193,737 research outputs found
Invisible City. A Multi-Sensory Approach to the Analysis of Urban Space
This thesis explores the relationship between sensory stimuli and human behaviour in urban space. It seeks to understand how spatial conditions, mediated, and supported by sensory experiences, impact individual and social activities and how this learning might be applied to other cities.
This research aims to challenge the âvisualismâ of planning and urban design approaches and to examine the urban environment through a multi-sensory analysis, focusing on the non-visual senses, such as hearing, smell and touch. It is based on a qualitative case study approach focused on Bishopsgate, in the City of London, an area with a unique variety of urban spaces, compact morphology and land use.
This thesis contributes to knowledge in three principal ways: First, the use of âsensewalksâ and âsensetalksâ as innovative user-centred methods of data collection, enabling in-situ semi-structured interviews with the presence of the researcher. Second, the use of thematic analysis of verbal and semantic descriptions received from participants, establishes a baseline for the exploration. Finally, the creation of a framework of analysis based on the concept of âsensescapesâ will facilitate the future exploration of the urban setting through its different dimensions. This framework not only creates a baseline for discussion but also establishes a tool for use in future urban development within the fields of environmental psychology, sensory analysis, urban design and spatial planning.
These contributions add to the academic literature and offer methods and techniques of analysis that may support future academic research, practice and policy. As planners and urban designers try to create better and healthier spaces, the analysis and production of urban âsensescapesâ can be used as a tool in (re)designing the city in new ways that stimulate the senses â ultimately making the role of the non-visual senses more âvisibleâ in the urban setting
Recommended from our members
Geovisualization of dynamics, movement and change: key issues and developing approaches in visualization research
Using Wii technology to explore real spaces via virtual environments for people who are blind
Purpose - Virtual environments (VEs) that represent real spaces (RSs) give people who are blind the opportunity to build a cognitive map in advance that they will be able to use when arriving at the RS. Design - In this research study Nintendo Wii based technology was used for exploring VEs via the Wiici application. The Wiimote allows the user to interact with VEs by simulating walking and scanning the space. Finding - By getting haptic and auditory feedback the user learned to explore new spaces. We examined the participants' abilities to explore new simple and complex places, construct a cognitive map, and perform orientation tasks in the RS. Originality â To our knowledge, this finding presents the first virtual environment for people who are blind that allow the participants to scan the environment and by this to construct map model spatial representations
Usability testing for improving interactive geovisualization techniques
Usability describes a productâs fitness for use according to a set of predefined criteria.
Whatever the aim of the product, it should facilitate usersâ tasks or enhance their performance
by providing appropriate analysis tools. In both cases, the main interest is to satisfy users in
terms of providing relevant functionality which they find fit for purpose. âTesting usability
means making sure that people can find and work with [a productâs] functions to meet their
needsâ (Dumas and Redish, 1999: 4). It is therefore concerned with establishing whether
people can use a product to complete their tasks with ease and at the same time help them
complete their jobs more effectively.
This document describes the findings of a usability study carried out on DecisionSite Map
Interaction Services (Map IS). DecisionSite, a product of Spotfire, Inc.,1 is an interactive
system for the visual and dynamic exploration of data designed for supporting decisionmaking.
The system was coupled to ArcExplorer (forming DecisionSite Map IS) to provide
limited GIS functionality (simple user interface, basic tools, and data management) and
support users of spatial data. Hence, this study set out to test the suitability of the coupling
between the two software components (DecisionSite and ArcExplorer) for the purpose of
exploring spatial data. The first section briefly discusses DecisionSiteâs visualization
functionality. The second section describes the test goals, its design, the participants and data
used. The following section concentrates on the analysis of results, while the final section
discusses future areas of research and possible development
Interactive visual exploration of a large spatio-temporal dataset: Reflections on a geovisualization mashup
Exploratory visual analysis is useful for the preliminary investigation of large structured, multifaceted spatio-temporal datasets. This process requires the selection and aggregation of records by time, space and attribute, the ability to transform data and the flexibility to apply appropriate visual encodings and interactions. We propose an approach inspired by geographical 'mashups' in which freely-available functionality and data are loosely but flexibly combined using de facto exchange standards. Our case study combines MySQL, PHP and the LandSerf GIS to allow Google Earth to be used for visual synthesis and interaction with encodings described in KML. This approach is applied to the exploration of a log of 1.42 million requests made of a mobile directory service. Novel combinations of interaction and visual encoding are developed including spatial 'tag clouds', 'tag maps', 'data dials' and multi-scale density surfaces. Four aspects of the approach are informally evaluated: the visual encodings employed, their success in the visual exploration of the clataset, the specific tools used and the 'rnashup' approach. Preliminary findings will be beneficial to others considering using mashups for visualization. The specific techniques developed may be more widely applied to offer insights into the structure of multifarious spatio-temporal data of the type explored here
Visual and interactive exploration of point data
Point data, such as Unit Postcodes (UPC), can provide very detailed information at fine
scales of resolution. For instance, socio-economic attributes are commonly assigned to
UPC. Hence, they can be represented as points and observable at the postcode level.
Using UPC as a common field allows the concatenation of variables from disparate data
sources that can potentially support sophisticated spatial analysis. However, visualising
UPC in urban areas has at least three limitations. First, at small scales UPC occurrences
can be very dense making their visualisation as points difficult. On the other hand,
patterns in the associated attribute values are often hardly recognisable at large scales.
Secondly, UPC can be used as a common field to allow the concatenation of highly
multivariate data sets with an associated postcode. Finally, socio-economic variables
assigned to UPC (such as the ones used here) can be non-Normal in their distributions
as a result of a large presence of zero values and high variances which constrain their
analysis using traditional statistics.
This paper discusses a Point Visualisation Tool (PVT), a proof-of-concept system
developed to visually explore point data. Various well-known visualisation techniques
were implemented to enable their interactive and dynamic interrogation. PVT provides
multiple representations of point data to facilitate the understanding of the relations
between attributes or variables as well as their spatial characteristics. Brushing between
alternative views is used to link several representations of a single attribute, as well as
to simultaneously explore more than one variable. PVTâs functionality shows how the
use of visual techniques embedded in an interactive environment enable the exploration
of large amounts of multivariate point data
- âŠ