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Hardin and Jensen (2011) presented six challenges to using small Unmanned Aerial Systems (sUAS) for environmental remote sensing: challenge of the hostile flying environment, challenge of power, challenge of available sensors, challenge of payload weight, challenge of data analysis, and challenge of regulation. Eight years later we revisit each of the challenges in the context of the current sUAS environment. We conclude that technological advances made in the interim (as applied to environmental remote sensing) have either (1) improved practitioner ability to respond to a challenge or (2) decreased the magnitude of the challenge itself. However, relatively short flight time remains a primary challenge to using sUAS in environmental remote sensing.

Background: Suicides by any method, plus 'nonsuicide' fatalities from drug self-intoxication (estimated from selected forensically undetermined and 'accidental' deaths), together represent self-injury mortality (SIM)fatalities due to mental disorders or distress. SIM is especially important to examine given frequent undercounting of suicides amongst drug overdose deaths. We report suicide and SIM trends in the United States of America (US) during 1999À2018, portray interstate rate trends, and examine spatiotemporal (spacetime) diffusion or spread of the drug self-intoxication component of SIM, with attention to potential for differential suicide misclassification. Methods: For this state-based, cross-sectional, panel time series, we used de-identified manner and underlying cause-of-death data for the 50 states and District of Columbia (DC) from CDC's Wide-ranging Online Data for Epidemiologic Research. Procedures comprised joinpoint regression to describe national trends; Spearman's rank-order correlation coefficient to assess interstate SIM and suicide rate congruence; and spacetime hierarchical modelling of the 'nonsuicide' SIM component. Findings: The national annual average percentage change over the observation period in the SIM rate was 4.3% (95% CI: 3.3%, 5.4%; p<0.001) versus 1.8% (95% CI: 1.6%, 2.0%; p<0.001) for the suicide rate.

Heat-related death is considered the number one weather-related cause of mortality throughout the world. There is growing concern that, heat waves, the primary meteorological phenomena responsible, will become more intense and numerous in the near future. Provided with this growing hazard the responsibility for mitigation, early detection and warning rests with emergency response agencies as well as academic researchers. Numerous tools exist in the present time to model very complex relationships that truly define vulnerability to such impending disasters. However, compared to other disasters (i.e. flooding, hurricanes, tornadoes, earthquakes, etc.) heatrelated effects have not been thoroughly investigated in a geospatial framework. It seems likely that such approaches will provide significant benefit to the vulnerable communities and to policy makers responsible for planning. These approaches involve the usage of multiple sensor data (multi-sensor data fusion) coupled with socioeconomic characteristics to truly capture the fabric of social vulnerability. Evidence is growing that these approaches are beginning to have an impact in forecasting and planning for heat-related health disasters.

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Bikeshare programs are a popular, convenient, and sustainable mode of transportation that provide a range of benefits to urban communities such as reduction in carbon emissions, decreased travel times, financial savings, and heightened physical activity. Although, tourists are especially inclined to use bikeshare to explore a destination as the programs are a convenient, cheap, flexible, and an active alternative to vehicles and mass transit little research or attention has focused on visitor usage. As such the current study investigated the spatial-temporal usage patterns of bikeshare by visitors to an urban community using GPS based big data (N ¼ 353,733). The results revealed differential usage patterns between visitors and local residents based on user provided ZIP Codes using a 50 mile geometric circular buffer around the urban destination. The visitors and residents significantly varied on numerous trip behaviors including route selection, time of rental, checkout/check-in locations, distance, speed, duration, and physical activity intensity. The user patterns uncovered suggest visitors primarily use bikeshare for leisure based urban exploration, compared to residents' primary use of bikeshare to be public transportation related. Implications for bikeshare, urban planning, and tourism management are provided aimed at delivering a more sustainable and richer visitor experience.

IMPORTANCE Self-injury mortality (SIM) combines suicides and the preponderance of drug misuserelated overdose fatalities. Identifying social and environmental factors associated with SIM and suicide may inform etiologic understanding and intervention design. OBJECTIVE To identify factors associated with interstate SIM and suicide rate variation and to assess potential for differential suicide misclassification.

Mortality from extreme heat is a leading cause of weather-related fatality, which is expected to increase in frequency with future climate scenarios. This study examines the spatiotemporal variations in heat-related health risk in three Midwestern cities in the United States between the years 1990 to 2010; cities include Chicago, Illinois, Indianapolis, IN, and Dayton, OH. In order to examine these variations we utilize the recently developed Extreme Heat Vulnerability Index (EHVI) that uses a principal components solution to vulnerability. The EHVI incorporates data from the U.S. Decadal Census and remotely sensed variables to determine heat-related vulnerability at an intra-urban level (census block group). The results demonstrate significant spatiotemporal variations in heat-health risk within the cities involved.