Table 5 Descriptive statistical analysis of each metric and their interpretations in the context of sandwiched scenery

From: Exploring spatial visual characteristics of scenic archetypes through AI multimodal mapping methods in Hangzhou Westlake

Metrics

Statistical Values

Interpretation

Implication for Design

S_API

Mean = 43.241; Mdn = 39.368; 95% CI [37.480, 49.002]; Sk = 0.678

Moderate positive skewness

Symmetrical arrangement of foreground elements

P_ECI

Mean = 1.332; 95% CI [1.213, 1.451]; Sk = −0.207

Slight negative skew

Controlled depth transitions in the sandwiching structure

P_LN

Mean = 243.057; 95% CI [235.416, 250.698]; Sk = −2.243

High value with strong negative skew

Very close positioning to the observer

S_ADI

Mean = 0.976; Mdn = 0.994; 95% CI [0.962, 0.990]

Near maximum value

Highly optimized spatial distribution

S_VFR

Mean = 0.451; Mdn = 0.44; 95% CI [0.398, 0.504]

Moderate proportion

Balanced visual field occupation

P_LV

Mean = 165.189; 95% CI [149.898, 180.480]; Sk = −0.64

High value with moderate negative skew

Extended depth reached in the foreground

Foreground T_ISI, T_IVI, T_ESI, T_ER

T_ISI = 0.068, 95% CI [0.053, 0.083]; T_IVI = 114.652, 95% CI [107.875, 121.429]; T_ESI = 2.421, 95% CI [2.183, 2.659]; T_ER = 2.717, 95% CI [2.283, 3.151]

Low T_ISI, moderate T_IVI, T_ESI, T_ER

Enclosed, uniform texture with consistent variations

Middle ground and Background T_ISI, T_IVI, T_ESI, T_ER

T_ISI = 0.767, 95% CI [0.714, 0.820]; T_IVI = 113.588, 95% CI [89.656, 99.028]; T_ESI = 3.005, 95% CI [2.699, 3.311]; T_ER = 5.868, 95% CI [5.425, 6.311]

Higher values across metrics

Open, fragmented textures with rich elements