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Urban growth and decline occur every year and show changes in urban areas. Although various approaches to detect urban changes have been developed, they mainly use large-scale satellite imagery and socioeconomic factors in urban areas, which provides an overview of urban changes. However, since people explore places and notice changes daily at the street level, it would be useful to develop a method to identify urban changes at the street level and demonstrate whether urban growth or decline occurs there. Thus, this study seeks to use street-level panoramic images from Google Street View to identify urban changes and to develop a new way to evaluate the growth and decline of an urban area. After collecting Google Street View images year by year, we trained and developed a deep-learning model of an object detection process using the open-source software TensorFlow. By scoring objects and changes detected on a street from year to year, a map of urban growth and decline was generated for Midtown in Detroit, Michigan, USA. By comparing socioeconomic changes and the situations of objects and changes in Midtown, the proposed method is shown to be helpful for analyzing urban growth and decline by using year-by-year street view images., Competing Interests: The authors have declared that no competing interests exist.

A key challenge of environmental planning is to craft recommendations for future sustainable spatial development amid ubiquitous uncertainties. This paper aims to explore how different data uncertainties, usually unknown to the planner, may influence environmental planning recommendations. We apply a case study-based approach, in which we provide three illustrative examples of how data with different kinds and levels of uncertainty affect environmental assessments and, by that, the decision-support provided by environmental planning. The cases stem from different spatial levels in Germany and consider 'Regional soil-based climate change mitigation' in the region of Hannover, 'State-wide habitat conservation siting' in the federal state of Saxony-Anhalt, and 'National renewable energy planning'. Based on the three examples, we discuss implications for planning practice and derive recommendations for further research. The three cases studies illustrate the substantial effects of data uncertainty on environmental assessments and planning recommendations derived from those results. We identify four problem constellations of dealing with data uncertainty in environmental planning that relate to the severeness of uncertainty impacts, the responsibility of the decision-maker, and the kinds of impacts that wrong decisions may have. We close with recommendations for further research, among others to develop robust and pragmatic methods for identifying the uncertainty levels in environmental data and assessment results., Competing Interests: The authors have declared that no competing interests exist.

Background: Exposure to green space has beneficial effects on several cognitive and behavioral aspects. However, to our knowledge, no study addressed intelligence as outcome. We investigated whether the level of urbanicity can modify the association of residential green space with intelligence and behavior in children., Methods and Findings: This study includes 620 children and is part of the East Flanders Prospective Twin Survey (EFPTS), a registry of multiple births in the province of East Flanders, Belgium. Intelligence was assessed with the Wechsler Intelligence Scale for Children-Revised (WISC-R) in 620 children (310 twin pairs) between 7 and 15 years old. From a subset of 442 children, behavior was determined based on the Achenbach Child Behavior Checklist (CBCL). Prenatal and childhood residential addresses were geocoded and used to assign green space indicators. Mixed modeling was performed to investigate green space in association with intelligence and behavior while adjusting for potential confounding factors including sex, age, parental education, neighborhood household income, year of assessment, and zygosity and chorionicity. We found that residential green space in association with both intelligence and behavior in children was modified by the degree of urbanicity (p < 0.001). In children living in an urban environment, multivariable adjusted mixed modeling analysis revealed that an IQR increment of residential green space (3,000-m radius) was associated with a 2.6 points (95% CI 1.4-3.9; p < 0.001) higher total intelligence quotient (IQ) and 2.0 points (95% CI -3.5 to -0.4; p = 0.017) lower externalizing behavioral score. In children residing in a rural or suburban environment, no association was found. A limitation of this study is that no information was available on school location and the potential for unmeasured confounding (e.g., time spend outdoors)., Conclusions: Our results indicate that residential green space may be beneficial for the intellectual and the behavioral development of children living in urban areas. These findings are relevant for policy makers and urban planners to create an optimal environment for children to develop their full potential., Competing Interests: The authors have declared that no competing interests exist.

