Information fusion to estimate resilience of dense urban neighborhoods

Anthony Palladino, Elisa J. Bienenstock, Bradley M. West, Jake R. Nelson, Tony H. Grubesic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Diverse sociocultural influences in rapidly growing dense urban areas may induce strain on civil services and reduce the resilience of those areas to exogenous and endogenous shocks. We present a novel approach with foundations in computer and social sciences, to estimate the resilience of dense urban areas at finer spatiotemporal scales compared to the state-ofthe-art. We fuse multi-modal data sources to estimate resilience indicators from social science theory and leverage a structured ontology for factor combinations to enhance explainability. Estimates of destabilizing areas can improve the decision-making capabilities of civil governments by identifying critical areas needing increased social services.

Original languageEnglish (US)
Title of host publicationSignal Processing, Sensor/Information Fusion, and Target Recognition XXVIII
EditorsIvan Kadar, Erik P. Blasch, Lynne L. Grewe
PublisherSPIE
ISBN (Electronic)9781510627017
DOIs
StatePublished - Jan 1 2019
EventSignal Processing, Sensor/Information Fusion, and Target Recognition XXVIII 2019 - Baltimore, United States
Duration: Apr 15 2019Apr 17 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11018
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceSignal Processing, Sensor/Information Fusion, and Target Recognition XXVIII 2019
CountryUnited States
CityBaltimore
Period4/15/194/17/19

Keywords

  • Behavior modeling
  • Dense urban areas
  • Situation/threat assessment
  • Social capital
  • Social/cultural modeling

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Palladino, A., Bienenstock, E. J., West, B. M., Nelson, J. R., & Grubesic, T. H. (2019). Information fusion to estimate resilience of dense urban neighborhoods. In I. Kadar, E. P. Blasch, & L. L. Grewe (Eds.), Signal Processing, Sensor/Information Fusion, and Target Recognition XXVIII [110180K] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11018). SPIE. https://doi.org/10.1117/12.2519304