Space syntax and spatial cognition: or why the axial line?

200

A sketch planning methodology for determining interventions for bicycle and pedestrian crashes: an ecological approach

Bicycle and pedestrian safety planning have recently been gaining increased attention. With this focus, however, comes increased responsibilities for planning agencies and organizations tasked with evaluating and selecting safety interventions, a potentially arduous task given limited staff and resources. This study presents a sketch planning framework based on ecological factors that attempts to provide an efficient and effective method of selecting appropriate intervention measures. A Chicago case study is used to demonstrate how such a method may be applied

SUSMETRO : Impact Assessment Tools for Food Planning in Metropolitan Regions : IA tools and serious gaming in support of sustainability targets for food planning, nature conservation and recreation

By offering a series of decision support tools for stakeholders of metropolitan regions, SUSMETRO facilitates and enables evidence-based decision making by means of ‘serious gaming’. Making use of the Phase 1 thematic maps such as on agricultural competitiveness, nature conservation and recreational values, stakeholders can compare impacts of traditional versus innovative forms of agricultural production. The SUSMETRO Impact Assessment tool provides information on the expected effects of spatial planning with regard to the self-supportive capacities of the region (ecological footprint) and the share of recreational and nature conservation facilities (land use functions), offering cost-benefit calculations regarding the expected economic revenues. The whole process is embedded in a Landscape Character Assessment process and guided by Knowledge Brokerage procedures to strengthen the science-policy interface. In sum, the SUSMETRO approach allows a wide range of stakeholders to co-develop images for sustainable Metropolitan Agriculture

Cognitive evaluation of computer-drawn sketches

CISRG discussion paper ; 1

Understanding Space: the nascent synthesis of cognition and the syntax of spatial morphologies

24-28 September, 200

The significance of distance constraints in peasant farming systems with special reference to sub-Saharan Africa

Analysis of agricultural development potential at village level tends to neglect the factor of relative location, compared with the attention paid to physical resources and economic factors. This paper argues that, in African peasant agriculture, distance takes on increasing significance when farming populations are resettled and agglomerated, there being little intensification in evidence. The impacts of agglomeration and excessive ‘journeys to work’ are identified as affecting the quantity and the quality of agricultural labour inputs, the collection of domestic necessities (especially fuelwood), livestock husbandry, and socio-cultural and welfare conditions.\ud \ud Some simple analyses of time-distance relations, such as the ‘effective working day’, are also described, and a model of peasant decision-making with respect to optimizing farm activity location is proposed as a descriptive-explanatory tool. Response to distance problems is considered as part of rural change; and the particular position of peasant women vis-à-vis distance and transport technology is stressed. Data collection methods and descriptive statements of the spatial relationships within a village, or an agro-ecological zone, are outlined within the framework of rapid rural appraisal. Finally, a number of potential solutions to the agro-economic distance problem are briefly discussed—either as changes in farming systems, or as redistributions of the working population. Changes with the greatest potential are intensification and satellite settlements, though both face difficulties in policy and in implementation

Sketch-based subspace clustering of hyperspectral images

Sparse subspace clustering (SSC) techniques provide the state-of-the-art in clustering of hyperspectral images (HSIs). However, their computational complexity hinders their applicability to large-scale HSIs. In this paper, we propose a large-scale SSC-based method, which can effectively process large HSIs while also achieving improved clustering accuracy compared to the current SSC methods. We build our approach based on an emerging concept of sketched subspace clustering, which was to our knowledge not explored at all in hyperspectral imaging yet. Moreover, there are only scarce results on any large-scale SSC approaches for HSI. We show that a direct application of sketched SSC does not provide a satisfactory performance on HSIs but it does provide an excellent basis for an effective and elegant method that we build by extending this approach with a spatial prior and deriving the corresponding solver. In particular, a random matrix constructed by the Johnson-Lindenstrauss transform is first used to sketch the self-representation dictionary as a compact dictionary, which significantly reduces the number of sparse coefficients to be solved, thereby reducing the overall complexity. In order to alleviate the effect of noise and within-class spectral variations of HSIs, we employ a total variation constraint on the coefficient matrix, which accounts for the spatial dependencies among the neighbouring pixels. We derive an efficient solver for the resulting optimization problem, and we theoretically prove its convergence property under mild conditions. The experimental results on real HSIs show a notable improvement in comparison with the traditional SSC-based methods and the state-of-the-art methods for clustering of large-scale images

The cognitive representation of the large-scale environment

This thesis is concerned with the processes involved in the acquisition and use of cognitive representations of the large-scale environment, or 'cognitive mapping'. The first half of the thesis reviews relevant literature in three main sections. Firstly, the historical roots of the subject are described in chapters on early investigations of wayfinding and orientation, theoretical models of behaviour incorporating the concept of subjective knowledge and multidisciplinary studies of environmental images. Secondly, studies of group differences in cognitive mapping and initial theoretical frameworks are reviewed. Finally, the current state of research evidence is assessed in relation to four research areas. These concern methodological issues, the structure of internal representations, the process of acquiring new representations and individual differences in cognitive mapping.The remainder of the thesis reports and discusses four experimental studies of issues which were judged to be inadequately researched on the basis of the literature review. The first compared the utility of freehand sketch-mapping and three-dimensional modelling with educated, adult subjects. The second investigated the rate of acquisition of cognitive maps, particularly during the first days of environmental experience; using a structured mapping task. Objective accuracy, subjective ratings of accuracy and recall order were examined in relation to building usage and spatial experience. The third experiment compared artificial map learning with spatial relations ability, visual imagery ratings and everyday map usage. Additionally, the effect upon learning of stimulus mode (map or verbal list), response mode and stimulus-response mode compatibility was measured. The final experiment compared performance upon the 'real-life' mapping task of the second study with the map learning and spatial ability measures used in the third study. Evidence was found that cognitive mapping. spatial ability and attitudes to navigational problems are positively related. It was concluded that future work should emphasize the process of cognitive mapping and the relationship between map form and practical needs