Recently, Google Street View (GSV) has been examined as a tool for remotely conducting systematic observation of the built environment. Studies have found it offers benefits over in-person audits, including efficiency, safety, cost, and the potential to expand built environment research to larger areas and more places globally. However, one limitation has been the lack of documentation on the date of imagery collection. In 2011, Google began placing a date stamp on images which now enables investigation of this concern. This study questions the spatio-temporal stability in the GSV date stamp. Specifically, is the imagery collected contemporaneously? If not, how frequently and where is imagery from different time periods woven together to represent environmental conditions in a particular place. Furthermore, how much continuity exists in imagery for a particular time period? Answering these questions will provide guidance on the use of GSV as a tool for built environment audits.

How people feel about places matters, especially in their neighborhood. It matters for their health, the health of their children, and their social cohesion and use of local resources. A growing body of research in public health, planning, psychology, and sociology bears out this point. Recently, a new methodological tack has been taken to find out how people feel about places. The sketch map, a once popular tool of behavioral geographers and environmental psychologists to understand how people perceive the structural aspects of places, is now being used in concert with geographic information systems (GIS) to capture and spatially analyze the emotional side of urban environmental perception. This confluence is generating exciting prospects for what we can learn about the characteristics of the urban environment that elicit emotion. However, due to the uncritical way this approach has been employed to date, excitement about the prospects must be tempered by the acknowledgement of its potential problems. In this paper we review the extant research on integrating sketch maps with GIS and then employ a case study of mapping youth fear in Los Angeles gang neighborhoods to demonstrate these prospects and the problems, particularly in the areas of (1) representation of environmental perception in GIS and (2) spatial analysis of these data.

Understanding the spatial dimension of fear of crime in the urban environment is important to understanding behaviors in response to this concern. Making this connection between perception and action has long been a goal of scholars in the social and health sciences, though this complex relationship has yet to be fully elucidated. Specifically, in studies on fear of crime and its influence on behavior, a variety of definitions and methods have been employed. This situation has yielded insights, as well as inconsistencies. In the past decade, Geographic Information Systems (GIS) has been added to this methodological mix, though it too has contributed limited understanding of the environmental perception-behavior nexus. During this time, some scholars have integrated a traditional technique for accessing environmental perception, the sketch map, with this newer technology. This article provides a review and critical assessment of the way GIS has been used to understand fear of crime, specifically through th...

A call has recently been made by the public health and medical communities to understand the neighborhood context of a patient’s life in order to improve education and treatment. To do this, methods are required that can collect “contextual” characteristics while complementing the spatial analysis of more traditional data. This also needs to happen within a standardized, transferable, easy-to-implement framework. The Spatial Video Geonarrative (SVG) is an environmentally-cued narrative where place is used to stimulate discussion about fine-scale geographic characteristics of an area and the context of their occurrence. It is a simple yet powerful approach to enable collection and spatial analysis of expert and resident health-related perceptions and experiences of places. Participants comment about where they live or work while guiding a driver through the area. Four GPS-enabled cameras are attached to the vehicle to capture the places that are observed and discussed by the participant. Audio recording of this narrative is linked to the video via time stamp. A program (G-Code) is then used to geotag each word as a point in a geographic information system (GIS). Querying and density analysis can then be performed on the narrative text to identify spatial patterns within one narrative or across multiple narratives. This approach is illustrated using case studies on post-disaster psychopathology, crime, mosquito control, and TB in homeless populations. SVG can be used to map individual, group, or contested group context for an environment. The method can also gather data for cohorts where traditional spatial data are absent. In addition, SVG provides a means to spatially capture, map and archive institutional knowledge. SVG GIS output can be used to advance theory by being used as input into qualitative and/or spatial analyses. SVG can also be used to gain near-real time insight therefore supporting applied interventions. Advances over existing geonarrative approaches include the simultaneous collection of video data to visually support any commentary, and the ease-of-application making it a transferable method across different environments and skillsets.

New geographic approaches are required to tease apart the underlying sociospatial complexity of neighborhood decline to target appropriate interventions. Typically maps of crime hotspots are used with relatively little attention being paid to geographic context. This article helps further this discourse using a topical study of a neighborhood drug microspace, a phrase we use to include the various stages of production, selling, acquiring, and taking, to show how context matters. We overlay an exploratory data analysis of three cohort spatial video geonarratives (SVGs) to contextualize the traditional crime rate hotspot maps. Using two local area analyses of police, community, and ex-offender SVGs and then comparing these with police call for service data, we identify spaces of commonality and difference across data types. In the Discussion, we change the scale to consider revealed microspaces and the interaction of both “good” and “bad” places. We enrich the previous analysis with a mapped spatial video assessment of the built environment and then return to the narrative to extract additional detail around a crime-associated corner store next to a community center. Our findings suggest that researchers should reevaluate how to enrich typical hotspot approaches with more on-the-ground context.