Table 1.

Glossary of technical terms/expressions used in the article, including concepts, data, and methods, along with use cases.

Term	Explanation
Data pre-processing stage	A stage during which GPS and accelerometry data is pre-processed. Tasks in this stage usually include examining completeness, outliers and accuracy and performing missing data imputation (Duncan et al., 2009; Krenn et al., 2011).
Data integration stage	A stage during which pre-processed GPS and accelerometry data is integrated to produce TAGA point data. Tasks in this stage usually include aggregating (if temporal intervals of GPS and accelerometry data differ) and aligning GPS and accelerometry data by timestamps (James et al., 2016; Kerr et al., 2011).
RBECs exposure assessment stage	A stage during which TAGA point data is processed and integrated with BE GIS data to assess RBECs. Tasks in this stage usually include applying spatial linkage and averaging operations to 1) draw a polygon in space based on TAGA point data (only for buffer-based and activity space-based categories); 2) import and process BE GIS data; 3) calculate RBECs exposure estimates by integrating processed GIS data and TAGA point data (Chaix et al., 2013).
Analytical stage	A stage during which RBECs exposure estimates are analyzed directly or aggregated depending on the research question(s) and the statistical analysis to test the association between built environment and physical activity outcomes is conducted. Tasks in this stage usually include 1a) if domain-based method, aggregate RBECs assessment outputs by BE domains to study distribution patterns of PA outcomes or 1b) if buffer or activity space-based methods, perform statistical analysis to study associations between RBECs and PA outcomes (Chaix et al., 2013; McCrorie et al., 2014).
Domain-based approach	An approach that identifies domains first which could be places of special meaning to individuals (e.g., home, work) or behaviors (e.g., trips) and then assigns RBECs exposure by spatially joining and averaging built environment characteristics within the boundaries of those domain-based activity spaces. For example, Burgi et al. (Bürgi et al., 2016) identified 7 physical activity domains based on TAGA data, drew polygons in space around them, spatially joined them to GIS layers and calculated a spatial average of the built environment characteristics within those polygons as estimates of RBECs.
Spatial averaging approach	An approach that estimates RBECs exposure by spatially averaging built environment characteristics within line- or polygon-based activity spaces. For example, Zenk et al. (Zenk et al., 2018) generated activity space polygons by buffering daily travel paths and calculated spatial averages of BE characteristics within those activity space polygons (e.g., density of fast food outlets).
Time-weighted spatial averaging approach	An approach that estimates RBECs exposure by a) generating weights based on duration of time spent at each location and b) using these weights to calculate a time-weighted spatial average of the BE characteristic within line- or polygon-based activity spaces. For example, the Kernel Density Estimation method is a typical example of a time-weighted spatial averaging approach. Chaix et al. (Chaix et al., 2016) implemented a variation on kernel density estimation approach where they extracted activity hotspots or areas where participants spent the longest duration of time, based on spatial (i.e., densities of points within searching radius) and temporal (i.e., minimum durations of stay at a given location) properties of TAGA point data. Buffers were then generated around these hotspots and spatial averages of BE characteristics were calculated within these buffers.
TAGA point data	A dataset with each row entry contains columns of geographic coordinates collected by GPS and PA movements collected by accelerometry aligned at an epoch-level (e.g., 30-sec).
RBECs exposure assessment outputs	A database that contains both geometries and tabular data attached to each geometry with the calculated summary BE exposure metric which can then be linked to health outcomes.
Activity space	Set of spatial locations one visited during a specific period of time.
GIS Operations
Radius buffer	Radius Buffer (also termed as crow-fly buffer or circular buffer) is a spatial operation that creates polygon geometries around point, line and polygon geometries based on a pre-selected radius distance.
Network buffer	Network Buffer (also termed as street buffer) is a spatial operation that creates polygon geometries around point based on pre-selected distances along street networks.
Spatial join	A spatial operation that assigns attributes of one GIS layer to another intersecting layer in space.
Kernel density estimation	An algorithm that extracts peaks of point data clusters within an extent that is identified by a search radius and generates raster surfaces where each pixel represents the density value.
Trip identification	An algorithm that identifies trip activities from TAGA point data (meaning a series of points with an origin and end) and further classifies trips into different modes (e.g., walk, run, bike, drive).

^*GPS = Global Positioning Systems, GIS = Geographic Information Systems, PALMs = Physical Activity Location Measurement System, TAGA point data = time-aligned GPS accelerometry point data, RBECs = relevant built environment contexts.