Exploring the Notion of Spatial Lenses

Allen, Christopher; Hervey, Thomas; Lafia, Sara; Phillips, Daniel W.; Vahedi, Behzad; Kuhn, Walther

doi:10.1007/978-3-319-45738-3_17

Cited by 9 publications

(7 citation statements)

References 10 publications

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“…To model the spatial context of interventions, model components representing the Urban Environment and human agents have to be georeferenced, resulting in multiple GIS layers interacting with each other. Decisions have to be taken concerning which components to model, how to conceptualize them in terms of spatial information (eg, as discrete object, continuous field, network, or event 55 ), on what resolution levels to represent them and what operations to use for their interactions. 56 While it is tempting to represent components and processes as granular and detailed as possible, the model has to remain verifiable.…”

Section: Modeling Human-environment Interactionsmentioning

confidence: 99%

Agent-based modeling of urban exposome interventions: prospects, model architectures, and methodological challenges

et al. 2022

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With ever more people living in cities worldwide, it becomes increasingly important to understand and improve the impact of the urban habitat on livability, health behaviors and health outcomes. However, implementing interventions that tackle the exposome in complex urban systems can be costly and have long-term, sometimes unforeseen, impacts. Hence, it is crucial to assess the health impact, cost-effectiveness, and social distributional impacts of possible urban exposome interventions before implementing them. Spatial agent-based modeling can capture complex behavior-environment interactions, exposure dynamics, and social outcomes in a spatial context. This paper discusses model architectures and methodological challenges for successfully modeling urban exposome interventions using spatial agent-based modeling. We review the potential and limitations of the method; model components required to capture active and passive exposure and intervention effects; human-environment interactions and their integration into the macro-level health impact assessment and social costs benefit analysis; strategies for model calibration. Major challenges for a successful application of agent-based modeling to urban exposome intervention assessment are (1) the design of realistic behavioral models that can capture different types of exposure and that respond to urban interventions, (2) the mismatch between the possible granularity of exposure estimates and the evidence for corresponding exposure-response functions, (3) the scalability issues that emerge when aiming to estimate long-term effects such as health and social impacts based on high-resolution models of human-environment interactions, (4) as well as the data- and computational complexity of calibrating the resulting agent-based model. Although challenges exist, strategies are proposed to improve the implementation of ABM in exposome research.

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Section: Modeling Human-environment Interactionsmentioning

confidence: 99%

Agent-based modeling of urban exposome interventions: prospects, model architectures, and methodological challenges

et al. 2022

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“…They provide us with a set of interchangeable lenses through which research data can be spatialized and viewed. 43 To produce maps, we first produce a field of continuous topic values from the texts of research documents with a topic value at each position. This can be thought of as a landscape or surface of topic values.…”

Section: Data Visualizationmentioning

confidence: 99%

Mapping research topics at multiple levels of detail

et al. 2021

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Many institutions use metrics to evaluate their research productivity; however, it is challenging to effectively summarize and evaluate research across academic disciplines. We use topic modeling to develop maps of science at multiple levels of detail. The maps were used in an institutional review and evaluated by leading researchers at an earth science institute. We demonstrate that mapping research topics supports the review process by offering insights into interdisciplinary research collaborations and areas of expertise at the institute.

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“…On this account, networks are one of a range of concepts needed for interpreting the environment and for reasoning with GIS. These concepts constitute conceptual “lenses” through which the environment can be studied independently of technical representations (Allen et al, 2016 ; Kuhn & Ballatore, 2015 ). Besides the base concept of location , allowing for metric distance assessments in space, Kuhn distinguished the following content concepts, which we interpret here in a broader research context: Fields are understood as continuous functions (Galton, 2004 ) whose domain is time and location, and whose range may be any kind of measurable quality.…”

Section: Related Workmentioning

confidence: 99%

A conceptual model for automating spatial network analysis

Scheider

Jong

2021

Transactions in GIS

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Spatial network analysis is a collection of methods for measuring accessibility potentials as well as for analyzing flows over transport networks. Though it has been part of the practice of geographic information systems for a long time, designing network analytical workflows still requires a considerable amount of expertise. In principle, artificial intelligence methods for workflow synthesis could be used to automate this task. This would improve the (re)usability of analytic resources. However, though underlying graph algorithms are well understood, we still lack a conceptual model that captures the required methodological know-how. The reason is that in practice this know-how goes beyond graph theory to a significant extent. In this article we suggest interpreting spatial networks in terms of quantified relations between spatial objects, where both the objects themselves and their relations can be quantified in an extensive or an intensive manner. Using this model, it becomes possible to effectively organize data sources and network functions towards common analytical goals for answering questions.We tested our model on 12 analytical tasks, and evaluated automatically synthesized workflows with network experts.Results show that standard data models are insufficient for answering questions, and that our model adds information crucial for understanding spatial network functionality.

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Exploring the Notion of Spatial Lenses

Cited by 9 publications

References 10 publications

Agent-based modeling of urban exposome interventions: prospects, model architectures, and methodological challenges

Agent-based modeling of urban exposome interventions: prospects, model architectures, and methodological challenges

Mapping research topics at multiple levels of detail

A conceptual model for automating spatial network analysis

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