Arboriculture & Urban Forestry 43(2): March 2017 ery for this purpose is consistent with a rapidly growing number of studies, including Jiang et al. (2015). The qualitative methods consisted of guided interviews with residential develop- ers and real estate agents. Researchers sought to understand home buyer behavior as observed by real estate agents, and also regional home mar- kets, as observed by residential developers. These professionals tend to know what types of hous- ing sells, as buyer behavior and market strengths are both indicators of home buyer preferences. This approach allowed for the develop- ment of a nuanced and comprehensive under- standing of the economic value that may accrue as a result of tree preservation, as well as challenges to implementing tree pres- ervation in the home development market. Methods Researchers determined a multi-county case study was appropriate for understanding the combination of research questions (providing a large enough real estate market and a variety of landscape/ land cover settings). The Cleveland region was chosen for the study to provide greater access to land development and real estate profession- als for qualitative methods selected for the study. Five counties in the Cleveland-Elyria-Mentor Metropolitan Statistical Area (MSA), plus Sum- mit County (part of the Akron MSA), were used in the study. The conceptual model for the study research design is presented in Figure 2, a conceptual but not a chronological depiction. The objective for the quantitative data was to identify data acquisition methods using digitized and web-based technology that could provide information without relying on data from local governments, given the weak planning require- ments in the state. Qualitative data from the real estate and development sectors provided infor- Table 1. Tree canopy of new home sales by county, 2009–2011. Sale (canopied?) Percent of Cuyahoga Geauga Lake Lorain Medina Summit Total sales No 300 0 273 680 276 267 1,796 Yes 289 17 152 491 151 188 1,288 sales canopied 49% 100% 36% 42% 35% 41% 42% 59 mation on their professional experiences on how the market values preserved trees. The inter- views were conducted in parallel, chronologically, with the initial modeling and mapping effort— particularly Model A, the base model. During rou- tine meetings and discussions of the entire team (working on both the quantitative and qualita- tive portions of the study), other formulations of the regression model were suggested, partly from regular feedback on preliminary findings, and partly as a result of the qualitative findings that were beginning to take shape. Models B and C, and the efforts detailed under “Additional Regres- sion Explorations,” came out of those discussions. Quantitative analysis Three hedonic models were specified to answer research question #1. The database for the mod- eling consisted of sales and property characteris- tics files from county administrative databases, reconciled across different counties, which were then filtered to include only single family and condominium sales, only the first sale aſter the house was built, and only sales to individual buyers (as compared to other developers, LLCs, etc.). Aſter this data cleaning, nearly 3,100 resi- dential units were identified for analysis during the 2009–2011 study period. The right-most col- umn of Table 1 presents new construction home sales by county in the study area. Figure 1 pres- ents the housing sale locations in the six counties. In terms of quantitative data considerations, issues of tree canopy, dominance, and location were considered. For the parcels with new con- struction home sales during the study period, researchers sought to know the influence of preserved trees on the sale price. This is dif- ferentiated from the value attributed to land- scaping that was added to the parcel during the site construction process. The identifica- Average canopy (ſt2 2,057 23,365 1,804 790 1,078 718 1,325 ) Average canopy (percent coverage) 8.1 35.9 7.4 5.4 4.1 5.6 6.2 Total sales 589 17 425 1,171 427 455 3,084 ©2017 International Society of Arboriculture
March 2017
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