General Spatial Pattern and Meta-Pattern Model for Problems That Need Analytical Approach in Complex Spatial Systems

Spatial Pattern (SP) Description, Identification, and Application Methodology (SPDIAM) was developed for describing and detecting spatial economic, social, and environmental phenomena and providing basic information technology (IT) artefacts that can be used for the spatial analysis development using GIS technologies. SPDIAM allows urban planning and design practitioners to describe SP in a computerized manner, identify SP automatically, and apply them in the spatial planning and design domain. In this article, we explain the general SP and spatial meta-pattern model, used in SPDIAM, that is based on the theory of Complex Spatial System (CSS), spatial configuration, and spatial capital concepts and is presented using UML diagrams as standard used for visualization of project models from structure and behavior points of views. The practical experiment of describing and identifying 6 basic spatial meta-pattern values is conducted using the new algorithm that combines Space Syntax method, Visibility Graph Analysis (VGA), and VGA measures to create a computer model of space and to quantify its configuration, which can then be used to handle geographic and geometric data associated with attribute information, to perform spatial, mathematical, and statistical calculations and to visualize SP. The results of the experiment show that the model and the algorithm are appropriate for spatial meta-patterns identification, and the best results can be achieved using VGA measure Isovist Compactness. In the future, general SP and the spatial meta-pattern model can be used to describe and identify complex SP and to solve problems in CSS with the help of the spatial meta-pattern values described in this article.

Spatializing the Image

<p>Modern society has become ocular-centric as a result of technological development making the production and distribution of images easier than ever before. This ocular bias extends to architecture. Rather than resisting the increasingly ocular-centric nature of our social-media driven culture, this research aims to find new methods for designing space which incorporate a tactile process. This process simultaneously focuses on the creation of marketable perspectives. Through this research I advocate for tactility in the design process to evoke spatial awareness of the image. This research portfolio operates through a design-led research methodology where knowledge is uncovered by designing. Hundreds of models were produced and critically reflected upon in terms of both their process and outcome. The research culminates with the development of a design process centred on using architectural models as design tools. Referred to as devices, these models are spatial systems that are able to be manipulated by hand to alter the composition of a perspective view. Although focusing on the image, the physicality of the devices implicate spatial awareness in the design process ensuring the design is considered in both two and three dimensions. A design for the proposed Kapiti Island Biosecurity Gateway Centre formed an architectual testing ground which was used to evalute the design process developed in this research. Influenced by the design process the architecture itself also became an optical device. The resulting design controls and composes views through concealing, revealing, superimposing, aligning and framing particular elements. The final outcome provides visitors with a choreographed journey of highly considered perspective compositions</p>

Spatializing the Image

<p>Modern society has become ocular-centric as a result of technological development making the production and distribution of images easier than ever before. This ocular bias extends to architecture. Rather than resisting the increasingly ocular-centric nature of our social-media driven culture, this research aims to find new methods for designing space which incorporate a tactile process. This process simultaneously focuses on the creation of marketable perspectives. Through this research I advocate for tactility in the design process to evoke spatial awareness of the image. This research portfolio operates through a design-led research methodology where knowledge is uncovered by designing. Hundreds of models were produced and critically reflected upon in terms of both their process and outcome. The research culminates with the development of a design process centred on using architectural models as design tools. Referred to as devices, these models are spatial systems that are able to be manipulated by hand to alter the composition of a perspective view. Although focusing on the image, the physicality of the devices implicate spatial awareness in the design process ensuring the design is considered in both two and three dimensions. A design for the proposed Kapiti Island Biosecurity Gateway Centre formed an architectual testing ground which was used to evalute the design process developed in this research. Influenced by the design process the architecture itself also became an optical device. The resulting design controls and composes views through concealing, revealing, superimposing, aligning and framing particular elements. The final outcome provides visitors with a choreographed journey of highly considered perspective compositions</p>

Dynamical efficiency for multimodal time-varying transportation networks

Spatial systems that experience congestion can be modeled as weighted networks whose weights dynamically change over time with the redistribution of flows. This is particularly true for urban transportation networks. The aim of this work is to find appropriate network measures that are able to detect critical zones for traffic congestion and bottlenecks in a transportation system. We propose for both single and multi-layered networks a path-based measure, called dynamical efficiency, which computes the travel time differences under congested and free-flow conditions. The dynamical efficiency quantifies the reachability of a location embedded in the whole urban traffic condition, in lieu of a myopic description based on the average speed of single road segments. In this way, we are able to detect the formation of congestion seeds and visualize their evolution in time as well-defined clusters. Moreover, the extension to multilayer networks allows us to introduce a novel measure of centrality, which estimates the expected usage of inter-modal junctions between two different transportation means. Finally, we define the so-called dilemma factor in terms of number of alternatives that an interconnected transportation system offers to the travelers in exchange for a small increase in travel time. We find macroscopic relations between the percentage of extra-time, number of alternatives and level of congestion, useful to quantify the richness of trip choices that a city offers. As an illustrative example, we show how our methods work to study the real network of a megacity with probe traffic data.

System alignment supports cross-domain learning and zero-shot generalisation

Recent findings suggest conceptual relationships hold across modalities. For instance, if two concepts occur in similar linguistic contexts, they also likely occur in similar visual contexts. These similarity structures may provide a valuable signal for system alignment when learning to map between domains, such as when learning the names of objects. To assess this possibility, we conducted a paired-associate learning experiment in which participants mapped objects that varied on two visual features to locations that varied along two spatial dimensions. We manipulated whether the featural and spatial systems were \textit{aligned} or \textit{misaligned}. Although system alignment was not required to complete this supervised learning task, we found that participants learned more efficiently when systems aligned and that aligned systems facilitated zero-shot generalisation. We fit a variety of models to individuals' responses and found that models which included an offline unsupervised alignment mechanism best accounted for human performance. Our results provide empirical evidence that people align entire representation systems to accelerate learning, even when learning seemingly arbitrary associations between two domains.