Healthy Cities

The health impact of individuals’ exposure to built environment is a key issue in the field of healthy city research. Individuals’ exposure to built environment means someone’s contact with the built environment, especially with the harmful factors. Accurate assessment of exposure to built environment is the basis of research on how built environment influences human health. As for the indicators and data in studies of assessing individuals’ exposure to built environment, indicators from 5D theory like density, diversity, design, destination accessibility and distance to transition were usually used, and to measure these indicators, GIS data were usually used. However, in these studies, less attention is paid to image data that can reflect the human-scale built environment characteristics such as the indicator of neighborhood physical disorder, which lead to limitation of assessment dimension. As for the assessment areas and spatial averaging methods in studies of assessing individuals’ exposure to built environment,  most of them take the neighborhood of individuals’ residence as the assessment area for the whole day, ignoring individuals’ mobility, which can be called the static residence-based approach. But there comes two problems in this approach, the first is that the region-based attributes could be affected by how the residential units are geographically delineated, which is called Uncertain Geographic Context Problem; and the second is that the assessment can be erroneous when people’s mobility is ignored, because people’s daily mobility may amplify or attenuate the exposures they experienced in their residential neighborhoods, which is called the Neighborhood Effect Averaging Problem. The consideration of individuals’ mobility is the common solution to avoid the above problems. Few studies have used the mobility-based approach to assess individuals’ exposure to built environment, however, these studies are mainly based on 5D indicators and GIS data. Thus, individual mobility has not been considered in assessment of exposure to built environment based on image data, which is a combined limitation in assessment indicator and data, as well as in assessment area and spatial averaging method. With the development of science and technology, the available tools for assessing exposure to built environment are becoming more and more abundant. It is suggested that in the future studies of assessing individuals’ exposure to built environment, for assessment data, image data that can reflect the human-scale quality of the built environment should be considered, and for assessment area, individuals’ mobility should be considered. Referring to the assessment of exposure to natural environment, in this article, two assessment methods of individuals’ exposure to built environment based on image data and individuals’ mobility are proposed. The first one is to assess exposure to built environment by overlaying individuals’ spatio-temporal trajectories with spatial distribution map of street view images. By auditing the street view images, the researchers can get the score of human-scale built environment characteristics, then by overlaying the map of built environment characteristics with the map of  individuals’ spatio-temporal trajectories, the researcher can get the time-weighted averaging built environment characteristics that the individual exposed to. The second one is to invite the individual to wear a wearable camera to record the built environment they exposed to. The wearable camera can take photos at regular intervals, and by auditing these photos and calculating the results, the researcher can get the time-weighted averaging built characteristics the individual exposed to. Compared with the two proposed methods, for assessment accuracy, the first one is less accurate because the update frequency of street view images is not high and the spatial coverage area of them is not complete; while the second one is more accurate because the photos taken by wearable camera can record the complete and real-time built environment information. For labor and capital cost, the first proposed method has less capital cost and more labor cost. It is because that the street view images can be freely downloaded but the wearable camera is costly to buy. And although the two proposed methods both have to audit images, on the basis, the first proposed method has to do more work in overlaying the trajectories. For the above reasons, the two proposed methods are suitable in different scenarios. The new methods proposed in this article fill the gap that the assessment of individuals’ exposure to built environment seldom consider the image based human scale built environment characteristics in existing studies, and with the consideration of mobility, the new methods are more accurate compared with the existing static residence-based assessment approach. The new assessment method of individuals’ exposure to built environment will help the exploration of the new theory in the field of healthy city research.