Skip to main content
. 2024 Feb 28;12:1337804. doi: 10.3389/fpubh.2024.1337804

Table 2.

Measures of street greenness and active travel in the studies included in the review.

Study ID First author (year) Type of street greenness measure Detailed measure of street greenness Type of active travel measure Detailed measure of active travel
1 Sarkar, 2015 (34) Objective measure The density of street trees Self-reported questionnaire: London Travel Demand survey Walking distance
2 Li, 2018 (35) Objective measure: derived from Google Street View images The amount of street greenery: Green View Index Objective measure: collected from a smartphone application Walking activities: trip number
3 Lu, 2018a (36) Objective measure: derived from Google Street View images The eye-level street greenness Objective measure

  1. The odds of walking

  2. Total walking time
4 Lu, 2018b (15) Objective measure: derived from Google Street View images The availability of eye-level street greenery Self-report questionnaire: HKTCS

  1. The odds of walking

  2. Total walking time
5 Lu, 2018c (37) Objective measure: derived from Google Street View images The quantity and quality of street greenery Self-reported questionnaire: IPAQ The total duration of green physical activity (≥150 min/week vs. 150 min/week)
6 Lu, 2019 (38) Objective measure: derived from Google Street View images Eye-level street greenness Self-reported questionnaire: HKTCS The odds of cycling
7 Tsai, 2019 (30) Objective measure: EnviroAtlas Street tree cover Self-report questionnaire: survey of the Health of Wisconsin

  1. The odds of walking or cycling

  2. Frequency of walking or cycling

  3. Duration of walking or cycling
8 Vich, 2019 (39) Objective measure: GPS tracking points obtained from MOVES smartphone app Environmental exposure to greenness Objective measure: GPS tracking points obtained from MOVES smartphone app Walking patterns: distances, durations, steps, and burned calories
9 Yang, 2019 (40) Objective measure: derived from Google Street View images The level of street greenery Self-report questionnaire: HKTCS

  1. The odds of engaging in walking

  2. Total walking time
10 Chen, 2020 (29) Objective measure: derived from Tencent Street View Green view index Objective measure: captured the data from Mobike The use of dockless shared bicycles
11 Wang, 2020 (16) Objective measure:
derived from Tencent Online Map		 Eye-level street view greenness Objective measure: obtained from bike-sharing company Mobike Cycling frequency
12 Wu, 2020 (31) Objective measure: derived from Baidu Maps street view image Street green view index

  1. Objective measure: obtained from GPS tracking

  2. Self-report questionnaire: obtained from the travel diary

  1. The probability of Active Travel

  2. Active Travel distance, duration
13 Zang, 2020 (41) Objective measure: obtained from Baidu Street View images Street green view index Self-report questionnaire: IPAQ Total walking time
14 Gao, 2021 (42) Objective measure: obtained via BaiduMap street view images Eye-level urban greenness Objective measure: obtained from the bike sharing operators (Mobike, Ofo, Bluegogo, and Xiaoming Bike) Bike sharing usage
15 Ki, 2021 (18) Objective measure: derived from Google Street View images Street green view index Self-report questionnaire Walking time
16 Ta, 2021 (43) Objective measure: obtained from
Baidu Maps Street View images		 Street Green View Index

  1. Objective measure: obtained from GPS tracking devices

  2. Self-report questionnaire: obtained from the daily activity diary

 Active travel satisfaction
17 Yang, 2021a (44) Objective measure: derived from Google Street View images Eye-level streetscape greenery Self-report questionnaire: HKTCS Walking propensity
18 Yang, 2021b (13) Objective measure: Google Street View imagery Eye-level street greenery index Self-report questionnaire: HKTCS Walking time
19 Bai, 2022 (45) Objective measure: derived from Baidu Maps street view images Street greenery Self-report questionnaire Active travel preference
20 Koo, 2022 (46) Objective measure: derived from Google Street View images Streetscape factors: greenness Self-report questionnaire: National Household Travel Survey The odds of walking
21 Luo, 2022 (32) Objective measure: derived from Baidu Maps Street View images Street green view index Objective measure: Strava data Cycling and running activities
22 Song, 2022 (25) Objective measure Eye-level street greenness Self-report questionnaire: obtained from the daily activity diary Walking satisfaction
23 Bai, 2023 (47) Objective measure: street-view images from Baidu Maps Street-view greenness Objective measure: obtained from the daily order dataset of bicycle-sharing companies updated by the Shenzhen government’s open data platform Cycling frequency
24 Gao, 2023 (48) Objective measure: derived from Baidu Maps street view images The eye-level street greenery view index Objective measure: obtained from Mobike Bike sharing usage
25 Liu, 2023 (49) Objective measure: obtained geo-tagged street view images from Amsterdam’s data portal Street greenery Objective measure: obtained from Dutch National Travel Survey Walking duration
26 Xie, 2023 (17) Objective measure: using the street network analysis provided by Baidu Maps The greenway proximity Self-report questionnaire The use of the East Lake Greenway: frequency, time, and intensity

HKTCS, Hong Kong Travel Characteristics Survey; IPAQ, International Physical Activity Questionnaire.