Accessible path finding for historic urban environments: feature extraction and vectorization from point clouds

Sidewalk inventory is a topic whose importance is increasing together with the widespread use of smart city management. In order to manage the city properly and to make informed decisions, it is necessary to know the real conditions of the city. Furthermore, when planning and calculating cultural routes within the city, these routes must take into account the specific needs of all users. Therefore, it is important to know the conditions of the city’s sidewalk network and also their physical and geometrical characteristics. Typically, sidewalk network are generated basing on existing cartographic data, and sidewalk attributes are gathered through crowdsourcing. In this paper, the sidewalk network of an historic city was produced starting from point cloud data. The point cloud was semantically segmented in ”roads” and ”sidewalks”, and then the cluster of points of sidewalks surfaces were used to compute sidewalk attributes and to generate a vector layer composed of nodes and edges. The vector layer was then used to compute accessible paths between Points of Interest, using QGIS. The tests made on a real case study, the historic city and UNESCO site of Sabbioneta (Italy), shows a vectorization accuracy of 98.7%. In future, the vector layers and the computed paths could be used to generate maps for city planners, and to develop web or mobile phones routing apps.Ministerio de Ciencia e Innovación | Ref. RYC2020-029193-

Tanzania: Pilot Rural Investment Climate Assessment. Stimulating Nonfarm Microenterprise Growth

Tanzania’s Pilot Rural Investment Climate Assessment (RICA) measures the economic environment of non-farm entrepreneurs. The pilot assessment has three key objectives: it aims to better understand the rural non-farm economy in Tanzania, shed light on rural enterprise dynamics and business constraints, and reflect on areas where government policies are readily directed to help promote rural non-farm enterprise activity. The RICA is based on an analysis of a unique survey data set collected by the National Bureau of Statistics (NBS) during January and March 2005, covering enterprises, households, and communities in all seven geographical zones of the country. Selected findings are: (i) Non-farm activities are an important source of income for approximately 1.4 million rural households, (ii) Tanzanian rural non-farm enterprises differ from their urban counterparts, (iii) the predominant entrepreneurial activity is trading, (iv) labor productivity is typically low, (v) formal enterprises have higher levels of labor productivity than informal, (vi) the rate of new firm creation appears to be lower than in other African countries, and (vii) only a minority of enterprises propels employment growth. The pilot approach call for a careful evaluation of the following recommendations, which presented to stimulate dialogue and future analysis: (i) favorable policies and investments for agriculture play a big role for rural enterprises, (ii) maintaining favorable internal trade policies may therefore be of utmost importance in determining enterprise performance, (iii) microcredit and savings may offer a tool for promoting rural non-farm activity in buoyant rural markets, (iv) easing bottlenecks in rural infrastructure is important, (v) exploring options for better telecommunications via private sector cell phone nodes may be an attractive policy option to stimulate entrepreneurial activities, (vi) continuation of business registration reform and effective implementation at the local level remains a high priority, and (vii) future analysis should address knowledge gaps.Tanzania; rural labor markets; enterprise performance; informal sector

Does better local governance improve district growth performance in Indonesia?

A large literature suggests that countries with better governance have higher growth rates. We explore whether this is also true at the sub-national level in Indonesia. We exploit a new dataset of firm perceptions of the quality of economic governance in 243 districts across Indonesia to estimate the impact of nine different dimensions of governance on district growth. Surprisingly, we find relatively little evidence of a robust relationship between the quality of governance and economic performance. However, we do find support for the idea that structural variables, such as economic size, natural resource endowments and population, have a direct influence on the quality of local governance as well as on economic growth. This suggests that efforts to improve local governance should pay greater attention to understanding how such structural characteristics shape the local political economy and how this in turn influences economic performance.governance, institutions, economic performance, economic growth

The variability of urban safety performance functions for different road elements: an Italian case study

