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The ability to interpret graphs is foundational to understanding many science topics, although mastering this skill can prove challenging to many students. This article illustrates how a lesson on motion graphs was implemented in physical science classes using modern smartphone LiDAR technology. It also presents the differences in accessibility and student motivation that resulted from instruction with the novel technology as compared with commercially available sonic rangers. With the help of a free, publicly-available, gamified app, students used their walking movements to match motion graphs of increasing difficulty. Students demonstrated shifts in their intuition for making graphs and showed significant gains on a pre-post assessment. Teachers observed increased enthusiasm for learning about graphs with mobile devices. 

Environmental hazards vary locally and even street to street resulting in microspatial inequities, necessitating climate resilience solutions that respond to specific hyperlocal conditions. This study uses remote sensing data to estimate two environmental hazards that are particularly relevant to community health: land surface temperature (LST; from LandSat) and air pollution (AP; from motor vehicle volume via cell phone records). These data are analyzed in conjunction with land use records in Boston, MA to test (1) the extent to which each hazard concentrates on specific streets within neighborhoods, (2) the infrastructural elements that drive variation in the hazards, and (3) how strongly hazards overlap in space. Though these data rely on proxies, they provide preliminary evidence. Substantial variations in LST and AP existed between streets in the same neighborhood (40% and 70–80% of variance, respectively). The former were driven by canopy, impervious surfaces, and albedo. The latter were associated with main streets and zoning with tall buildings. The correlation between LST and AP was moderate across census tracts (r = 0.4) but modest across streets within census tracts (r = 0.16). The combination of results confirms not only the presence of microspatial inequities for both hazards but also their limited coincidence, indicating that some streets suffer from both hazards, some from neither, and others from only one. There is a need for more precise, temporally-dynamic data tracking environmental hazards (e.g., from environmental sensor networks) and strategies for translating them into community-based solutions. 

Abstract Certain places generate inordinate amounts of crime and disorder. We examine how places differ in their nature of crime and disorder, with three objectives: (1) identifying a typology of profiles of crime and disorder; (2) assessing whether different forms of crime and disorder co-locate at parcels; and (3) determining whether problematic parcels explain crime and disorder across neighborhoods. The study uses 911 and 311 records to quantify physical and social disorder and violent crime at residential parcels in Boston, MA (n = 81,673). K-means cluster analyses identified the typology of problematic parcels and how those types were distributed across census block groups. Cluster analysis identified five types of problematic parcels, four specializing in one form of crime or disorder and one that combined all issues. The second cluster analysis found that the distribution of problematic parcels described the spectrum from low- to high-crime neighborhoods, plus commercial districts with many parcels with public physical disorder. Problematic parcels modestly explained levels of crime across neighborhoods. The results suggest a need for diverse intervention strategies to support different types of problematic parcels; and that neighborhood dynamics pertaining to crime are greater than problematic properties alone. 

Objectives Scholars and practitioners have paid increasing attention to problematic properties, but little is known about how they emerge and evolve. We examine four phenomena suggested by life-course theory that reflect stability and change in crime and disorder at properties: onset of issues; persistence of issues; aggravation to more serious types of issues; and desistance of issues. We sought to identify the frequency and dynamics of each. Methods We analyze how residential parcels (similar to properties) in Boston, MA shifted between profiles of crime and disorder from 2011 to 2018. 911 dispatches and 311 requests provided six measures of physical disorder, social disorder, and violence for all parcels. K-means clustering placed each parcel into one of six profiles of crime and disorder for each year. Markov chains quantified how properties moved between profiles year-to-year. Results Onset was relatively infrequent and more often manifested as disorder than violence. Pathways of aggravation led from less serious profiles to a mixture of violence and disorder. Desistance was more likely to occur as de-escalations along these pathways then complete cessation of issues. In neighborhoods with above-average crime, persistence was more prevalent whereas desistance less often culminated in cessation, even relative to local expectations. Conclusions The results offer insights for further research and practice attentive to trends of crime and disorder at problematic properties. It especially speaks to the understanding of stability and change; the role of different types of disorder; and the toolkit needed for problem properties interventions. 

Objectives. To examine the relationships among environmental characteristics, temperature, and health outcomes during heat advisories at the geographic scale of street segments. Methods. We combined multiple data sets from Boston, Massachusetts, including remotely sensed measures of temperature and associated environmental characteristics (e.g., canopy cover), 911 dispatches for medical emergencies, daily weather conditions, and demographic and physical context from the American Community Survey and City of Boston Property Assessments. We used multilevel models to analyze the distribution of land surface temperature and elevated vulnerability during heat advisories across streets and neighborhoods. Results. A substantial proportion of variation in land surface temperature existed between streets within census tracts (38%), explained by canopy, impervious surface, and albedo. Streets with higher land surface temperature had a greater likelihood of medical emergencies during heat advisories relative to the frequency of medical emergencies during non–heat advisory periods. There was no independent effect of the average land surface temperature of the census tract. Conclusions. The relationships among environmental characteristics, temperature, and health outcomes operate at the spatial scale of the street segment, calling for more geographically precise analysis and intervention.