Using Street View Images to Examine the Impact of Built Environment on Street Property Crimes in the Old District of CA City, China

Table 2

Negative binomial regression results.

Variables	Model 1: whole day		Model 2: before dawn		Model 3: daytime		Model 4: nighttime
	B	IRR	B	IRR	B	IRR	B	IRR
Greenness	−0.14	0.87	−0.77	0.46	0.23	1.25	−0.55	0.32
Road coverage	−0.13	0.88	0.47	1.60	−0.26	0.77	0.393	1.48
Closeness	−0.21	0.81	−0.44	0.65	0.86	1.37	0.245	1.28
Openness	0.60	1.82	0.02	1.02	0.63	1.82	0.27	1.31
Distance to the nearest police patrol station	−0.21	0.81	−0.19	0.83	−0.20	0.82	−0.514	0.60
Police camera	−0.21	0.81	0.13	1.14	−0.60	0.55	0.19	1.22
Restaurant	1.02	1.59	0.99	1.72	0.97	1.52	0.08	1.09
Bubble tea and cafe	−0.03	0.97	0.22	1.25	−0.96	0.38	0.37	1.45
Convenience store	0.01	1.01	−0.24	0.78	0.14	1.13	−0.01	1.00
Grocery store	−0.61	0.54	−0.39	0.67	−0.86	0.76	−0.53	0.59
Bank	0.50	1.64	−0.03	0.97	0.53	1.62	0.43	1.14
Bar	0.40	1.50	0.81	2.26	0.01	1.01	0.13	1.14
AIC	2557.10		2245.38		2077.76		1995.96
N	212		101		76		35

Significance level marks: “”: ; “”: .