Background: Urban safety performance functions are used to predict crash frequencies, mostly based on Negative Binomial (NB) count models. They could be differentiated for considering homogeneous subsets of segments/intersections and different predictors. Materials and methods: The main research questions concerned: a) finding the best possible subsets for segments and intersections for safety modelling, by discussing the related problems and inquiring into the variability of predictors within the subsets; b) comparing the modelling results with the existing literature to highlight common trends and/or main differences; c) assessing the importance of additional crash predictors, besides traditional variables. In the context of a National research project, traffic volumes, geometric, control and additional variables were collected for road segments and intersections in the City of Bari, Italy, with 1500 fatal+injury related crashes (2012–2016). Six NB models were developed for: one/two-way homogeneous segments, three/four-legged, signalized/unsignalized intersections. Results: Crash predictors greatly vary within the different subsets considered. The effect of vertical signs on minor roads/driveways, critical sight distance, cycle crossings, pavement/markings maintenance was specifically discussed. Some common trends but also differences in both types and effect of crash predictors were found by comparing results with literature. Conclusion: The disaggregation of urban crash prediction models by considering different subsets of segments and intersections helps in revealing the specific influence of some predictors. Local characteristics may influence the relationships between well-established crash predictors and crash frequencies. A significant part of the urban crash frequency variability remains unexplained, thus encouraging research on this topic

The variability of urban safety performance functions for different road elements: an Italian case study

Abstract Background Urban safety performance functions are used to predict crash frequencies, mostly based on Negative Binomial (NB) count models. They could be differentiated for considering homogeneous subsets of segments/intersections and different predictors. Materials and methods The main research questions concerned: a) finding the best possible subsets for segments and intersections for safety modelling, by discussing the related problems and inquiring into the variability of predictors within the subsets; b) comparing the modelling results with the existing literature to highlight common trends and/or main differences; c) assessing the importance of additional crash predictors, besides traditional variables. In the context of a National research project, traffic volumes, geometric, control and additional variables were collected for road segments and intersections in the City of Bari, Italy, with 1500 fatal+injury related crashes (2012–2016). Six NB models were developed for: one/two-way homogeneous segments, three/four-legged, signalized/unsignalized intersections. Results Crash predictors greatly vary within the different subsets considered. The effect of vertical signs on minor roads/driveways, critical sight distance, cycle crossings, pavement/markings maintenance was specifically discussed. Some common trends but also differences in both types and effect of crash predictors were found by comparing results with literature. Conclusion The disaggregation of urban crash prediction models by considering different subsets of segments and intersections helps in revealing the specific influence of some predictors. Local characteristics may influence the relationships between well-established crash predictors and crash frequencies. A significant part of the urban crash frequency variability remains unexplained, thus encouraging research on this topic

Children\u27s Physical Activity and the Built Environment: The Impact of Neighbourhood Opportunities and Contextual Environmental Exposure

Childhood obesity rates have risen dramatically since 1981, in part due to decreased physical activity (PA) levels. Research suggests that PA is influenced in part by an individual’s exposure to and engagement with their built environment. Using a multi-tool protocol, this thesis examines how (a) neighbourhood opportunities facilitate or constrain children’s moderate-to-vigorous PA (MVPA) and (b) contextual environmental exposure facilitates or constrains children’s MVPA. Results suggest that children’s MVPA is influenced by their built environment, but more so by the contextual environments that they are directly exposed to rather than their overall neighbourhood settings. Children are mobile and unlikely to never leave their neighbourhood, especially considering that many parents drive their children to activities outside their neighbourhood. Examining contextual environmental exposure is a novel approach that can be used by researchers to clarify the environments that exert an influence on children’s MVPA

Cycling area can be a confounder and effect modifier of the association between helmet use and cyclists’ risk of death after a crash

