Arboriculture & Urban Forestry 35(2): March 2009 storm damage and debris costs is available as the Storm Dam- age Assessment Protocol, a component of the i-Tree program (www.iTreeTools.org). However, this protocol does not spe- cifically account for hurricane damage profile and management. Urban forests in Florida encompass a wide variety of spe- cies, urban morphologies, and land cover types. Any protocol that is developed must be applicable over this range of vari- ability. Most studies on hurricane effects on urban and natural forest are based on single tree, plot or landscape-scale based assessments (Duryea et al. 2007a, Duryea et al. 2007b; Fran- cis and Gillespie 1991; Kupfer et al. 2008; Oswalt and Oswalt 2008). Many debris assessments use empirical studies such as these as inputs for broad-based, often single-parameter mod- els and approaches for quantifying debris (FEMA, 2007a). This study takes a different approach, and uses on-ground data reported from hurricane impacted communities to as- sess and characterize debris and damage at the urban and community forest level. Its objectives are to assess, compile, and analyze urban forest debris and tree damage data from the 2004 and 2005 hurricane seasons in Florida. These esti- mates can then be used to develop a hurricane debris assess- ment protocol that estimates potential damage before a storm and report tree debris and damage after a hurricane in Florida. MATERIALS AND METHODS Debris and Tree Damage Data Collection We examined recent hurricanes making landfall in Florida: Charley, Francis, Ivan, and Jeanne in 2004; and Dennis, Katrina, and Wilma in 2005. An initial sample of hurricane-affected coastal and inland communities was used to determine the utility of FEMA Project Worksheets (PWs) for quantifying tree debris, damage, and costs. Project Worksheets are compiled by each community request- ing public, monetary assistance for hurricane damage, and con- stitute a dynamic record of information and data needed for justi- fication for reimbursement in an emergency management project (FEMA, 2007c). Project Worksheets are categorized by the type of hurricane damage. We sampled Category A, the debris damage category, which contains relevant debris data as well as hazard tree pruning and removal reimbursement; and Category G, which is a general category that often contains debris data. Project Worksheets were obtained from the Florida Division of Emergency Manage- ment. The initial sample of PWs from 15 communities from the 2004 and 2005 hurricane seasons in Florida provided enough data to justify their use in obtaining debris quantity and cleanup costs. A list of Florida communities impacted by each of the sev- en hurricanes during 2004 and 2005 with PW applications in Category A was compiled and each community was then as- signed a unique number. Using the unique number and a ran- dom number generator, a 10% sample of communities impacted as depicted in maps (FEMA, 2004) by each hurricane was then selected for use in this study. Entities other than communities (e.g., counties, tribes, official departments, hospitals) were ex- cluded from the sample. Stump removal, for which insufficient data were available, was also excluded from the data collection. Data for debris amounts and reported costs were taken directly from the PWs. Individual cost line items were not specifically listed by many communities. In addition to removal and reduc- tion of debris, individual costs might have included debris moni- toring, site preparation, tipping fees, equipment or other costs 101 that were directly related to debris elimination. Debris quantity and costs were commonly reported in several different PWs for a hurricane by a single community. Therefore, data from all PWs for a single hurricane event were summarized along with com- munity specific data as presented in Table 1. Data on both tree removals and hazard prunings were less consistently reported in PWs. Data was obtained by direct request from the communities. Table 1. Data collected for each hurricane and community. Data Source Public street miles % developed urban land % tree cover Tree density (per hectare) Sustained wind speed (knots) Debris and costs Tree removal and pruning costs Tree removal and pruning totals Total vegetation debris (m3 Total cost for debris disposal Community center (UTM) ; yd3 ) TIGER/Line files (US Census Bureau 2004) USDA Forest Service (Nowak et al. 2008) USDA Forest Service (Nowak et al. 2008) University of Florida (Escobedo et al. 2008) National Oceanic and Atmospheric Administration (NOAA, 2004) Project Worksheets Project Worksheets, Community contact Project Worksheets, Community contact Project Worksheets Project Worksheets Google Earth (Google Earth, 2007) UTM = Universal Transverse Mercator Hurricane debris amounts and costs, urban forest tree den- sity and cover data, street mileage, and percent of urban de- veloped land were derived from a number of sources (Table 1). Maximum sustained wind speed data for each community were obtained from tabular data (NOAA, 2004), and report- ed for selected communities by the National Hurricane Cen- ter. Where wind speed data were not available for a sample community, wind speeds were assigned to sample communi- ties based on nearest community with a recorded wind speed. Debris data were converted to a total cost per cubed meter by summing all reported debris volume disposed and its asso- ciated costs from PWs. Estimates of debris generation per unit street segment length were made with i-Tree’s “Sample Street Segment Generator” using ArcGIS 9.1 and street mileage ob- tained from U. S. Census Bureau’s TIGER/Line data (U.S. Census Bureau, 2004), in an ESRI shapefile (i-Tree 2008). Relationships between tree cover, density, and debris amounts collected from Street Rights-of-Way were investigated using Re- newable Natural Resources Planning Act (RPA) assessment urban forest cover data tabulated by Census Designated Place (Nowak et al. 2008). These data are based on 30 m resolution Landsat TM and ETM imagery that is part of the 2001 National Land Cover Database. RPA data included percent tree canopy and developed urban land for each sampled community (Table 1). Percent can- opy was converted to community-specific tree density using rep- resentative mean tree density factors from similar geographic and physiographic communities (Escobedo et al. 2008). Communities in north Florida were assigned Pensacola’s tree density of 315 trees/ha (127 trees/ac), Tampa Bay’s tree density of 257 trees/ha (104 trees/ac) was used for the central Florida gulf coast, Miami- Dade Counties’ 83 trees/ha (34 trees/ac) for south Florida and lower Atlantic coast, and Gainesville’s 242 trees/ha (98 trees/ac) were used for communities in central Florida’s non-coastal areas. The distribution of cubic meters of debris per linear street segment data was determined to be significantly different from ©2009 International Society of Arboriculture
March 2009
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