Humming trains as an opportune source for imaging the shallow crust

<div><span>Freight trains are one of the most powerful and persistent seismic sources of cultural noise. They generate tremors equivalent to earthquakes of magnitude 1 that can be detectable up to 100 km distance.  Here, we propose to use the freight train passages as an opportunistic source of noise for passive seismic interferometry (SI). Usually, passive SI relies on blind correlations of long time series of noise for imaging and monitoring purposes. We suggest an alternative method based on noise source characterization, signal and station pairs selection, and specific seismic phase extraction (surface and body waves) for each virtual source to imaging the subsurface. To illustrate our novel method's potential, we show a case study in Canada's mineral exploration context, where we use retrieved body waves to estimate travel time tomography. This noise recovery approach to create valuable sources could be applied for several seismic noise sources and in different contexts improving spatial and temporal resolutions.</span></div>

ASSESSMENT OF TIME ON THE WAY USING ON-BOARD EQUIPMENT OF BUSES

Using urban passenger transport as a data source has several advantages, since it covers most of the urban transport network, and the equipment necessary for data collection has already been installed in rolling stock. Although buses and personal cars move differently, relationships can be developed to estimate travel time using available data. The main hypothesis of the study is that the travel time of nearby routes has a strong correlation, since these directions are subject to similar traffic conditions. The model is tested using real-time travel data

Analysis of Component Errors in the Highway Capacity Manual Travel Time Reliability Estimations for Urban Streets

The Highway Capacity Manual 6th edition (HCM6) includes a new methodology to estimate and predict the distribution of average travel times (TTD) for urban streets. The TTD can then be used to estimate travel time reliability (TTR) metrics. Previous research on a 0.5-mi testbed showed statistically significant differences between the HCM6 estimated TTD and the corresponding empirical TTD. The difference in average travel time was 4 s that, while statistically significant, is not important from a practical perspective. More importantly, the TTD variance was underestimated by 70%. In other words, the HCM6 results reflected a more reliable testbed than field measurement. This paper expands the analysis on a longer testbed. It identifies the sources and magnitude of travel time variability that contribute to the HCM6 error. Understanding the potential sources of error, and their quantitative values, are the first steps in improving the HCM6 model to better reflect actual conditions. Empirical Bluetooth travel times were collected on a 1.16-mi testbed in Lincoln, Nebraska. The HCM6 methodology was used to model the testbed, and the estimated TTD by source of travel time variability was compared statistically to the corresponding empirical TTD. It was found that the HCM6 underestimated the TTD variability on the longer testbed by 67%. The demand component, missing variable(s), or both, which were not explicitly considered in the HCM6, were found to be the main source of the error in the HCM6 TTD. A focus on the demand estimators as the first step in improving the HCM6 TTR model was recommended.

Travel times to hospitals in Australia

Travel time to hospital is a key measure of health service accessibility, and impacts patients’ experiences of care and health outcomes. Methods used to estimate travel time vary across studies. In Australia the smallest geographical areas defined by the Australian Bureau of Statistics for the release of population counts are mesh blocks (MBs) and the smallest geographical areas for the release of health-related statistics are statistical areas level 2 (SA2). SA2s are built up from whole MBs. This project used the Open Source Routing Machine (OSRM) HTTP server to compute estimated travel times between the centroid of each inhabited MB and each hospital in Australia, as well as the shortest travel times between MBs and any hospital. By computing population-weighted averages across MBs, the average travel times to hospitals and the shortest travel time to any hospital were estimated for each SA2. This dataset will promote consistency across studies investigating geographic influences on health care in Australia, and the methods are applicable to generating similar datasets for other countries.

Geospatial mapping of access to timely essential surgery in sub-Saharan Africa

IntroductionDespite an estimated one-third of the global burden of disease being surgical, only limited estimates of accessibility to surgical treatment in sub-Saharan Africa exist and these remain spatially undefined. Geographical metrics of access to major hospitals were estimated based on travel time. Estimates were then used to assess need for surgery at country level.MethodsMajor district and regional hospitals were assumed to have capability to perform bellwether procedures. Geographical locations of hospitals in relation to the population in the 47 sub-Saharan countries were combined with spatial ancillary data on roads, elevation, land use or land cover to estimate travel-time metrics of 30 min, 1 hour and 2 hours. Hospital catchment was defined as population residing in areas less than 2 hours of travel time to the next major hospital. Travel-time metrics were combined with fine-scale population maps to define burden of surgery at hospital catchment level.ResultsOverall, the majority of the population (92.5%) in sub-Saharan Africa reside in areas within 2 hours of a major hospital catchment defined based on spatially defined travel times. The burden of surgery in all-age population was 257.8 million to 294.7 million people and was highest in high-population density countries and lowest in sparsely populated or smaller countries. The estimated burden in children <15 years was 115.3 million to 131.8 million and had similar spatial distribution to the all-age pattern.ConclusionThe study provides an assessment of accessibility and burden of surgical disease in sub-Saharan Africa. Yet given the optimistic assumption of adequare surgical capability of major hospitals, the true burden of surgical disease is expected to be much greater. In-depth health facility assessments are needed to define infrastructure, personnel and medicine supply for delivering timely and safe affordable surgery to further inform the analysis.

Traffic and Transit Travel Time Reliability Indexes and Confidence Intervals

As congestion worsens, the importance of rigorous methodologies to estimate travel time reliability increases. Exploiting fine-granularity transit GPS data, this research proposes a novel method to estimate travel time percentiles and confidence intervals. Novel transit reliability measures based on travel time percentiles are proposed to identify and rank low-performance hot spots; the proposed reliability measures can be utilized to distinguish peak-hour low performance from whole-day low performance. As a case study, the methodology is applied to a bus transit corridor in Portland, Oregon. Time–space speed profiles, heat maps, and visualizations are employed to highlight sections and intersections with high travel time variability and low transit performance. Segment and intersection travel time reliability are contrasted against analytical delay formulas at intersections—with positive results. If bus stop delays are removed, this methodology can also be applied to estimate regular traffic travel time variability.