The effect of helmet use on reducing the risk of death in cyclists appears to be distorted by some variables (potential confounders, effect modifiers, or both). Our aim was to provide evidence for or against the hypothesis that cycling area may act as a confounder and effect modifier of the association between helmet use and risk of death of cyclists involved in road crashes. Data were analysed for 24,605 cyclists involved in road crashes in Spain. A multiple imputation procedure was used to mitigate the effect of missing values. We used multilevel Poisson regression with province as the group level to estimate the crude association between helmet use and risk of death, and also three adjusted analyses: (1) for cycling area only, (2) for the remaining variables which may act as confounders, and (3) for all variables. Incidence–density ratios (IDR) and their 95% confidence intervals were calculated. Crude IDR was 1.10, but stratifying by cycling area disclosed a protective, differential effect of helmet use: IDR = 0.67 in urban areas, IDR = 0.34 on open roads. Adjusting for all variables except cycling area yielded similar results in both strata, albeit with a smaller difference between them. Adjusting for cycling area only yielded a strong association (IDR = 0.42), which was slightly lower in the adjusted analysis for all variables (IDR = 0.45). Cycling area can act as a confounder and also appears to act as an effect modifier (albeit to a lesser extent) of the risk of cyclists’ death after a crash

WWPA: Factor Analysis of Young Driver Perceptions, Behaviours and Driving Experience. WWPB: Predictors of Time to First Crash for Young Drivers: Survival Analysis

Analysis of young drivers behaviour, experience and first crash survival analysi

Measuring the impact of spatial network layout on community social cohesion: a cross-sectional study

Background There is now a substantial body of research suggesting that social cohesion, a collective characteristic measured by the levels of trust, reciprocity and formation of strong social bonds within communities, is an important factor in determining health. Of particular interest is the extent to which factors in the built environment facilitate, or impede, the development of social bonds. Severance is a characteristic of physical environments which is hypothesized to inhibit cohesion. In the current study we test a number of characteristics of spatial networks which could be hypothesized to relate either to severance, or directly to community cohesion. Particular focus is given to our most promising variable for further analysis (Convex Hull Maximum Radius 600 m). Methods In the current study we analysed social cohesion as measured at Enumeration District level, aggregated from a survey of 10,892 individuals aged 18 to 74 years in the Caerphilly Health and Social Needs Cohort Study, 2001. In a data mining process we test 16 network variables on multiple scales. The variable showing the most promise is validated in a test on an independent data set. We then conduct a multivariate regression also including Townsend deprivation scores and urban/rural status as predictor variables for social cohesion. Results We find convex hull maximum radius at a 600 m scale to have a small but highly significant correlation with social cohesion on both data sets. Deprivation has a stronger effect. Splitting the analysis by tertile of deprivation, we find that the effect of severance as measured by this variable is strongest in the most deprived areas. A range of spatial scales are tested, with the strongest effects being observed at scales that match typical walking distances. Conclusion We conclude that physical connectivity as measured in this paper has a significant effect on social cohesion, and that our measure is unlikely to proxy either deprivation or the urban/rural status of communities. Possible mechanisms for the effect include intrinsic navigability of areas, and the existence of a focal route on which people can meet on foot. Further investigation may lead to much stronger predictive models of social cohesion

Associations between personal attitudes towards covid-19 and public space soundscape assessment: An example from antwerp, Belgium

The COVID-19 pandemic, and the lockdown events and policies that followed, led to significant changes in the built environment and how it is experienced by people and communities. Among those, variations in the acoustic environments were some of the most noticeable in cities. This study investigated the relationships between the perception of the acoustic environment (i.e., sound-scape) and different personal factors such as attitudes towards the pandemic and noise sensitivity, by performing a survey with 109 participants in an urban green public space in Antwerp (Belgium), shortly after most restrictions issued by the government were lifted in September 2020 when the first contamination wave ended. While preliminary in nature, the results of this data collection campaign show that people actively changing their behaviors (using less public transport or cycling more) assessed the soundscapes as less vibrant/exciting. People who were more concerned about the pandemic tended to notice more natural sounds and noise from traffic on nearby local roads. This same subset also put a bigger importance on the environmental quality of the public space than in the pre-pandemic period. Noise sensitivity also played a role, as an association was found between more-than-average noise sensitive persons and those more worried regarding the pandemic. Overall, the findings of this study confirm that at least part of the people have started to perceive the public space, including its soundscape, differently since the start of the pandemic