This study reviews the methods of measuring and assessing walking environments, which are classified into two categories:objective method and subjective method. The objective method is mainly based on GIS technology and data to measure neighborhood walkability at a meso or macro urban scale, which is relatively weak in measuring micro walking environment. The subjective method is mainly based on questionnaire scales and on-site participatory approaches to assess the walking environment at meso and micro scales, focusing on the pedestrian's subjective perception of the objective built environment, and considering the impact of individual walking ability, walking preference, and socio-economic attributes. With the rise and application of 3D GIS models, street view image data, and machine learning methods, objective methods have shifted from two-dimensional walkability measurement to three-dimensional measurement. Meanwhile, the research scale has also shifted from macro-scale to micro-scale, concentrating more on people and considering more refined walking environment elements that meet visual aesthetic needs from a human-oriented perspective. The subjective method turns to combine new technologies and methods such as machine learning, big data algorithm, virtual reality technology, and wearable physiological sensors to obtain the pedestrian's subjective perception of the walking environment. In the end, we propose future research trends and prospect the measurement and assessment of urban walking environments in China in the context of a humanoriented turn.

walking environment  /  walkability  /  human-oriented turn