An iPhone 6 using the Avenza software for capturing horizontal positions was employed to understand relative positional accuracy in an urban environment, during two seasons of the year, two times of day, and two perceived WiFi usage periods. On average, time of year did not seem to influence the average error observed in horizontal positions when GPS-only (no WiFi) capability was enabled, nor when WiFi was enabled. Observations of average horizontal position error only seemed to improve with time of day (afternoon) during the leaf-off season. During each season and during each time of day, horizontal position error seemed to improve in general during perceived high WiFi usage periods (when more people were present). Overall average horizontal position accuracy of the iPhone 6 (7–13 m) is consistent with the general accuracy levels observed of recreation-grade GPS receivers in potential high multi-path environments.

Key components of a digital forestry program (digital tools, databases, and decision-support systems) can be of great importance in the management of forests today. A general lack of knowledge of the needs of forest managers and landowners for components of digital forestry has been hypothesized. A survey regarding digital forestry tools was conducted of registered foresters from five USA states (Alabama, Michigan, Mississippi, New Jersey, and North Carolina). Registered foresters may be private landowners or those working for organizations that meet the requirements for licensure in a state. Of the registered foresters who identified as nonindustrial private landowners, roughly half currently do not use digital technologies for forest management efforts. Of the registered foresters who identified as employees of forestry organizations, about 80% use digital technology in the management of their organization’s forests. Geographic information systems technology was the most important, followed by inventory systems, databases, and field-ready smartphone applications. Those registered foresters who had not used digital technologies in the past suggested that their usefulness for the management of their property and their lack of awareness of potential options were likely reasons for not using digital technologies.Study Implications: From surveying five eastern states in the United States, we found that forest landowners are not current users of technology, whereas those associated with forest organizations are more apt to use technologies when managing their forests. Desirable technologies used by both private landowners and forestry organizations include geographic information systems and smartphone applications, whereas those working for forestry organizations also desired inventory systems and databases. Current technology gaps were also identified.

Fire is an essential ecological process and management tool for many forested landscapes, particularly the pine (Pinus spp.) forests of the southern USA. Within the Talladega National Forest in Alabama, where restoration and maintenance of pine ecosystems is a priority, fire frequency (both wild and prescribed) was assessed using a geographical process applied to a fire history database. Two methods for assessing fire frequency were employed: (1) a simple method that utilised the entire range of years acknowledged in the database and (2) a conservative method that was applied only the date of the first and last fires recorded at each location. Analyses were further separated by (a) method of mean fire return interval calculation (weighted by area or Weibull) and (b) fire season interval with analyses conducted on growing season and dormant season fires. Analyses of fire frequency for national forest planning purposes may help determine whether a prescribed fire program mimics ecological and historical fire frequencies and meets intended objectives. The estimated fire return interval was between ~5 and 6.5 years using common, straightforward (simple) methods. About one-third of the forest receives no fire management and about half of the balance has sufficiently managed fuels.

Using imagery available through Google Earth Pro and a point sampling methodology, changes in land cover for three U.S. cities were assessed, beginning during the Great Recession (2007) and extending through to 2018. The cities were Buffalo (New York), Denver (Colorado), and San Diego (California), and 11 land cover classes were used to characterize each. The novel contributions of this work, and the innovative contributions to science include an analysis of urban land cover change in the years since the Great Recession, and the use of point pattern analysis on sample points that changed from non-developed in 2007 to developed in 2018, to determine whether a spatial pattern of land cover class change was evident. An initial assumption was made that forest cover change in these three cities would be minimal since the Great Recession. In fact, forest cover decreased by less than 1% in all three cities with the greatest decrease in Buffalo. Over the post-recession study period, increases in the developed land classes were evident in all three cities at the expense of grasses, tree cover, and other land classes. Some clustering of new development activities was noticed at a relatively small scale in San Diego, while some dispersion of new developed activities was noticed at a larger scale in Denver. Among other factors, changes in population, economics, and land use are factors that influence land cover change with specific impacts on forest cover, and therefore in the provision of urban forest benefits to the environment and society.

The recreational opportunities available across landscapes of the Southern United States can be broad and diverse, and collectively are considered a subset of cultural ecosystem services. In describing the settings of recreational opportunities, a number of methods have been proposed that are based in part on geographic information and that can be facilitated by geographical analyses. Presented here are two expedient and cost-effective methods for assessing the recreation supply potential of large, heavily-roaded areas that are situated mainly with privately-owned land in the Southern United States. One land classification process uses fine-scale aerial imagery and other geospatial data in a process that results in three recreational opportunity setting zones with a focus on motorised sightseeing: foreground, background, and remote areas. Within these zones, land cover was derived and aggregated into three major land cover classes, including forest, agriculture, and bare ground classes. Further, a second process uses fuzzy classification methods, and through this highly suitable recreation settings were identified. Each recreational opportunity zone is further subdivided by public- and privately-owned land. We feel these types of recreation setting models can allow managers and planners to gain an understanding of the passive recreation potential of heavily-roaded privately-owned landscapes typical of the Southern United States.