A GIS-based Route Mapping Tool for Disabled Access in Urban ...

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164Urban barriersstepshigh kerbsdeep guttersgravel surfaceslack of dropped kerbsnarrow pavementssteep gradientsdifficult camberscobbled surfacescongested pavementsdropped kerbs not adjacentuneven paving slabsraised manhole coversstreet furniturehandrails not on ramps9181767573696665625656504743420 10 20 30 40 50 60 70 80 90% of respondents who found thebarriers either prohibitive or severeFigure 1 Percentage of questionnaire respondents regarding an urban feature to be asevere prohibitive barrier to movement, by type of wheelchairThe results of both the questionnaire and focus groups highlighted the importancenot only between urban features but also in diversity of experience and type ofwheelchair used. As would be expected, there was consensus that steps are a majorimpediment, denying access on most occasions. High kerbs, too, limited movementas do poor surface conditions of various kinds. Where there are no adjacent droppedkerbs then road crossing may be impossible and journeys are lengthened. Gradientsare a particular problem for most manual and assisted wheelchair users but were amuch lesser problem to users of powered wheelchairs. A number of other urban barrierswere identified as being prohibitive to access including narrow pavements, inconsiderateplacement of street furniture, gutters, and difficult cambers.3. Database developmentIn order to construct a database of the identified barriers to wheelchair access for usein the GIS model, it was necessary to devise a number of methods to accuratelyquantify urban features. A number of pavement surface types were identified and therolling resistance of each was calculated. Dragging a wheelchair and occupant overthe surface with a force gauge allowed the required effort to be quantified. Theweight of the occupant increased the required inertia, but rolling resistance was observedto level out and become relatively consistent at distances greater then 8m.Copyright © IGU/ISEP, Wien 2002. ISBN: 3-9500036-7-32504 EI P 906 I2 BealeL.doc 29.08.02
165The starting force was, as would be expected, always the highest recorded force forall surfaces. This measure is weight dependant. It was, however, found to be a veryimportant measure, with uneven surfaces causing the wheelchair to be slowed downand in some cases brought to a halt. The range of measured force was therefore acrucial measure, providing a good indicator for surface roughness. The results reflectedthe questionnaire and focus group responses.Dropped kerbs provide crossing points for wheelchairs across roads and consequentlyhad been identified as being extremely important to allowing movementaround an urban area. A total of nine factors were identified as being required to assessa drop kerb and included: height, surface, slope, camber, width, orientation,curvature, with bullnose and brickrunners. Collation of this information enabled acomprehensive and efficient method of ranking drop kerbs.The remaining urban features to be included in the digital database (e.g. the locationof steps, ramps and cambers) required only mapping by location, rather thanquantifying. Many of the urban features were gathered in the field, using a palmcomputer running ArcPad GIS. This provided an efficient method of mapping thedata and reduced the error that can often occur during data conversion.Initially, a network coverage representing pedestrian routes around the town centrewas derived using Ordnance Survey Land-Line data - an enhanced vector dataset, where features are represented as points and lines that are digitised and specificallycoded to show 37 layers. A number of issues arise when attempting to demarcatepavements as a range of different features defines pavement edges (e.g. buildingoutlines, walls, road edges). In order to provide consistency, pavement centrelineswere manually extracted using the Ordnance Survey Land-Line data as a backdrop.This removed the need to alter the original data whilst allowing the designer to uselocal knowledge to derive a network that best represented the general flow of pedestriansaround the town centre. Using the Dynamic Segmentation module inARC/INFO ® , linear measurements were used to define locations along linear features.All urban barriers were then associated with the correct measurement along theroute, defined as linear measures (e.g. pavement surface) or point events at measuredlocations (e.g. steps). The routes were assigned a direction along which the measurementsare made, thus, each route must be labelled twice since some of the barriersare direction dependent (e.g. slope). The drop kerbs were then stored as turntabledata, thereby allowing the direction of traverse to be significant. Storing the data usingdynamic segmentation means that the data is stored as a tabular database. Datacan be updated without altering the network topology.3. Model developmentMAGUS (Modelling Access with GIS in Urban Systems) is built entirely withinESRI ArcView ® GIS, using AVENUE programming language and Dialog De-Copyright © IGU/ISEP, Wien 2002. ISBN: 3-9500036-7-32504 EI P 906 I2 BealeL.doc 29.08.02
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Page 7: 1674. ConclusionsA number of volunt

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