Over the past few decades many corporate organisations have moved to open-plan office designs, mostly due to financial and logistical benefits. However, recent studies have found significant drawbacks to open plan offices and it is unclear how office designs can facilitate the best work output and company culture. Current design practice aims to optimise efficiency of space, but no previous research has tested the effect of office design experimentally in a working office. This paper describes an experiment comparing four different office designs (Open-plan, Zoned open-plan, Activity based, and Team offices) against a suite of wellbeing and productivity metrics in a real world technology company. Results suggest that two very different designs (Zoned open-plan and Team offices) perform well compared to Open-plan office designs. Zoned open-plan and Team office designs improved employee satisfaction, enjoyment, flow, and productivity, while Activity based and Open-plan designs performed poorly by comparison. The Open-plan office design was rated more poorly by employees, had higher levels of unsafe noise, and once employees no longer had to be in the Open-plan office design of the experiment, they spent more time at their desks., Competing Interests: Authors 1 and 3 (JP, MH) are employed by Booking.com. Booking.com fully funded this research, but did not have any influence over the study design, or decision to publish. Data collection and analysis was conducted using Booking.com data resources. The Booking Public Relations and Data Privacy teams checked the manuscript and submitted data for factual correctness and to ensure no commercially sensitive or PII information was released. Author 4 (WO) is employed by CBRE Consulting, and was contracted by Booking.com to manage the project. CBRE Consulting did not provide any funding, and had no influence over any stage of the project. Author 2 (EN) is employed by Learn Adapt Build, and was contracted by CBRE Consulting to advise on the data collection and analysis stages of the project. Learn Adapt Build did not provide any funding for any stage of the project. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Eco-engineering and the installation of green infrastructure such as artificial floating islands (AFIs), are novel techniques used to support biodiversity. The European Convention on Biological Diversity highlighted the development of green infrastructure as a key method of enhancement in degraded habitats. Research specifically on AFIs in marine environments has largely focused on their ecological functioning role and engineering outcomes, with little consideration for the social benefits or concerns. The aim of this study was to gain an understanding of public perception of coastal habitat loss in the UK and AFIs as a method of habitat creation in coastal environments. This was achieved via a survey, consisting of six closed and two open questions. Of the 200 respondents, 94.5% were concerned about the loss of coastal habitats in the UK, but less than a third were aware of habitat restoration or creation projects in their area of residence. There was a positive correlation between proximity of residency to the coast and knowledge of habitat restoration or creation projects. The majority of the respondents understood the ecological functioning role of AFIs and 62% would preferably want successful plant growth and avian species utilising the AFI. Nearly a third of the respondents had concerns about AFI installations, such as the degradation of the plastic matrix, long term maintenance and disturbance of native species. Despite 90.9% of the respondents supporting the installation of AFIs, the concerns of the public must be addressed during the planning stages of any habitat creation project., Competing Interests: The authors have declared that no competing interests exist.

Introduction: Assessing the contextual factors that influence walking for transportation is important to develop more walkable environments and promote physical activity. To advance previous research focused on residential environments and overall walking for transportation, the present study investigates objective environmental factors assessed around the residence, the workplace, the home--work itinerary, and the home--supermarket itinerary, and considered overall walking for transportation but also walking to work and to shops., Methods: Data from the RECORD Study involving 7290 participants recruited in 2007-2008, aged 30-79 years, and residing in the Paris metropolitan area were analyzed. Multilevel ordinal regression analyses were conducted to investigate environmental characteristics associated with self-reported overall walking for transportation, walking to work, and walking to shops., Results: High individual education was associated with overall walking for transportation, with walking to work, and walking to shops. Among workers, a high residential neighborhood education was associated with increased overall walking for transportation, while a high workplace neighborhood education was related to an increased time spent walking to work. The residential density of destinations was positively associated with overall walking for transportation, with walking to work, and with walking to shops, while the workplace density of destinations was positively associated with overall walking for transportation among workers. Environmental factors assessed around the itineraries were not associated with walking to work or to the shops., Conclusion: This research improves our understanding of the role of the environments on walking for transportation by accounting for some of the environments visited beyond the residential neighborhood. It shows that workers' walking habits are more influenced by the density of destinations around the workplace than around the residence. These results provide insight for the development of policies and programs to encourage population level active commuting.