lighting and surveillance
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All recorded data - town centre
Analysis This study showed that the town centre was the most densely populated area of Tunstall in terms of anti-crime manifestations. This is in direct contrast to the amount of recorded crime and community perception of crime in this area. It could be assumed that surveillance and anti-crime were more a means of deterrant - to safe guard private interest - rather than a reactor to the levels of crime that were present in reality.
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TUNSTALL > CRIME PREVENTION Grid Square D3 This area was analysed in the police interview and through recorded crime data as a HIGH CRIME zone. A derive around the area was used to document and analyse the crime / anti-crime manifestations and implications.
Street lighting zones
Surveilled zones
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Analysis The denser areas of anti-crime - surveillance in particular - were found near zones of private ownership. A school and shop had their own systems of surveillance. A few non-descript houses had miniature surveillance cameras mounted in windows - perhaps a reaction to the percieved and actual crime in the area, or an ancillary protection for the actors of crime themselves (eg. cannabis plantation security, etc?). The derive was underwritten by preconceptions of the area as a high crime, dysfunctional neighbourhood. This reflected the police and community perception studies and the police crime data.
Residual zones around lighting and surveillance
All recorded data - D3
Dereliction and decay were very prominent in the surveyed zone. This directly links with the amount of recorded and percieved crime analysed from all sources, however the resultant anti-crime manifestations were not as abundant as expected. With very little high-value private ownership / interest in the area the level of technologically enabled security systems was low.
There was a direct relationship between lighting and vandalism in the area. The zones which had the least lighting corresponded to those that had the most vandalism. The spacial qualities (materiality and size) of most back alleys in the grid square were very similar, however those which employed uniform, high level lighting tended to be those which were not as prone to litter agglomeration and vandalism.
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TUNSTALL > CRIME PREVENTION Grid Square E5 This area was analysed in the police interview as a HIGH ANTI-SOCIAL BEHAVIOUR zone. A derive around the area was used to document and analyse the drime / anti-crime manifestations and implications.
Street lighting zones
Surveilled zones
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Analysis This grid square represented the threshold of a relatively low quality housing development meeting the northern boundary of the town centre. There is a tangible shift in amounts of lighting and surveillance from the high frequency town centre to the low frequency housing estate. There is an axial divide separating the two conditions which contains private businesses, high levels of lighting and surveillance. The levels of crime by street were inversely proportional to the amount of anti-crime manifestation. High crime corresponded to low anti-crime.
Residual zones around lighting and surveillance
All recorded data - E5
Dereliction was evident in the area, but primarily limited to ex-industrial (factory) building types. The presence of shuttering on the road-fronting streets corresponded to minimal levels of vandalism and litter. The back streets associated with these buildings however were zones of high vandalism, fly tipping, etc. and low amounts of anti-crime measures. The police data for the ex-industrial streets suggested that there were relatively high levels of crime present. This may be interpreted as the innaccuracies in the police data, where a crime may have occurred on an unnamed back street, yet been statistically attributed to the nearest main street.
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TUNSTALL > CRIME PREVENTION Grid Square F4 This area was analysed in the police interview and collated police data as a LOW CRIME zone. A derive around the area was used to document and analyse the drime / anti-crime manifestations and implications.
Street lighting zones
Surveilled zones
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Analysis The grid square is a relatively affluent area of the town. Although the building stock is similar in age and design as the high crime zone, the amounts of crime - both recorded and percieved - are extremely low. There is one instance of surveillance in the entire area, and a uniformly distributed lighting scheme.
Residual zones around lighting and surveillance
All recorded data - F4
Community is key to this area. This is principally a residential area, with one point of private commercial interest - a convenience corner shop (which incidentally is the one point of camera surveillance). Analysed in the police interview as an almost exclusively Asian neighbourhood, there is apparently a very strong sense of community cohesion - with neighbourhood watch having a strong signposted and stickered presence. This outlook is insular however, as neighbouring grid square streets have much higher levels of crime and anti-crime measures.
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TUNSTALL > ELEVATION ANALYSIS Investigation areas Within the derive / analysis grid squares a series of streets were chosen for detailed two-dimensional analysis.
Process The aim of this section is to visually document the crime and anti-crime physical manifestations of real world space. An objective, linear photographic study of each street was done so that a taxonomy of spacial interventions could be documented and visually analysed in a unified, barcoded system. The study highlighted the presence of surveillance, anti-crime and lighting.
