Enhancing Disaster Management: Development of a Spatial Database of Day Care Centers in the USA
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Children under the age of five constitute around 7% of the total U.S. population and represent a segment of the population, which is totally dependent on others for day-to-day activities. A significant proportion of this population spends time in some form of day care arrangement while their parents are away from home. Accounting for those children during emergencies is of high priority, which requires a broad understanding of the locations of such day care centers. As concentrations of at risk population, the spatial location of day care centers is critical for any type of emergency preparedness and response (EPR). However, until recently, the U.S. emergency preparedness and response community did not have access to a comprehensive spatial database of day care centers at the national scale. This paper describes an approach for the development of the first comprehensive spatial database of day care center locations throughout the USA utilizing a variety of data harvesting techniques to integrate information from widely disparate data sources followed by geolocating for spatial precision. In the context of disaster management, such spatially refined demographic databases hold tremendous potential for improving high resolution population distribution and dynamics models and databases.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE
- Grant/Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1210152
- Journal Information:
- ISPRS international journal of geo-information, Vol. 4, Issue 3; ISSN 2220-9964
- Publisher:
- MDPICopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
Multi-Objective Emergency Material Vehicle Dispatching and Routing under Dynamic Constraints in an Earthquake Disaster Environment
|
journal | May 2017 |
Similar Records
Multi-Formalism Modeling for Disaster Resilience, Forecasting, and Response
USA Structures Phase 2 Technical Report