Arboriculture & Urban Forestry 35(4): July 2009 To evaluate whether the recorded signal and noise values were significantly different (α = 0.05) between “clear” and “tree” con- ditions, a paired t-test was used with each AP as a replicate (n = 7). This test was repeated in winter as well, both on all APs (n = 7) and also only on the APs obscured by the defoliated deciduous trees (n = 5). Where more than one measurement was taken at an AP (i.e., attenuation measured at several distances), the signal mea- surements were averaged, and the averages used in the paired t-test. The study sites were selected to include the most common tree species in the area: all species (except Pinus pinea) are among the ten most common urban trees in the San Francisco Bay area (Laćan and McBride, unpublished). The study was further re- fined to present a variety of tree sizes (small: juvenile Platanus × acerifolia; mid-sized: Liquidambar styraciflua, Pistacia chin- ensis, Prunus cerasifera; large: Liriodendron tulipifera, Pinus pinea, P. radiata, and Sequoia sempervirens). The AP-computer distances selected [20–150 m (65–492 ft)] were those that would be typically encountered by a municipal Wi-Fi user, given the density of APs in Mountain View. The study measured and re- corded the following tree characteristics: leaf type (needle/broa- dleaf), canopy depth (horizontal distance along the line from AP to computer that was obscured by the tree canopy), and the number of trees between the computer and AP. Sixteen leaves on each tree were also sampled, by the taking of four leaves from each cardinal side (N, E, S, W) of the tree, between 1.5 and 5.5 m (5–18 ft), or between 1.5 m (5 ft) and the top of the tree for the small P. × acerifolia trees. The average leaf area (in mm2 ) mm2 = 1.55 in2 205 was estimated by multiplying the two longest axes of the leaf blade (103 ). The study authors also determined the ratio of longest to shortest dimension of each leaf. These two approximations of leaf size and shape allowed the exami- nation of the possible importance of leaf architecture to signal attenuation (previously suggested by Perras and Bouchard 2002). A general linear model (GLM) was used to evaluate the relative contribution of each parameter to describing the observed signal attenuation, noise difference (attenuation), and SNR difference. The attenuation values were used in the GLM rather than the sig- nal and SNR values (which vary with distance from AP), which would have allowed us to eliminate the AP-computer distance from GLM in case multi-colinearity with other variables (specifi- cally, crown depth) had been detected (it was not). GLM was con- structed using a backwards-stepwise procedure (α = 0.05; F-to- enter: 4.00; F-to-remove: 3.90) in SigmaStat 3.1 software package. RESULTS Wi-Fi signal attenuation (loss) was observed when one or more trees were present in the signal path (Table 1, Figures 3-7), rang- ing from < 2 dB in the case of three small, newly planted trees [2 m (6.6 ft) tall Platanus × acerifolia, planted 10 m (33 ft) apart] to almost 19 dB in the case of seven large conifers [> 30 m (98 ft) tall Pinus radiata and Sequoia sempervirens, planted 7–8 m (23–26 ft) apart]. The average attenuation caused by trees (broadleaf and conifer) in-leaf was 5.6 dB, whereas defoliated Figure 2a. “Clear condition,” AP visible (the white box with two aerials, on the horizontal arm next to the lamp; arrow). Figure 2b. “Tree condition,” AP obscured by L. tulipifera (lower part of the light pole visible to the left of the tree trunk). ©2009 International Society of Arboriculture
July 2009
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