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Town centre street analysis
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TUNSTALL > ELEVATION ANALYSIS When analysing the town centre, two key arterial sections were taken. Dissecting the previous study zone, they deal with major threshold conditions of ownership, occupancy, demography and use.
A_A High Street
B_B Town Centre - Horizontal Transect North
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TUNSTALL > ELEVATION ANALYSIS
C_C Town Centre - Horizontal Transect South
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TUNSTALL > ELEVATION ANALYSIS Grid square street analysis
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E_E Grid Square F4 - Kenworthy Street North East Elevation
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TUNSTALL > ELEVATION ANALYSIS Grid square street analysis
F_F Grid Square F7 - Williamson Street Elevation
D_D Grid Square D3 - Bond Street North West Elevation
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TUNSTALL > ELEVATION OVERALL COMPARISON Taxomony contrast and comparison Each of the elevations were laid out at the same relative bar scale where street length was rationalised for straightforward comparison. Visually, the barcodes show the frequency of surveillance, anti-crime and lighting, giving an abstract representation of street elevations, punctuated not by built form but instead by ancilliary devices of percieved control, security and safety.
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They highlight the correlation between the town centre (private business ownership) and the residential periphery (personal ownership). Where there is a vested interest in monetary transactions (retail and commerce) there is major investment in anti-crime measures, regardless of the fact that recorded crime is not particularly prevalent in these areas. It might be assumed that the town centre as a public domain is governed and controlled by surveillance and anti-crime to protect the interests of private businesses rather than those of the public
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TUNSTALL > DATA VISUALISATION Town centre recorded crime data The data from the police website from a 12 month period was translated into a 3D stacked bargraph. Shown in context, the relative heights create a latent crime map for each street in the town centre.
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Town centre recorded crime prevention The data collected in the town centre in the derive is displayed as a 3D stacked bargraph. Again, this shows relative density and frequency of crime prevention classes in the centre. The two representations of reported crime and the spacial manifestations of crime / anti-crime can be easily compared and contrasted.
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TUNSTALL > DATA VISUALISATION Data combination To combine all of the data sets previously analysed, the grid system was utilsed. The data set is distributed over the grid squares with the relative heights of the grid centre points showing the frequency of any given category. These analyses are grouped and merged to create a combined data set and representation for each given grid square. An alternate crimescape is created, where topography is defined in each grid area by the recorded crime or perception of crime.
Police crime data
Police interview data
MyTunstall data
Combined data sets
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Sectional analysis Two transecting sections were taken through the whole study site. The crimescape representations below show each of the data sets and their associated geography at the cut throughs.
A_A Grid row 3 section Police crime data
B_B Grid row 3 section Police crime data
A_A Grid row 3 section Police interview data
B_B Grid row 3 section Police interview data
A_A Grid row 3 section MyTunstall data
B_B Grid row 3 section MyTunstall data
A_A Grid row 3 section Combined data sets
B_B Grid row 3 section Combined data sets
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TUNSTALL > DATA INTEGRATION Implementation After the analysis and combination of data sets the latent data needed to be activated in its physical context, so that as a spacial intervention the data could begin to alter the way in which users derived, navigated and utilised their urban environment. A digital interface - smart phone enable app - was chosen as the conduit for the data to be stored and as the accessible platform with which it would touch down in user space. In physical space on the streets of Tunstall, coded, wall mounted symbols were chosen as the object based manifestation of the latent data. These symbols would be read by a smart phone to allow access to the digitally based crime data of the area in which they were positioned. The system intends to allow interaction with the latent data, both passively and actively, with users adding and adapting the data in real time. This generates a feedback loop where the data sets of crime perception, recorded crime, and anti-crime manifestations are constantly in flux, being generated and adapted by a feedback loop of user interaction.
