The Syntax of Movement: Weighted Axial Analysis and Simulation

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THE SYNTAX OF MOVEMENT: WEIGHTED AXIAL ANALYSIS AND SIMULATION PROJECT DESCRIPTION This project investigates the spatial network of Hackney Wick and Fish Island in London in response to the London Legacy Cooperation Plan to enhance connectivity and internal movement within the neighbourhoods. The aim is to create a weighted axial model of the built environment and use Space Syntax analysis to predict the impact of spatial configuration along with the following three parameters on movement :

Proximity to Landmarks and Local Amenities

Access to Open Space and Public realm

The Impact of Traffic Congestion

Green Space

+

+ Local Landmarks

Local Landmarks

Green Space

Traffic

Finally, Galapagos, an evolutionary computing solver, was used to simulate an optimized location for a new hub/ intervention which improves the overall integration of the tested model.

Traffic

IDEA BACKGROUND Myriad amount of research has been conducted using Space Syntax to study the impact of the morphological and spatial structure of urban areas on pedestrian movement (Teklenburg et al., 1993). Central to this study is the ‘integration value’ of axial grids, ‘a set of intersecting lines through all spaces’ (Hillier and Hanson, 1984: pp.17). The ‘integration’ reflects how close an origin node to all other nodes and has strong correlation with movement patterns within an urban setting (Teklenburg et al., 1993). Yet, the topological axial model does not take into consideration various attributes which might contribute to making a built environment more walkable (Pafka, 2017). The aim of this project is to try to overlay some of the parameters which might influence movement on an axial model for a more comprehensive study of the examined neighborhoods. Note: The plugin used to conduct the Integration analysis for both the weighted and non-weighted axial model is developed by Tasos Varoudis.

Adapted Image, Source: Google maps

REFERENCES: Ewing, R., Handy, S., Brownson, R.C., Clemente, O., & Winston, E. (2006). Identifying and measuring urban design qualities related to walkability. Journal of Physical Activity and Health, 3(Suppl 1), S223-S240. Hillier, B. & Hanson, J. (1984), The Social Logic of Space, Cambridge University Press: Cambridge. Pafka, E. (2017). Integration is not Walkability. 11th Space Syntax Symposium. Lisbon, pp.1- 11.

Axial Model

Teklenburg, J.A.F., Timmermans, H.J.P., Van Wagenberg, A.F., 1993. Space syntax: standardised integration measures and some simulations. Environment and Planning B: Planning and Design 20, 347–357. Transport, D. (2018). Traffic counts - Transport statistics - Department for Transport. [online] Dft.gov.uk. Available at: https://www.dft.gov.uk/trafficcounts/cp.php?la=Hackney [Accessed 31 Mar. 2018].

Spatial Dynamics and Computation

MSc Space Syntax Architecture and Cities (2017-2018) Bartlett School of Architecture

Project by: Mariam Amer


CASE STUDY: PROXIMITY TO AMENITIES AND PUBLIC TRANSPORTATION LOCAL LANDMARKS MAP:

AXIAL MODEL:

High

Low

INTEGRATION [HH] | Radius= 3 Un-Weighted Analysis

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Low

INTEGRATION [HH] | Radius= 3 Weighted Analysis

Low

High

INTEGRATION [HH] | Radius= 3 Difference

GRASSHOPPER DEFINITION:

In this analysis, the effect of public transportation and local amenities on attracting movement to a local street is reflected on an axial model. The grasshopper definition checks whether a streets lies within a selected radius (walkable distance) from a local landmark or public transportation. For each local landmark that lie within a close proximity to a street, a value of 1 is added to the axial line. The reciprocal of total values assigned to each line represent a weight, which is then used to calculate the integration value. The weights are numbers from 0 to 1. Ultimately, the less the weight assigned to the axial line , the more integrated and walkable the street is.

