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Location and accessibility are core concepts for land-value research. However, the perspective is still limited in their conceptual and methodological application to cities from the Global South. The objective of this research is to bridge concepts and definitions to comprehensively operationalize accessibility indicators and uncover its relation with residential land-values in Guatemala City. We developed a multivariate regression model using the following access metrics: (1) geographic-access indices that were computed using time-based analyses per transport mode; (2) geometric-access metrics estimated via Space Syntax at various spatial scales; (3) a proposed geometric via geographic-access metric computed as potential access to network centrality. A variable selection process allowed to assess the information contribution of each variable in building a parsimonious model. We assessed the model in the context of model variations that represent common approaches used in existing literature. Geographic access to the core business district has the highest impact on the land-values, followed by proximity to urban areas with high geometric-access, measured as geometric via geographic access. Geometric accessibility at neighbourhood and city-wide scales add spatialized information that contributes to a parsimonious model and reduces spatial dependence. The model yielded the highest goodness of fit and prediction accuracy compared with the model variations. We concluded that Guatemala City land-values follow a predominant monocentric structure. Additionally, potential access to vital urban areas as identified via Space Syntax denotes the presence of economic activities, or potential for such, which were not explicitly addressed through the geographic-access metrics. The results have limitations but pose methodological possibilities relevant for research and practice in similar Latin American cities.

A frequent criticism of knowledge-based planning tools is the apparent mismatch between information frameworks used in their spatial models and the information needs of planning actors. Increasingly, these actors are contributing their context-specific knowledge during the development of such tools. Transferring this knowledge from actors to the model remains a challenge. This study establishes a set of design requirements for knowledge elicitation in small group settings and introduces game co-design as a method allowing planning actors and planning support experts to meet halfway between the technology and user domains in the so-called third space. We present an initial case where in three nominal group sessions, actors encountered and critiqued parameterized assumptions of their planning issues in a tangible game environment. Findings indicate that the method can elicit different types of knowledge (divergence) about a spatial system in operationalized terms (formalization). We discuss the potential of tangible game co-design as a modeling as learning exercise and its complementarity to dedicated digital technologies for more holistic planning support.

Cities are recognised as key players in global adaptation and mitigation efforts because the majority of people live in cities. However, in Europe, which is highly urbanized and one of the most advanced regions in terms of environmental policies, there is considerable diversity in the regional distribution, ambition and scope of climate change responses. This paper explores potential factors contributing to such diversity in 200 large and medium-sized cities across 11 European countries. We statistically investigate institutional, socio-economic, environmental and vulnerability characteristics of cities as potential drivers of or barriers to the development of urban climate change plans. Our results show that factors such as membership of climate networks, population size, GDP per capita and adaptive capacity act as drivers of mitigation and adaptation plans. By contrast, factors such as the unemployment rate, warmer summers, proximity to the coast and projected exposure to future climate impacts act as barriers. We see that, overall, it is predominantly large and prosperous cities that engage in climate planning, while vulnerable cities and those at risk of severe climate impacts in the future are less active. Our analysis suggests that climate change planning in European cities is not proactive, i.e. not significantly influenced by anticipated future impacts. Instead, we found that the current adaptive capacity of a city significantly relates to climate planning. Along with the need to further explore these relations, we see a need for more economic and institutional support for smaller and less resourceful cities and those at high risk from climate change impacts in the future.

Cumulative burden assessment (CuBA) has the potential to inform planning and decision-making on health disparities related to multiple environmental burdens. However, scholars have raised concerns about the social complexity to be dealt with while conducting CuBA, suggesting that it should be addressed in an adaptive, participatory and transdisciplinary (APT) approach. APT calls for deliberation among stakeholders by engaging them in a process of social learning and knowledge co-production. We propose an interactive stakeholder-based approach that facilitates a science-based stakeholder dialogue as an interface for combining different knowledge domains and engendering social learning in CuBA processes. Our approach allows participants to interact with each other using a flexible and auditable CuBA model implemented within a shared workspace. In two workshops we explored the usefulness and practicality of the approach. Results show that stakeholders were enabled to deliberate on cumulative burdens collaboratively, to learn about the technical uncertainties and social challenges associated with CuBA, and to co-produce knowledge in a realm of both technical and societal challenges. The paper identifies potential benefits relevant for responding to social complexity in the CuBA and further recommends exploration of how our approach can enable or constraint social learning and knowledge co-production in CuBA processes under various institutional, social and political contexts.

Outdoor walking has positive impacts on older adults' health. It is crucial to identify less active older adults and to encourage them to take outdoor walks. Previous studies have shown that physical activity levels vary according to socioeconomic deprivation. However, knowledge on objectively measured older adults' outdoor walking levels is limited. This study investigated associations between area (socioeconomic) deprivation and older adults' objectively (geographic positioning system [GPS]) measured outdoor walking levels (i.e., walking durations and frequencies) in Birmingham, United Kingdom. It used a multilevel approach. The final sample included 173 participants (65 years and above). A questionnaire was used to collect data on personal characteristics (e.g., educational attainment as a proxy of individual deprivation, age, and marital status). The results show that independent of personal characteristics, area deprivation associates with outdoor walking durations. Participants from high-deprivation areas spend less time for outdoor walking than those from low-deprivation areas. Associations between area deprivation and outdoor walking frequencies were nonsignificant. Future research needs to investigate how attributes (e.g., environmental attributes) of low- and high-deprivation areas drive disparities in outdoor walking durations among older residents of low- and high-deprivation areas.