Post on 14-Jun-2015
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Morphological and Functional
Attributes of the Urban Environment
and Pedestrian MovementPresented by: Yoav Lerman
Tel-Aviv University
The joy of being a pedestrian
The sorrow of being a pedestrian
Tel-Aviv Basics
Founded: 1909
Population: 400,000
Land size: 52 sq. km
Metro Population: 3 million
Agenda
Research question
Research area location
Methodology
Spatial-physical dimension
Functional dimension
Findings
Research Question
Which attributes of the built environment correlate with the volume of pedestrian movement in two adjacent areas in the center of Tel-Aviv?
Research Area
Research Area
East of Ibn-Gvirol street vs. west of Ibn-Gvirol street
Research area boundary
Sub areas boundary
Methodology
Dependent variable: pedestrian counts
Independent variables: built environment attributes
Positivist methodology based on non-intrusive observations
Looking for statistical correlations between the independent variables and the dependent variable
Each square – 500m X 500m
Two dimensions of the built environment
Spatial-physical dimension The basis of the urban form Extremely durable and rarely modified
Functional dimension The content that fills the form Relatively fast changes
Spatial-Physical Variables
Space syntax measures Connectivity by street name Pavement width Road crossing difficulty Intersection density
Functional Variables
Commercial fronts Residential density Proximity to bus stations
Measures Space Syntax
Use of DepthMap software based upon axial lines analysis:
Connectivity
Control
Integration
- Global Integration – Mean distance from the entire street network
- Local Integration – Mean distance from nearby streets
A Comment about Mapping
Fixed the street network according to pedestrian routes Boulevards Squares
Street Scheme
Axial Lines
Connectivity
Connectivity
Global Int.
Global Int .
Connectivity by Street Name
Pavement Width
Commercial Fronts
Pedestrian Count Points
95 count points 51 street segments
24 western segments 24 eastern segments 3 border segments
Count method: 5 minutes at each point 5 counts at each point
(once per hour for 5 hours)
Pedestrian Count Points Location
Avg. Pedestrian Volume in each segment (per hour)
Findings
Four correlated variables in descending order: R squared 0.83
1. Connectivity by street name
2. Total commercial front
3. Residential density in subzone
4. Proximity to bus stations
Findings – Western Area
One correlated variable Connectivity by street name
R squared 0.82 R squared 0.88 without boulevards and squares
Findings – Eastern Area
Three correlated variables: R squared 0.86
1. Total commercial front
2. Space syntax connectivity
3. Space syntax control
Findings – Eastern Area (Cont’)
Without the squares (Kikar Hamdina) Three correlated variables:
R squared 0.9
1. Connectivity by street name
2. Space syntax global int.
3. Total commercial front
Summary
In most cases the spatial-physical structure has greater correlation than the functional structure with pedestrian movement
There are major differences between the western and eastern areas correlations
Connectivity by street name correlated better than space syntax variables
The large square in the eastern side changes the correlation model significantly