Reciprocal

Collision radius

Weight/ Penalty Collision with axial lines Addition of 1 to avoid the division by 0 in the reciprocal

Spatial Dynamics and Computation

MSc Space Syntax Architecture and Cities (2017-2018) Bartlett School of Architecture

Project by: Mariam Amer


CASE STUDY: PROXIMITY TO PUBLIC REALM/ GREEN SPACE GREEN SITES MAP:

AXIAL MODEL:

High

Low

INTEGRATION [HH] | Radius= 3 Un-Weighted Analysis

The presence of a pleasant landscape or a public realm GRASSHOPPER DEFINITION: along a street segment could attract movement along that path. Not only does trees and landscape serve as an attraction, but also as a shelter from extreme weather conditions. The regular axial analysis does not take into account the affect of public realm on attracting movement a long an urban path. Thus in this analysis a grasshopper definition was introduced to Offset of axial lines to represent side walks address the possible effect of open space on the walkability within an neighbourhood. In this case an offset of the axial lines representing side walks are created and in case they cross a polygon of green space, they are assigned a value equal to the areas of the public realm they pass through. The reciprocal of these areas are remapped between 0 and 1 and used as the weight, thus the larger the area of the open green spaces or public realm a long a segment, the less the penalty/ weight for that line and the higher its integration value.

High

Low

Low

High

INTEGRATION [HH] | Radius= 3 Weighted Analysis

INTEGRATION [HH] | Radius= 3 Difference

Total area of open space each offset line collide with

Weight/ Penalty

Check if the offset line collide with open space

Spatial Dynamics and Computation

MSc Space Syntax Architecture and Cities (2017-2018) Bartlett School of Architecture

Project by: Mariam Amer


CASE STDY: THE EFFECT OF TRAFFIC CONGESTION AVERAGE ANNUAL DAILY TRAFFIC FLOW MAP:

AXIAL MODEL:

High

Low

High

INTEGRATION [HH] | Radius= 3 Un-Weighted Analysis

Transport, D. (2018). Traffic counts - Transport statistics - Department for Transport. [online] Dft.gov.uk. Available at: https://www.dft.gov.uk/traffic-counts/cp.php?la=Hackney [Accessed 31 Mar. 2018].

Unlike proximity to amenities and public space, traffic congestion has an adverse effect on pedestrian movement. Streets with higher traffic count is less likely to encourage pedestrian moment due to safety issues and pollution. Streets with higher average daily vehicular flow are assigned higher penalty, i.e. weight, thus reducing the integration value of that street segment. To calculate the weight, a factor of one is added to the traffic count, the reciprocal of the added amount is subtracted from the value of 1 so that the more the traffic count is , the higher the penalty.

Low

INTEGRATION [HH] | Radius= 3 Weighted Analysis

High

Low

INTEGRATION [HH] | Radius= 3 Difference

GRASSHOPPER DEFINITION:

Addition of 1 to avoid the division by 0 in the reciprocal

Imported traffic count data

Weight/ Penalty

Limitations: Traffic count data provided in this case study is only for main roads. Spatial Dynamics and Computation

MSc Space Syntax Architecture and Cities (2017-2018) Bartlett School of Architecture

Project by: Mariam Amer


CASE STUDY: COMBINED MODEL AGGREGATED MODEL ANALYSIS:

AXIAL MODEL:

Local Landmarks

Green Space

Traffic Low

High

INTEGRATION [HH] | Radius= 3 Un-Weighted Analysis

Low

High

High

Low

INTEGRATION [HH] | Radius= 3 Difference

INTEGRATION [HH] | Radius= 3 Weighted Analysis

GRASSHOPPER DEFINITION:

The diagrams below represent a comparison between the weighted and un-weighted axial maps where all the three parameters discussed above are aggregated and represented on axial girds. Since all the weights are originally distributed between 0 and 1. Each Weight is multiplied by a factor depending on the impact of the parameter on the model. In this case study, it is assumed that the presence of a transportation hub and local amenities will have the largest impact on the movement pattern within the neighborhood thus the weight is multiplied by a factor of 0.2 followed by the effect of traffic with a factor 0.3 and finally a factor of 0.5 for the proximity to public realm. Even though the difference between the unweighted and weighted model is minute, the benefit of conducting such analysis is that it gives a rather comprehensive picture of the actual built environment.

