Resultados

The process of geotagging, a form of ‘georeferencing’, normally refers to the process of attaching geographic metadata to an object or item such as a

photograph or a video (Welsh et al, 2012). Like global position systems (GPSs), geotagging software captures the coordinates of an item by triangulating the coordinates data received from an array of GPS satellites (see Kaplan and Hegarty, 2005, pp. 2 – 5). GPS takes two forms:

• Precise Positioning Systems (PPS) for military use

• Standard Positioning Systems (SPS) for civilian use.

SPS is free of direct charges and were accurate within at least 13 metres of the horizontal plane and 22 metres of the vertical plane in 2005 (Kaplan and

Hegarty, 2005, p. 5). Civilian GPS today is notably used in movement tracking applications (Apps) developed on Android and Apple operating systems. For example, the Runtastic Running and Distance & Fitness Tracker phone apps exploit GPS data provided by Google commissioned satellites which enables app users to trace their journeys through an urban space. As of 2016, GPS data is accurate within 5 metres of a receiving device. Paths are traced based on the continuous updates provided by the satellite array every 100 milliseconds. Apps such as Runtastic are created in the freely available Android SDK (Software Development Kit) within which parameters, such as the size of the satellite array and frequency of returned coordinates, can be manually set. This flexibility was exploited in the development of a purpose-built App called ‘Parade™’, for the capturing of static pedestrian activities.

Parade™, which I, the researcher, developed with my brother, Roderick Timmerman, captures two surveys with regards to static pedestrian activities:

low-resolution and high-resolution surveys (see Timmerman and Timmerman, 2018).

160 5.2.1.1 Low-resolution pedestrian survey

The low-resolution survey monitors the occurrence of standing and sitting activities and whether they respectively engage or disengage with the urban fabric. The categories for the low-resolution survey are as follows:

• Standing Engaged

• Standing (Disengaged)

• Sitting Engaged

• Sitting (Disengaged)

Engaged activities broadly capture those that Gehl and Svarre (2013) refers to as being optional, but also indicative of street user assimilation or interaction with the environment. These include:

• Standing/Sitting to eat

• Standing/Sitting to enjoy life

• Standing to do something (i.e. feed pigeons or take pictures)

• Standing to trade

• Standing to look at something (window displays)

• Standing to look at an activity (i.e. watching a performance)

• Sitting to read

On the other hand, disengaged activities refer to those where the street user doesn’t appear to be interacting with their environment despite being stationary.

These activities were:

• Standing to quench thirst

• Standing to greet/talk

• Sitting to supervise (i.e. children at play)

The objective of the low-resolution survey is to test whether a correlation is present between static activities and the increased presence of customisation. It provides a basic indicator as to whether apparent trends can be justified by the overall engagement (attachment) or disengagement (detachment) with the urban realm.

5.2.1.2 High-resolution pedestrian survey

In the high-resolution survey observations are split directly into finer categories that describe a static pedestrian activity. This survey is more time consuming than its low-resolution counterpart and so is more likely to provide a distorted

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distribution if used as a standalone dataset. The principle purpose of this survey is to further analyse any apparent correlations from the low-resolution survey with more qualitative detail. The specific categories were based on Gehl and Svarre, and were as follows:

Standing Sitting

• Standing to enjoy life

• Standing to quench thirst

• Standing to eat

• Standing to do something (i.e.

feed pigeons or take pictures)

• Standing to trade (buy / sell)

Parade™ is programmed to act more like a geotagger than a geotracker,

however, it depends on the same continuous data used by trackers. Essentially the surveyor navigates through the pedestrianised portions of the case study and presses buttons that corresponded with an appropriate activity on the user interface to capture the current coordinate being received by Parade at that time, whilst standing next to the static activity. This process was repeated with other static pedestrian activities until the survey was completed. The

coordinates and metadata concerning the activity are captured and recorded into a database log which is extractable as a comma separate values file (CSV).

Because the app depends on GPS coordinates, the ‘x’ and ‘y’ coordinates are in the form of longitude and latitude. Once exported to an appropriate workspace, the data can be uploaded into R and plotted using ggplot2.

Because of the native latitude and longitude coordinates system favoured by Google, ESRI data imported into R, such as the heat mapping tiles, are

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subsequently converted from the British National Grid system (OSGB 1936) to Latitude and Longitude (WGS 84) for later correlations.

5.2.1.4 Further functionality within Parade™

In its present iteration, Parade™ is essentially a geo-tagging app. This enables it to additionally capture quantitative and qualitative counts of customisation specific to the 10-metre polygon mesh used in the heat mapping exercise (Section 5.1). The categories are found overleaf:

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Table 7. Quantitative counts for customisation

Aesthetic

Public Art / Mural Single Count (default value = 1) Physical

Wayfinding / Signage Single Count (default value = 1) Guerrilla Gardening

Sculptures / Structures Urban Knitting

Functional

Performances Single Count (default value = 1)

Sui Generis

Table 8. Qualitative counts for customisation

Aesthetic

Public Art / Mural (quality) User prompted to assign score between 1 & 5

Physical

Reconfiguration (quality) User prompted to assign score between 1 & 5

5.2.2 Correlating static pedestrian activities with customisation