334 Walton et al.: Assessing Urban Forest Canopy Cover Arboriculture & Urban Forestry 2008. 34(6):334–340. Assessing Urban Forest Canopy Cover Using Airborne or Satellite Imagery Jeffrey T. Walton, David J. Nowak, and Eric J. Greenfield Abstract. With the availability of many sources of imagery and various digital classification techniques, assessing urban forest canopy cover is readily accessible to most urban forest managers. Understanding the capability and limitations of various types of imagery and classification methods is essential to interpreting canopy cover values. An overview of several remote sensing techniques used to assess urban forest canopy cover is presented. A case study comparing canopy cover percentages for Syracuse, New York, U.S. interprets the multiple values developed using different methods. Most methods produce relatively similar results, but the estimate based on the National Land Cover Database is much lower. Key Words. Remote sensing; urban tree canopy. Urban Forest Canopy Cover Urban forest canopy cover, the area covered by tree and shrub canopies in an urbanized or developed region, is a fundamental measure of urban forest structure (Nowak 1994). The structure of the urban forest determines its ecologic functioning (Zipperer et al. 1997), including the many benefits the urban forest provides (Dwyer et al. 1992; Nowak and Dwyer 2007) as well as influ- encing actions needed to manage the forest. Benefits directly related to the amount of urban forest canopy cover include air pollutant removal, stormwater runoff reduction, and building en- ergy conservation. Urban tree management actions are also re- lated to the quantity of biomass, and therefore canopy cover, in a particular area. Specifically, urban forest canopy cover is the two-dimen- sional, orthogonal projection of tree and shrub canopies onto the plane of the ground surface. For a given area, urban forest canopy cover has two important properties: quantity and spatial distribution. The quantity is represented as a proportion or per- centage of the area covered by tree and shrub canopies when viewed from directly above. It can be used to compare regions in terms of their forest cover and track an area’s urban forest change over time. As Poracsky and Lackner (2004) note, canopy cover is also easily understood by the general public and is therefore a useful tool for communicating urban forestry issues. Spatial distribution is best displayed as a map and shows the location of tree cover in the area of interest. While the spatial distribution of urban forest canopy cover is exclusively deter- mined by aerial or satellite-based remote-sensing techniques, the quantity can also be estimated through the use of field plots or dot grid photograph interpretation. Urban forest canopy cover does not directly provide information about the species compo- sition, number of trees, or health of the urban forest, but these quantities can be inferred through the combined use of ground- based sampling. Measuring Urban Forest Canopy Cover Via Remote Sensing Urban forest canopy has been quantified using aerial photograph interpretation techniques (Rowntree 1984; Nowak et al. 1996) ©2008 International Society of Arboriculture and classification of high-resolution digital imagery (Myeong et al. 2001; Zhang 2001; Irani and Galvin 2002), medium- resolution satellite imagery (Wang 1988; Iverson and Cook 2000; Huang et al. 2001), and low-resolution satellite imagery (Zhu 1994; Dwyer et al. 2000). Each technique and imagery format provides certain advantages and possibly disadvantages for the assessment of urban forest canopy cover. Aerial Photograph Interpretation Interpretation of aerial photographs at randomly placed locations in a study area has been used to determine the quantity of urban forest cover (Rowntree 1984; Nowak et al. 1996). The presence or absence of tree canopy cover at the specific point position is tallied for each of the sample points, and the proportion of sample points that fell on the tree canopy statistically represents the amount of urban forest canopy cover in the study area. A standard error of the sampling can also be computed to yield a bound on the canopy percent estimate. With the wide availability of digital orthophotographs and geographic information systems in many municipalities, aerial photograph interpretation is very simple to implement. It yields very good results for quantity, but provides limited information on the spatial distribution of the forest cover. Aerial photograph interpretation requires little technical remote-sensing knowledge beyond the ability to inter- pret tree canopies. Tools to aid in digital aerial photograph in- terpretation are available at www.fs.fed.us/ne/syracuse/Tools/ tools.htm. Several properties of the aerial imagery itself can influence the ease of interpretation and quality of results. Imagery acquired during the leaf-on season for trees will be more straightforward to interpret than leaf-off imagery. Leaf-off imagery may still be used for photograph interpretation, but more interpretation skill and time is required to infer canopy from the visible branch structure and/or shadows of the stem and branches on the ground surface. Resolution for digital images, or scale for traditional print photographs, should be such that individual trees can clearly be discerned. For digital imagery, this resolution would generally be approximately 1 m (3.3 ft) or smaller. The draw- back of very high-resolution imagery is that the digital files will
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