Awareness of tree risk assessment and management has risen in the United States in recent years. This has been prompted by publications such as the American National Standards Institute (ANSI) standard for tree risk assessment (ANSI A300 Part 9 – Tree Risk Assessment) and the accompanying International Society of Arboriculture (ISA) Tree Risk Assessment Best Management Practices, as well as the subsequent development of the ISA Tree Risk Assessment Qualification. How this increase in awareness has broadly translated into common practice in communities, is not well understood. This paper reports findings from a recent survey of urban forest operations as they directly pertain to tree risk assessment. The survey consisted of a 109-question long-form questionnaire that was sent to 1727 communities, followed up by a truncated version to non-responding communities. Six hundred and sixty-seven (38.6%) communities responded to the survey – 513 to the full survey and 154 to the truncated version. Communities that reported having a certified arborist on staff (p-value = .010), a strategic plan (p-value = .002), an updated inventory (p-value < .001), collecting risk data (p-value = .004), and having a past claim for damage or injury (p-value < .001) were more likely to regularly conduct tree risk management activities.

Background and Objectives: The structural diversity of an urban forest affects ecosystem service provision, and can inform management, planning, as well as policy. Trunk diameter at breast height (DBH) is amongst the most common measures of tree structure due to its ease of measurement and strong relationships with other structural and non-structural urban forest characteristics. Materials and Methods: In this study, the DBH distributions of urban forests are summarised for 38 American cities with a combined population of over 30 million people and a range of geographic, climatic, and demographic conditions. The Anderson–Darling (AD) test was used to test the hypothesis that all DBH distributions came from a common population. Moreover, structural diversity was compared using the Shannon–Wiener index. Results: The AD test results failed to identify any statistically significant differences in DBH distributions. However, qualitatively, the DBH distributions have two primary forms, which have important functional, management, and planning implications. The vast majority of cities have an exponentially inverse-proportional distribution, such that the proportion of trees in each successively larger DBH class decreases exponentially. The Shannon–Wiener index indicates an uneven DBH distribution in the cities with an exponentially inverse-proportional diameter distribution; these cities are dominated by trees in the smallest diameter class. Potential explanations for a large proportion of trees in the smallest diameter classes include a large number of small, naturally regenerating trees; a preference for smaller trees in urban areas; or a recent increase in tree planting efforts. Conclusions: Despite no statistical differences in DBH distributions for the 38 study cities, the functional, management, and planning implications will differ considerably.

Urban forests are often heavily populated by street trees along right-of-ways (ROW), and monitoring efforts can enhance municipal tree management. Terrestrial photogrammetric techniques have been used to measure tree biometry, but have typically used images from various angles around individual trees or forest plots to capture the entire stem while also utilizing local coordinate systems (i.e., non-georeferenced data). We proposed the mobile collection of georeferenced imagery along 100 m sections of urban roadway to create photogrammetric point cloud datasets suitable for measuring stem diameters and attaining positional x and y coordinates of street trees. In a comparison between stationary and mobile photogrammetry, diameter measurements of urban street trees (N = 88) showed a slightly lower error (RMSE = 8.02%) relative to non-mobile stem measurements (RMSE = 10.37%). Tree Y-coordinates throughout urban sites for mobile photogrammetric data showed a lower standard deviation of 1.70 m relative to 2.38 m for a handheld GPS, which was similar for X-coordinates where photogrammetry and handheld GPS coordinates showed standard deviations of 1.59 m and the handheld GPS 2.36 m, respectively—suggesting higher precision for the mobile photogrammetric models. The mobile photogrammetric system used in this study to create georeferenced models for measuring stem diameters and mapping tree positions can also be potentially expanded for more wide-scale applications related to tree inventory and monitoring of roadside infrastructure.