100 Nielsen et al.: Review of Urban Tree Inventory Methods Used to Collect Data at Single-Tree Level Over the years, the number of different aspects aſter 2001. However, studies addressing transmis- sion of volatile organic compounds (VOCs) by urban trees were an exception from the temporal pattern in studies on the environmental aspects of urban trees. The growing number of publi- cations from 2008 onwards is largely due to an increase in the number of methodological stud- ies focusing on ‘test of examined in studies increased steadily, to a total of 14 (Table 1). Nearly all studies focusing on the economic benefits of urban trees (grouped under ‘Cost-benefit analysis’) and environmental aspects (grouped under ‘Biodiversity’, ‘Canopy cover’, and ‘Climate/greenhouse/CO2 storage’) were published tree inventory methods’ and ‘digitalization of tree shape’, and is also due to the emergence of studies in which urban tree inventory data on single-tree level are applied to assess ‘Biodiversity aspects’ (n = 3) (Table 1). Typology of Urban Tree Inventory Methods Four types of inventories for data collection at single-tree level with distinct characteristics were distinguished: 1) Satellite-supported methods, 2) airplane-supported methods, 3) on-the-ground scanning or digital photography, and 4) field surveys with direct manual measurements and/or visual inspection. As shown in Table 2, each of these types is supported by different means of technical aid. Satellite-supported methods can collect infor- mation from very large areas (Cook and Iverson 1991; Small and Lu 2006). Very High Resolution (VHR) images, as well as Panchromatic and mul- tispectral images taken by equipment on satel- lites (e.g., the QuickBird satellite), can be used to extract information on urban trees. Satellite- supported infrared (IR) scanning images of the wavelengths reflected by vegetation can also be used to collect information at single-tree level (e.g., Jansen et al. 2006). Satellite-supported data collection at single-tree level was used in two of the studies included in the review (Ardila et al. 2012; Cavayas et al. 2012) and to identify trees for subsequent field surveys in two other studies (Thaiutsa et al. 2008; Ningal et al. 2010) (Table 2). Airplane-supported methods also enable data collection over large areas (Ryherd and Woodcock 1990; Mausel et al. 1992). Like satellites, airplanes can ©2014 International Society of Arboriculture be equipped with appropriate devices, such as an IR scanner or different types of cameras (Goldberg 1981; Mausel et al. 1992; Andarz et al. 2009). However, only two of the studies reviewed adopted these methods (Miller and Winer 1984; Jutras et al. 2009) (Table 2). Compared with the aerial methods, data collection and processing from on-the-ground digital scanning (Patterson et al. 2011) or photog- raphy (Abd-Elrahman et al. 2010) are restricted to rather small areas because each scanning/ photography image is restricted to a single tree or a small group of trees. Although this technology is developing rapidly, it is still time-consuming. Of the 57 studies included in the review, five had applied methods in this typology (Abd-Elrahman et al. 2010; Park et al. 2010; Patterson et al. 2011; Rutzinger et al. 2011; West et al. 2012) (Table 2). Field survey methods comprise direct mea- surements and/or visual inspection of individual trees by field staff (Adkins et al. 1997; Martin et al. 2011; Östberg et al. 2012). Although field sur- veys are labor-intensive and time-consuming, 46 of the 57 papers reviewed applied this method to collect their data, making it the most com- mon of the four types. In the search for papers, a subtype of field survey was identified where the data collection is limited to visual inspec- tion of appearance and damage (to inform assessment of hazard status) from a car driven at low speeds. This method has been called windshield survey (Bassett 1976; Rooney et al. 2005) or drive-by survey (Pokorny 2003). How- ever, this subtype was not applied in any of the articles meeting the inclusion criteria (Table 2). Relationship Analysis Analysis of the relationship between study focus, inventory method, and parameters collected from each tree showed that data on the three parame- ters, crown size/density, tree size (other than crown size and DBH), and species information had been collected by studies falling into 12 different study focus classes, while the corresponding number for DBH was 11. Data on the remaining param- eter groups, especially tree age information and tree coordinates, were collected by studies with fewer focus classes (two studies each) (Table 3). Turning the perspective to the study focus, studies testing urban tree inventory methods,
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