TY - JOUR
T1 - Toward Integrated Urban Observatories
T2 - Synthesizing Remote and Social Sensing in Urban Science
AU - Yu, Danlin
N1 - Publisher Copyright:
© 2025 by the author.
PY - 2025/6
Y1 - 2025/6
N2 - Urbanization is reshaping landscapes and posing unprecedented sustainability challenges, necessitating more integrative approaches to urban observation. This review synthesizes recent advancements in traditional remote sensing and emerging social sensing technologies, emphasizing their convergence within urban science. A systematic thematic analysis of 667 peer-reviewed articles highlights the methodological progress, practical applications, and theoretical innovations arising from this integration. Traditional remote sensing effectively captures urban physical features but lacks insights into human behaviors. Conversely, social sensing, leveraging digital traces from social media and mobile data, introduces essential human-centered dimensions into urban monitoring. The fusion of these complementary paradigms through advanced data analytics and multimodal integration has produced transformative methodologies, enhancing urban resilience frameworks, functional zone delineation, and real-time disaster responses. Despite significant progress, the integration faces persistent challenges, including data heterogeneity, representational bias, ethical concerns, and scalability limitations. Differing from previous reviews that survey the landscape, the current work argues that current integration efforts remain ad hoc and technologically driven, lacking a unifying theory for real-time urban governance. To address this critical gap, I develop and operationalize a new systems-based framework for hybrid urban observatories. This framework is built on a socio-ecological foundation and explicitly integrates technical components with an essential governance layer, advancing both methodological rigor and actionable guidance for the field. Such a framework will enable a more holistic, responsive, and equitable approach to urban governance and sustainability.
AB - Urbanization is reshaping landscapes and posing unprecedented sustainability challenges, necessitating more integrative approaches to urban observation. This review synthesizes recent advancements in traditional remote sensing and emerging social sensing technologies, emphasizing their convergence within urban science. A systematic thematic analysis of 667 peer-reviewed articles highlights the methodological progress, practical applications, and theoretical innovations arising from this integration. Traditional remote sensing effectively captures urban physical features but lacks insights into human behaviors. Conversely, social sensing, leveraging digital traces from social media and mobile data, introduces essential human-centered dimensions into urban monitoring. The fusion of these complementary paradigms through advanced data analytics and multimodal integration has produced transformative methodologies, enhancing urban resilience frameworks, functional zone delineation, and real-time disaster responses. Despite significant progress, the integration faces persistent challenges, including data heterogeneity, representational bias, ethical concerns, and scalability limitations. Differing from previous reviews that survey the landscape, the current work argues that current integration efforts remain ad hoc and technologically driven, lacking a unifying theory for real-time urban governance. To address this critical gap, I develop and operationalize a new systems-based framework for hybrid urban observatories. This framework is built on a socio-ecological foundation and explicitly integrates technical components with an essential governance layer, advancing both methodological rigor and actionable guidance for the field. Such a framework will enable a more holistic, responsive, and equitable approach to urban governance and sustainability.
KW - big data
KW - data fusion
KW - remote sensing
KW - social sensing
KW - urban observatories
KW - urban sustainability
UR - https://www.scopus.com/pages/publications/105009020709
U2 - 10.3390/rs17122041
DO - 10.3390/rs17122041
M3 - Review article
AN - SCOPUS:105009020709
SN - 2072-4292
VL - 17
JO - Remote Sensing
JF - Remote Sensing
IS - 12
M1 - 2041
ER -