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Table 2 Land use features for street segments

From: Virtual audits of the urban streetscape: comparing the inter-rater reliability of GigaPan® to Google Street View

Features

N

PR

PA

Cohen’s kappa

PABAK

GP

GSV

GP (%)

GSV (%)

GP

95% CI

GSV

95% CI

GP

95% CI

GSV

95% CI

Detached housing

106

0.50

0.59

74

76

0.58

[0.44, 0.71]

0.64

[0.52, 0.77]

0.60

[0.48, 0.73]

0.65

[0.52, 0.77]

Institutional

106

0.13

0.18

90

91

0.54

[0.30, 0.79]

0.69

[0.52, 0.87]

0.84

[0.76, 0.93]

0.86

[0.77, 0.94]

Broken/boarded windows*

105

0.22

0.35

81

80

0.45

[0.25, 0.65]

0.56

[0.39, 0.73]

0.62

[0.47, 0.77]

0.60

[0.44, 0.76]

Attached housing

105

0.20

0.30

80

77

0.41

[0.21, 0.60]

0.50

[0.38, 0.58]

0.70

[0.58, 0.82]

0.66

[0.53, 0.78]

Trees that shade sidewalk

105

0.17

0.32

82

67

0.37

[0.17, 0.57]

0.31

[0.17, 0.46]

0.73

[0.62, 0.84]

0.50

[0.36, 0.64]

Amount of street trees

106

0.38

0.45

63

59

0.33

[0.18, 0.48]

0.33

[0.20, 0.47]

0.45

[0.31, 0.59]

0.39

[0.25, 0.53]

Bars on the windows*

105

0.19

0.20

76

82

0.26

[0.08, 0.45]

0.43

[0.22, 0.64]

0.52

[0.36, 0.69]

0.64

[0.49, 0.79]

Slope of the segment

106

0.17

0.14

75

83

0.19

[0.01, 0.38]

0.30

[0.09, 0.52]

0.63

[0.51, 0.76]

0.75

[0.64, 0.85]

Vacant building/Lot

106

0.30

0.45

58

57

0.13

[0.06, 0.27]

0.25

[0.10, 0.40]

0.38

[0.23, 0.52]

0.35

[0.21, 0.49]

Housing apartments

106

0.16

0.20

75

75

0.15

[−0.02, 0.33]

0.24

[0.06, 0.41]

0.63

[0.51, 0.76]

0.62

[0.49, 0.74]

  1. PR average prevalence, PA percent agreement, GP GigaPan®, GSV Google Street View, CI confidence interval, PABAK prevalence-adjusted bias-adjusted kappa. An * denotes the variable was dichotomous. All other variables not denoted with * were recoded to be dichotomous solely when calculating prevalence. Significant differences across audit tools are italicized.