Dataset Information

Scale-Adjusted Metrics for Predicting the Evolution of Urban Indicators and Quantifying the Performance of Cities.

ABSTRACT: More than a half of world population is now living in cities and this number is expected to be two-thirds by 2050. Fostered by the relevancy of a scientific characterization of cities and for the availability of an unprecedented amount of data, academics have recently immersed in this topic and one of the most striking and universal finding was the discovery of robust allometric scaling laws between several urban indicators and the population size. Despite that, most governmental reports and several academic works still ignore these nonlinearities by often analyzing the raw or the per capita value of urban indicators, a practice that actually makes the urban metrics biased towards small or large cities depending on whether we have super or sublinear allometries. By following the ideas of Bettencourt et al. [PLoS ONE 5 (2010) e13541], we account for this bias by evaluating the difference between the actual value of an urban indicator and the value expected by the allometry with the population size. We show that this scale-adjusted metric provides a more appropriate/informative summary of the evolution of urban indicators and reveals patterns that do not appear in the evolution of per capita values of indicators obtained from Brazilian cities. We also show that these scale-adjusted metrics are strongly correlated with their past values by a linear correspondence and that they also display crosscorrelations among themselves. Simple linear models account for 31%-97% of the observed variance in data and correctly reproduce the average of the scale-adjusted metric when grouping the cities in above and below the allometric laws. We further employ these models to forecast future values of urban indicators and, by visualizing the predicted changes, we verify the emergence of spatial clusters characterized by regions of the Brazilian territory where we expect an increase or a decrease in the values of urban indicators.

SUBMITTER: Alves LG

PROVIDER: S-EPMC4565645 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Scale-Adjusted Metrics for Predicting the Evolution of Urban Indicators and Quantifying the Performance of Cities.

Alves Luiz G A LG Mendes Renio S RS Lenzi Ervin K EK Ribeiro Haroldo V HV

PloS one 20150910 9

More than a half of world population is now living in cities and this number is expected to be two-thirds by 2050. Fostered by the relevancy of a scientific characterization of cities and for the availability of an unprecedented amount of data, academics have recently immersed in this topic and one of the most striking and universal finding was the discovery of robust allometric scaling laws between several urban indicators and the population size. Despite that, most governmental reports and sev ...[more]

PMID: 26356081

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Project description:INTRODUCTION:Unobtrusive metrics that can auto-assess performance during clinical procedures are of value. Three approaches to deriving wearable technology-based metrics are explored: (1) eye tracking, (2) psychophysiological measurements [e.g. electrodermal activity (EDA)] and (3) arm and hand movement via accelerometry. We also measure attentional capacity by tasking the operator with an additional task to track an unrelated object during the procedure. METHODS:Two aspects of performance are measured: (1) using eye gaze and psychophysiology metrics and (2) measuring attentional capacity via an additional unrelated task (to monitor a visual stimulus/playing cards). The aim was to identify metrics that can be used to automatically discriminate between levels of performance or at least between novices and experts. The study was conducted using two groups: (1) novice operators and (2) expert operators. Both groups made two attempts at a coronary angiography procedure using a full-physics virtual reality simulator. Participants wore eye tracking glasses and an E4 wearable wristband. Areas of interest were defined to track visual attention on display screens, including: (1) X-ray, (2) vital signs, (3) instruments and (4) the stimulus screen (for measuring attentional capacity). RESULTS:Experts provided greater dwell time (63% vs 42%, p?=?0.03) and fixations (50% vs 34%, p?=?0.04) on display screens. They also provided greater dwell time (11% vs 5%, p?=?0.006) and fixations (9% vs 4%, p?=?0.007) when selecting instruments. The experts' performance for tracking the unrelated object during the visual stimulus task negatively correlated with total errors (r?=?-?0.95, p?=?0.0009). Experts also had a higher standard deviation of EDA (2.52 µS vs 0.89 µS, p?=?0.04). CONCLUSIONS:Eye tracking metrics may help discriminate between a novice and expert operator, by showing that experts maintain greater visual attention on the display screens. In addition, the visual stimulus study shows that an unrelated task can measure attentional capacity. Trial registration This work is registered through clinicaltrials.gov, a service of the U.S. National Health Institute, and is identified by the trial reference: NCT02928796.

Project description:Background and aimsCoastal wetlands have evolved to withstand stressful abiotic conditions through the maintenance of hydrologic feedbacks between vegetation production and flooding. However, disruption of these feedbacks can lead to ecosystem collapse, or a regime shift from vegetated wetland to open water. To prevent the loss of critical coastal wetland habitat, we must improve understanding of the abiotic-biotic linkages among flooding and wetland stability. The aim of this research was to identify characteristic landscape patterns and thresholds of wetland degradation that can be used to identify areas of vulnerability, reduce flooding threats and improve habitat quality.MethodsWe measured local- and landscape-scale responses of coastal wetland vegetation to flooding stress in healthy and degrading coastal wetlands. We hypothesized that conversion of Spartina patens wetlands to open water could be defined by a distinct change in landscape configuration pattern, and that this change would occur at a discrete elevation threshold.Key resultsDespite similarities in total land and water cover, we observed differences in the landscape configuration of vegetated and open water pixels in healthy and degrading wetlands. Healthy wetlands were more aggregated, and degrading wetlands were more fragmented. Generally, greater aggregation was associated with higher wetland elevation and better drainage, compared with fragmented wetlands, which had lower elevation and poor drainage. The relationship between vegetation cover and elevation was non-linear, and the conversion from vegetated wetland to open water occurred beyond an elevation threshold of hydrologic stress.ConclusionsThe elevation threshold defined a transition zone where healthy, aggregated, wetland converted to a degrading, fragmented, wetland beyond an elevation threshold of 0.09 m [1988 North American Vertical Datum (NAVD88)] [0.27 m mean sea level (MSL)], and complete conversion to open water occurred beyond 0.03 m NAVD88 (0.21 m MSL). This work illustrates that changes in landscape configuration can be used as an indicator of wetland loss. Furthermore, in conjunction with specific elevation thresholds, these data can inform restoration and conservation planning to maximize wetland stability in anticipation of flooding threats.

Dataset Information

Scale-Adjusted Metrics for Predicting the Evolution of Urban Indicators and Quantifying the Performance of Cities.

Publications

Scale-Adjusted Metrics for Predicting the Evolution of Urban Indicators and Quantifying the Performance of Cities.

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