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SP_3 Automatic identification of high streets and classification of urban land use in large scale topographic database
- 1. Automatic identification of High Streets and classification of Urban Land Use in Large Scale Topographic Database Omair Z Chaudhry (Manchester Metropolitan University) Médéric Gravelle , Nicolas Regnauld (Ordnance Survey) GISRUK London 15 th April 2010
- 2. Motivation: Vis. Of Urban Land Use at small scales
- 3. Urban Boundary Extraction Chaudhry and Mackaness 2008
- 4. Urban Block Land Use Classification ∑ Building Area t /Block Area i
- 5. Result of Urban block classification
- 6. Extracting Commercial Or High Streets
- 7. Extracting Commercial Or High Streets > 250m
Hinweis der Redaktion
- Reason for doing this research Large scale topographic database OS MasterMap Large number of features Classifies features into buildings, roads, streets, etc Doesn’t provide usage classification of buildings OS Address Layer 2 Provides usage information for building features Provides very detailed classification as OS Basefunction Bank or bar or primary school Also provide information of National Land use classification – more abstract – retail, utility, commercial This is quite useful for applications and visualisations that require large levels of detail but for visualisation at more abstract levels such detailed information needs to generalised Include examples of building classification at MM level and then at 1:50k scale where block are represented
- Extraction of Urban boundary Quick explanation of urban boundary (Chaudhry and Mackaness 2008) Include Southampton and Glasgow results Partition Urban boundary into street Blocks
- Classification using Address layer 2 information into residentail, commerical and industrial By Count Problem Using Area And above 5%
- Glasgow Or Southampton Problem of Missing high Streets Use actual example and illustration
- Selecting Commercial and Industrial Address points from AL2 Building a proximity Graph using Delaunay triangulation Extracting MST from the proximity Graph Segmentation to create Clusters Buffer and aggregate buffers to create a region Select road segments
- Combine road segements into continous long roads – based on the principal of good continuation (Strokes) Selection of long straight roads Results with previous land use classification – here we buffer the selected roads Good examples from Medric Report