This study focuses on the use of systematic social observations (SSO) to measure crime prevention through environmental design (CPTED) and disorder. To improve knowledge about measurement issues in small area research, SSO is conducted by means of three different methods: in-situ, photographs, and Google Street View (GSV) imagery. By evaluating the methodological quality of the observation methods, the results of our study suggest that virtual SSO approaches have considerable promise for the reliable assessment of physical properties of small areas. We discuss challenges and provide avenues for future research to encourage the evolution of a more reliable approach to measure the physical environment.

本研究侧重于使用系统社会观察 (SSO) 通过环境设计 (CPTED) 和无序来衡量犯罪预防。为了提高对小区域研究中测量问题的了解，SSO 通过三种不同的方法进行：原位、照片和谷歌街景 (GSV) 图像。通过评估观察方法的方法学质量，我们的研究结果表明，虚拟 SSO 方法对于小区域物理特性的可靠评估具有相当大的前景。我们讨论了挑战并为未来的研究提供了途径，以鼓励发展一种更可靠的方法来测量物理环境。