Table 1 Formulas and explanations for each indicator.
From: A novel framework integrating GeoAI and human perceptions to estimate walkability in Wuhan, China
First-level indicators | Second-level indicators | Formula | Quantitative definition based on street view data |
|---|---|---|---|
Greenness | Vegetation coverage rate | \({G_i}=\frac{{\sum\nolimits_{{i=1}}^{4} {{V_i}} }}{4}\) | Vi is the number of vegetation pixels; |
Openness | Sky visible ratio | \({O_i}=\frac{{\sum\nolimits_{{i=1}}^{4} {{S_i}} }}{4}\) | Si is the number of sky pixels; |
Crowdedness | Space occupancy rate | \({C_i}=\frac{{\sum\nolimits_{{i=1}}^{4} {({M_i}+{P_i})} }}{4}\) | Mi is the number of non-motor vehicles pixels; Pi is the number of people pixels; |
Traffic flow | \({T_{traffic}}=\left\{ {\begin{array}{*{20}{c}} {0,}&{smooth} \\ {1,}&{slow} \\ {2,}&{congestion} \end{array}} \right.\) | 0,1,2 mean different levels of traffic flow; | |
Safety | Proportion of sidewalks | \({P_i}=\frac{{\sum\nolimits_{{i=1}}^{4} {P{1_i}} }}{{\sum\nolimits_{{i=1}}^{4} {{R_i}} }}\) | P1i is the number of sidewalk pixels; Ri is the number of road pixels; |
Road safety facilities | \({F_{facility}}=\left\{ {\begin{array}{*{20}{c}} {0,}&{deficient} \\ {1,}&{inadequate} \\ {2,}&{relatively{\text{ }}perfect} \\ {3,}&{complete} \end{array}} \right.\) | 0,1,2,3 mean the degree of perfection of road safety facilities; | |
Parking phenomenon on the sidewalk | \({F_{park}}=\left\{ {\begin{array}{*{20}{c}} {0,}&{exist} \\ {1,}&{non - exist} \end{array}} \right.\) | 0,1 mean whether the sidewalk parking phenomenon exists. |
