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The global COVID-19 pandemic had an unprecedented impact on transportation worldwide. Significant decreases in transportation across all modes were evident and sustained as governments worldwide implemented various countrywide closures and quarantine restrictions to slow the spread of the virus. This paper quantifies and assesses daily vehicle counts by Federal Highway Administration (FHWA) vehicle classifications during the COVID-19 pandemic in New York and Florida throughout 2020. The study found that duringMarch and April of 2020, traffic among all investigated FHWA categories was significantly reduced in both Florida and New York. However, commodity carriers in both states were able to recover faster and remained more consistent than passenger vehicles. This pattern was also observed in both urban and rural communities in Florida. The findings of this work demonstrate how commodity carrier movements, assessed through FHWA vehicle category counts, were less impacted by the governmental restrictions during the pandemic than passenger transportation. While overall traffic volume dropped by more than half in most places at the height of the pandemic, larger commodity-carrying vehicles remained nearly unchanged from the prior year by June of 2020. This was likely because of the critical need to maintain trucking movements to sustain populations. Understanding how truck traffic and freight movements more broadly were impacted during the COVID-19 pandemic is critical in preserving the continuity of service and preventing supply shortages in the event of future outbreaks. [ABSTRACT FROM AUTHOR]

There is a demand for noncontact, high-accuracy, high-spatial-resolution, wireless sensing technologies for various water level and coastal monitoring applications. This paper presents a low-cost, compact, easily configurable interferometry radar for noncontact water level monitoring, including its hardware design, signal processing algorithms, and wireless communication strategies. Interferometry radar measures distance by comparing the phase lag between reflected and transmitted signals. Water level measurements using this approach have been demonstrated in a solitary wave laboratory experiment, a field deployment observing wave run-up near Ponte Vedra, Florida, and a field deployment observing waves and tides in the Sparkill Creek located in Piermont, New York. The experimental results from the radars with millimeter-level accuracy have been compared with reference sensors and demonstrate the potential of continuous wave radar for water level observations. [ABSTRACT FROM AUTHOR]

Criminal justice system fines and fees are a source of revenue for courts, district attorneys, probation departments, and other actors both inside and outside of the justice system. Because these departments rely on fine and fee revenue to partially fund their budgets, they may be incentivized to oppose reforms that would reduce fine and fee collections. Using budget documents from counties and a sample of municipalities in Florida and New York, the authors find that budget reports provide more detailed data on fines and fees than are available from other data sources, including information on which types of fines and fees are collected and how much revenue criminal justice fines and fees provide, both on a per-capita basis and as a share of the total jurisdiction budget. This paper presents a replicable methodology for future research in how to use local government budget documents to evaluate fine and fee collections. A larger, forthcoming study will use this methodology to examine fine and fee collections in five states. [ABSTRACT FROM AUTHOR]

The U.S. electric-power infrastructure urgently needs renovation. Recent major power outages in California, New York, Texas, and Florida have highlighted U.S. electric-power unreliability. The media have discussed the U.S. aging power infrastructure and the Public Utilities Commission has demanded a comprehensive review of the causes of recent power outages. This paper explores geographic information systems (GIS) and a spatially enhanced predictive power-outage model to address: How may spatial analytics enhance our understanding of power outages? To answer this research question, we developed a spatial analysis framework that utilities can use to investigate power-failure events and their causes. Analysis revealed areas of statistically significant power outages due to multiple causes. This study's GIS model can help to advance smart-grid reliability by, for example, elucidating power-failure root causes, defining a data-responsive blackout solution, or implementing a continuous monitoring and management solution. We unveil a novel use of spatial analytics to enhance power-outage understanding. Future work may involve connecting to virtually any type of streaming-data feed and transforming GIS applications into frontline decision applications, showing power-outage incidents as they occur. GIS can be a major resource for electronic-inspection systems to lower the duration of customer outages, improve crew response time, as well as reduce labor and overtime costs. [ABSTRACT FROM AUTHOR]