Un-Weighted Analysis Difference in Integration Value

Factor

Weighted Analysis

Total Weight/ Penalty

Spatial Dynamics and Computation

MSc Space Syntax Architecture and Cities (2017-2018) Bartlett School of Architecture

Project by: Mariam Amer


RESULTS AND REFLECTIONS COMPARING DIFFERENT PARAMETERS

TOPOLOGICAL RADIUS COMPARISON

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Low

INTEGRATION [HH] | Radius= 3 Weighted Analysis WEIGHT: AGGREGATED MODEL

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Low

INTEGRATION [HH] | Radius= 3 Difference WEIGHT: AGGREGATED MODEL

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Low

INTEGRATION [HH] | Radius= 6 Weighted Analysis WEIGHT: AGGREGATED MODEL

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Low

INTEGRATION [HH] | Radius= 6 Difference WEIGHT: AGGREGATED MODEL

A Graph illustrating the difference in the integration values as a result of introducing different parameters to the axial model.

High

Low

High

Low

High

Low

INTEGRATION [HH] DIFFERENCE INTEGRATION [HH] DIFFERENCE INTEGRATION [HH] DIFFERENCE Radius= 3 Radius= 3 Radius= 3 WEIGHT: LOCAL LANDMARKS WEIGHT: PUBLIC SPACE WEIGHT: TRAFFIC

From the previous analysis, it can be concluded that in this case study proximity to public realm has the least impact on the integration value within the axial model especially for the selected neighbourhoods. This is due to the fact that the majority of open green spaces are located at the edge of neighbourhood. On contrary proximity to local amenities has the largest impact reducing the integration for the roads at the periphery. As for the Traffic effect it had an impact on both periphery and internal routes, accentuating the more integrated internal routes which can represent preferred routes away from traffic congestion.

Graphs Comparing Integration Values for Weighted Axial Models of different radius

The case study was originally conducted on different topological radii (R3 &R6). The smaller radius (R3) shows a greater impact on the integration value. This is due to the impact of the surrounding neighbourhood spatial morphology and the fact that the amenities tested affect is mostly concentrated with in the range of the smaller local radius. Both analyses highlight similar axial lines for which the integration value has decreased. Weighing the model can provide an insight on a possible location where a shop can be located to attract more visitors and where an intervention can be made to improve connectivity between the neighbourhoods

Spatial Dynamics and Computation

MSc Space Syntax Architecture and Cities (2017-2018) Bartlett School of Architecture

Project by: Mariam Amer


GENERATIVE DESIGN AND MACHINE INTUITION According to the London Legacy Cooperation, new LONDON LEGACY COOPERATION INTERVENTION SITE developments are to be established in the neighbourhoods of Hackney Wick and Fish Island to help re-vitalise and enhance connectivity in the area. In this project , an evolutionary algorithm was adapted to examine an optimized location for a new intervention based on the weighted axial analysis thus maximizing the integration of both neighbourhoods. A bounding box around the selected site was created and Galapagos solver, developed by David Rutton ,was used to control a set of sliders which test different iterations until an optimized location for the new intervention is reached so that a maximum cumulative Integration value for the weighted axial model can be achieved. The optimised site lies just across the canal from the Legacy development site which suggest that extending the development on both sides of the canal can help in connecting and revitalising both neighbourhoods.

OPTIMISED SITE FOR AN INTERVENTION

LLCD Site

Proposed Site

Source: London Legacy Cooperation Area Development Plan (2014)

Proposed Location according to generative algorithms optimization conducted on a weighted axial model

MACHINE INTUITION AND OPTIMISATION

The benefit of using simulation tools as such is to inform the design process at an early stage and engage ‘in a design practice based on feedback loops’ (Caldas & Norford, 2012). REFERENCES: Caldas, L.G. & Norford, L.K. 2002, "Automation in Construction, 2002, Vol.11(2), pp. 173- 184; A design optimization tool based on a genetic algorithm", Automation in Construction, vol. 11, no. 2, pp. 173-184.

Diagrams showing the different iterations to reach an optimized solution

GRASSHOPPER DEFINITION:

Galapagos Generative Algorithm Plugin Weighted Analysis

Local Landmarks Open Space Traffic

Site Boundary

New Intervention

Intervention Location Axial Lines

Addition of Weights Total Integration [HH]

Weight for the New Intervention

Remapping the Weights between 0 and 1 (1= max Penalty or Less Integration)

Spatial Dynamics and Computation

MSc Space Syntax Architecture and Cities (2017-2018) Bartlett School of Architecture

Project by: Mariam Amer


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