ARBORICULTURE ARBORICULTU URBAN FORESTRY Volume 34, Issue 6, November 2008 & CONTENTS sin, U.S. David J. Nowak, Daniel E. Crane, Jack C. Stevens, Robert E. Hoehn, Jeffrey T. Walton, and Jerry Bond A Ground-Based Method of Assessing Urban Forest Structure and Ecosystem Services ..............................347 Abstract. To properly manage urban forests, it is essential to have data on this important resource. An efficient means to obtain this informa- tion is to randomly sample urban areas. To help assess the urban forest structure (e.g., number of trees, species composition, tree sizes, health) and several functions (e.g., air pollution removal, carbon storage and sequestration), the Urban Forest Effects (UFORE) model was developed. Data collection variables and model methods are detailed and urban forest structure results are compared among 14 United States cities with average tree density ranging between 22.5 trees/ha (9.1 trees/ac) in Casper, Wyoming, U.S. to 275.8 trees/ha (111.6 trees/ac) in Atlanta, Geor- gia, U.S. Advantages and disadvantages of this ground-based method of assessing urban forest structure, functions, and values are discussed. Key Words. Air Pollution Removal; Carbon Sequestration; Tree Measurement; Urban Forest Monitoring; Urban Forest Sampling. Joe R. McBride A Method for Characterizing Urban Forest Composition and Structure for Landscape Architects and Urban Planners ........................................................................................................ 359 Abstract. A method combining numeric data collection with the preparation of street tree cross-sections and plans, based on surveys of 33 urban forests around the world, is reviewed. The combination can provide design professionals with graphic information on urban forest structure not collected by more traditional methods for urban forest inventories. Key Words. Composition; Planting Space; Species Frequency; Street Cross-Section; Street Plan; Structure; Tree Spacing. Formerly the Journal of Arboriculture, 1975 – 2005 (Volumes 1 – 31) www.isa-arbor.com Jeffrey T. Walton, David J. Nowak, and Eric J. Greenfield Assessing Urban Forest Canopy Cover Using Airborne or Satellite Imagery ..................................................334 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. Anne Buckelew Cumming, Daniel B. Twardus, and David J. Nowak Urban Forest Health Monitoring: Large-Scale Assessments in the United States ..........................................341 Abstract. The U.S. Department of Agriculture, Forest Service (USFS), together with state partners, developed methods to monitor urban forest structure, function, and health at a large statewide scale. Pilot studies have been established in five states using protocols based on USFS Forest Inventory and Analysis and Forest Health Monitoring program data collection standards. Variables and data analysis are described. Advantages of a large-scale monitoring study are discussed and examples of results from Wisconsin are presented. Studies in Indiana, Wisconsin, New Jersey, Tennes- see, and Colorado, U.S., have shown that urban forest health monitoring data collection and analysis is feasible and can be implemented nationally. Key Words. Forest Health Monitoring; Forest Inventory andAnalysis (FIA); Urban Forest Effects Model (UFORE); Urban Forestry, Wiscon- ©2008 | International Society of Arboriculture | ISSN:1935-5297
November 2008
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