In this session we invite papers using a variety of data sources to explore the characteristics of neighborhoods, or other spaces smaller than a city. This could include:
*Remotely Sensed Images
*Digital Trace Data (e.g. social media or cell phone data)
*High Resolution Buildings Data
We invite any synthesis of these or related data sources to explore or characterize sub-city properties, including spatial heterogeneity, spatial inequality, resilience or vulnerability.
If you would like to present please email Christa Brelsford (firstname.lastname@example.org) and Sarah Walters (email@example.com) an abstract no longer than 250 words, including AAG ID#, for consideration.
What makes a neighborhood? We have a qualitative understanding that parts of cities have very different characters - but how can we define that empirically? Many fine spatial resolution datasets on population, infrastructure, the built environment, and behavior have recently become available. Thus far, they’ve mostly been used independently. We believe the integration of these different sources, to include both quantitative and qualitative information, is a promising avenue for research into cities and neighborhoods. Data like census microdata, remotely sensed information, digital trace data, and detailed building characterizations can be independently applied to characterize neighborhoods, but combinations of the datasets are a novel contribution. These data can be used to generate a holistic understanding of neighborhoods, just as cities are currently defined based on combinations of infrastructure, population, and behavior patterns. Neighborhoods, too, can be understood by using a perspective that integrates patterns in the physical infrastructure and built environment, the types of businesses there, population, culture, demographics, mobility, and social connectivity. Urban dwellers are directly impacted by issues of urban resilience and vulnerability. A multi-modal perspective will more accurately represent their lived experience, and therefore enable a better understanding of neighborhoods and communities.
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