TY - JOUR
T1 - Whose park? Crowdsourcing citizen's urban green space preferences to inform needs-based management decisions
AU - Schrammeijer, E.A.
AU - van Zanten, B.T.
AU - Verburg, P.H.
PY - 2021/11/1
Y1 - 2021/11/1
N2 - © 2021 The AuthorsSubjective values of urban green spaces are difficult to quantify and thus easily overlooked in planning processes. Accounting for such values is an important challenge in developing sustainable cities. Crowdsourcing methods, such as big data and smart phone applications, have emerged as promising methods to improve insights into subjective perceptions and preferences. However, we know little about how well these relatively new methods actually quantify subjective values. We assessed several of these new methods by comparing observations of use (n = 1009) to three crowdsourcing methods in one large park in Amsterdam, the Netherlands: a dedicated mobile app providing in situ stated preferences (n = 377), passive social media (n = 78) and a municipal reporting app (n = 187). We show that observed use and passive social media only captured user quantity and were not able to identify green space qualities that are important for mental health functions, such as how relaxing or safe a location is. The dedicated mobile app combined with observed use helped to identify priority locations for improvement. Our findings emphasize that if inadequate measures are used in smart city developments, subjective values and specific user groups will continue to be overlooked in planning processes.
AB - © 2021 The AuthorsSubjective values of urban green spaces are difficult to quantify and thus easily overlooked in planning processes. Accounting for such values is an important challenge in developing sustainable cities. Crowdsourcing methods, such as big data and smart phone applications, have emerged as promising methods to improve insights into subjective perceptions and preferences. However, we know little about how well these relatively new methods actually quantify subjective values. We assessed several of these new methods by comparing observations of use (n = 1009) to three crowdsourcing methods in one large park in Amsterdam, the Netherlands: a dedicated mobile app providing in situ stated preferences (n = 377), passive social media (n = 78) and a municipal reporting app (n = 187). We show that observed use and passive social media only captured user quantity and were not able to identify green space qualities that are important for mental health functions, such as how relaxing or safe a location is. The dedicated mobile app combined with observed use helped to identify priority locations for improvement. Our findings emphasize that if inadequate measures are used in smart city developments, subjective values and specific user groups will continue to be overlooked in planning processes.
U2 - 10.1016/j.scs.2021.103249
DO - 10.1016/j.scs.2021.103249
M3 - Article
SN - 2210-6707
VL - 74
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
M1 - 103249
ER -