Background: Cities are becoming the socio-economic hubs for most of the world’s population. Understanding how our surroundings can mentally affect everyday life has become crucial to integrate environmental sustainability into urban development. The present review aims to explore the empirical studies investigating neural mechanisms underlying cognitive and emotional processes elicited by the exposure to different urban built and natural spaces. It also tries to identify new research questions and to leverageneurourbanismas a framework to achieve healthier and sustainable cities.Methods: By following the PRISMA framework, we conducted a structured search on PubMed, ProQuest, Web of Science, and Scopus databases. Only articles related to how urban environment–built or natural–affects brain activity through objective measurement (with either imaging or electrophysiological techniques) were considered. Further inclusion criteria were studies on human adult populations, peer-reviewed, and in English language.Results: Sixty-two articles met the inclusion criteria. They were qualitatively assessed and analyzed to determine the main findings and emerging concepts. Overall, the results suggest that urban built exposure (when compared to natural spaces) elicit activations in brain regions or networks strongly related to perceptual, attentional, and (spatial) cognitive demands. The city’s-built environment also triggers neural circuits linked to stress and negative affect. Convergence of these findings was observed across neuroscience techniques, and for both laboratory and real-life settings. Additionally, evidence also showed associations between neural social stress processing with urban upbringing or current city living–suggesting a mechanistic link to certain mood and anxiety disorders. Finally, environmental diversity was found to be critical for positive affect and individual well-being.Conclusion: Contemporary human-environment interactions and planetary challenges imply greater understanding of the neurological underpinnings on how the urban space affects cognition and emotion. This review provides scientific evidence that could be applied for policy making on improved urban mental health. Several studies showed that high-quality green or blue spaces, and bio-diverse urban areas, are important allies for positive neural, cognitive, and emotional processes. Nonetheless, the spatial perception in social contexts (e.g., city overcrowding) deserves further attention by urban planners and scientists. The implications of these observations for some theories in environmental psychology and research are discussed. Future work should take advantage of technological advancements to better characterize behavior, brain physiology, and environmental factors and apply them to the remaining complexity of contemporary cities.

The objective of this research is to propose a theoretical model based on studies on residents’ quality of life in smart tourism destinations. Smart tourism destinations are territories based on information and communication technologies (ICT), which improve travelers’ tourist experiences as well as affect the quality of life of residents. To know the context of the relationships between tourism and quality of life, main studies and theories regarding these two phenomena are analyzed. Likewise, the relationship between smart places and quality of life is also studied. Therefore, a theoretical model on residents’ quality of life in smart tourism destinations is proposed based on a systematized analysis of the literature. From the theoretical model, it is perceived that residents’ overall life satisfaction results from the relationship between perceived tourism impacts and satisfaction with specific life factors, and they are measured by qualitative indicators. Also, it is identified that the quality of life of residents is clearly influenced by the impacts of tourism and ICTs. In addition, it is understood that the residents’ overall life satisfaction corroborates for the further development of the smart tourism destination. Finally, we understand that the knowledge of residents’ perception and satisfaction of their quality of life contribute to formulation and implementation of urban and tourism development policies in smart tourism destinations.

The complexities of coupled environmental and human systems across the space and time of fragile systems challenge new data-driven methodologies. Combining geographic information systems (GIS) and artificial neural networks (ANN) allows us to design a model that forecasts the erosion changes in Costa da Caparica, Lisbon, Portugal, for 2021, with a high accuracy level. The GIS–ANN model proves to be a powerful tool, as it analyzes and provides the “where” and the “why” dynamics that have happened or will happen in the future. According to the literature, ANNs present noteworthy advantages compared to the other methods that are used for prediction and decision making in urban coastal areas. In order to conduct a sensitivity analysis on natural and social forces, as well as dynamic relations in the dune–beach system of the study area, two types of ANNs were tested on a GIS environment: radial basis function (RBF) and multilayer perceptron (MLP). The GIS–ANN model helps to understand the factors that impact coastal erosion changes, and the importance of having an intelligent environmental decision support system to address these risks. This quantitative knowledge of the erosion changes and the analytical map-based frame are essential for an integrated management of the area and the establishment of pro-sustainability policies.

While the role of cities and regions is increasingly acknowledged for climate action and discussed in the literature on sustainability transitions, the specific condition of peripheral regions has received less attention. This article develops a bibliometric review to shed light and discuss how the (multi-dimensional) notion of periphery has been conceived and implicitly declinate in different literature streams studying low-carbon sustainability transitions at the sub-national level. While the studies explicitly addressing the issues of peripherality are still scarce, the article identifies four critical dimensions that contribute to frame structural bottlenecks and opportunities: socio-spatial unevenness, asset fragility, network positionality and agency and the multi-scalar embeddedness of transition policies. At the interface of urban and regional studies and sustainability transitions’ research, these dimensions open up new research challenges and trading zones ahead for peripheral regions on navigating troubled waters of sustainability transitions.

The simulation and analysis of future land use and land cover—LULC scenarios using artificial neural networks (ANN)—has been applied in the last 25 years, producing information for environmental and territorial policy making and implementation. LULC changes have impacts on many levels, e.g., climate change, biodiversity and ecosystem services, soil quality, which, in turn, have implications for the landscape. Therefore, it is fundamental that planning is informed by scientific evidence. The objective of this work was to develop a geographic model to identify the main patterns of LULC transitions between the years 2000 and 2018, to simulate a baseline scenario for the year 2036, and to assess the effectiveness of the Chapecó River ecological corridor (an area created by State Decree No. 2.957/2010), regarding the recovery and conservation of forest remnants and natural fields. The results indicate that the forest remnants have tended to recover their area, systematically replacing silviculture areas. However, natural fields (grassland) are expected to disappear in the near future if proper measures are not taken to protect this ecosystem. If the current agricultural advance pattern is maintained, only 0.5% of natural fields will remain in the ecological corridor by 2036. This LULC trend exposes the low effectiveness of the ecological corridor (EC) in protecting and restoring this vital ecosystem.