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TUNSTALL > DATA MANIFESTATION Activating latent data The QR barcode was seen as the most viable option for encoding large amounts of data directly into the urban environment. The system used a link to a live web based app, which contained data and interactivity with the area in which the barcode was placed. This is accessed when the user has 3G or wifi enabled on their smartphone (or similar) device. Experimentation with the barcodes was done through legibility and materiality tests. Hand drawn barcodes were tested for their accuracy - a system which could see guerilla information thrown up onto walls. This testing was semi-successful, but was abandonned in favour of a more permanent version of the coding. Tiles were chosen because of their durability, ease of fixing, uniformity, abundance and relationship with Stoke’s past as a centre of pottery manufacture. Initially the tiles were etched with the barcodes. As objects they represented subtle, decorative interventions into space, however the contrast between background and symbol was not great enough, so their legibilty ruled out this type of data enabling. Glazed transfer printing was taken forward as the most suitable method of semi-permanently coding the urban environment with data at the manageable, human scale. The QR code is printed onto transfer paper, then overlaid onto a glazed tile. It is fired in a kiln at 800 degrees for several hours. The symbols are permanently fixed within the glaze of the tile. When affixed in context, they proved to be durable, colour-fast and neat finished objects.
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TUNSTALL > DATA MANIFESTATION Implementing the intervention Using tile adhesive, the QR barcodes were fixed onto the elevations / street furniture of the urban environment. A number of tiles were installed to allow the methodology to be demonstrated in context, and to give an indication of how the streets of Tunstall could be populated with this data if the infrastructure were fully installed.
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TUNSTALL > DATA MANIFESTATION Scale When enabled in context, the recorded and perceived crime / anti-crime data can be utlised in two different ways..
Variable route finder
High level options
This app mode allows the user to re-assess their (pre)conceptions with crime and the urban environment. As an extension to the concept of standard route finding technology, the app enables a destination to be entered. The app knows the current location and allows the user to adjust a series of crime-based variables to define their route from A-B.
Location Statistics - gives map view of QR and user location. Visualises data sets associated with site, to give an idea of the latent information relating to crime in the given. area
Each of the available data sets is activated and the user can choose a high or low value in any instance. Once the preferences are accepted the app calculates the nearest and most appropriate street to satisfy the parameters. At each barcode, the user is able to input their requirements or carry on with their chosen programme.
Report crime - directs the user to police details, contact information and direct services - 999, etc.
Post a comment - directs user to integrated MyTunstall post, titled and set up approriately.
A step-by-step, street-by-street navigation of routes through the urban environment is created; constantly adaptable and constantly influenced by latent crime data. The app could potenially be used as a method of safest travel home (avoiding areas of potential high crime risk), finding the best place to park overnight, changing perception of high crime areas, or even identifying the most appropriate place to commit a crime.
App use options When the app mode is selected the user can select from a series of preferences. High and low values of desirability can be chosen from any data set to identify the most suitable next move in the journey.
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Anti-derive game
Feedback loop
This app mode is a data driven exploratory tool for Tunstall.
With both instances of the app, user interaction is actively encouraged.
Users scan a QR barcode located in a grid square. Their location is identified on a gridded map on their screen. They select the anti-derive game and the data set options are enabled. They set their preferences, selecting high or low ratings for any combination of variables.
If a crime is witnessed, or committed to a person, the app will enable the user to contact the police in the most direct way. This will feed back into the app - as RSS enabled recorded police crime data which will change the statistical data and the resulting representation / perception of the area.
The app calculates the most appropriate neighbouring square for the user to enter. Initially only the map is displayed in an attempt to force the user to navigate from one square to the next, in a situationist manner, exploring the area as they progress to the next QR code. Their route will have been defined by the data variables, but they will be encouraged to challenge or change their perceptions of an area by comparing the physical environment to that of the latent crime data.
If small scale, community relevant issues are visible in the urban environment, the user can access the MyTunstall forum directly. There they will be able to categorise their post and interact with the forum live. The posts are structured so that the RSS feed picks up the comments and feeds them back into the app’s data stream, again, restructuring the representation / perception of crime.
They can then feedback their experiences and adjusted perceptions into the MyTunstall website, so that the feedback loop of community data input is enabled. If the user wishes they can alternately select “directions� from the menu, indicating a prescribed route to the next grid square, based on the variables of crime data which they selected.
Next stage calculator The map based representation of the grid squares highlights the next move in the antiderive game.
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TUNSTALL > INSTALLATION Video The derive, the implementation and the methodology are documented in a video. Section 1 shows the latent crime data app enabled as a variable route finder.
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Section 2 shows the latent crime data app enabled as the anti-derive game.
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