TECHNOLOGY AREAS: Information Systems

ACQUISITION PROGRAM: N/A

RESTRICTION ON PERFORMANCE BY FOREIGN CITIZENS (i.e., those holding non-U.S. Passports): This topic is "ITAR Restricted." The information and materials provided pursuant to or resulting from this topic are restricted under the International Traffic in Arms Regulations (ITAR), 22 CFR Parts 120 - 130, which control the export of defense-related material and services, including the export of sensitive technical data. Foreign Citizens may perform work under an award resulting from this topic only if they hold the "Permanent Resident Card", or are designated as "Protected Individuals" as defined by 8 U.S.C. 1324b(a)(3). If a proposal for this topic contains participation by a foreign citizen who is not in one of the above two categories, the proposal will be rejected.

OBJECTIVE: Develop software tools that incorporate innovative methods for analyzing spatio-temporal data. The tools should integrate seamlessly with existing geographic information system (GIS) software.

DESCRIPTION: In recent years, spatio-temporal statistical methods have been developed in academia and in the GIS (Geographic Information System) community. At the same time, the ability to exploit the spatial and temporal characteristics of data has become more important in DoD applications. We seek innovative theoretical and methodological approaches for analyzing spatial data that have a time component associated with them. Of particular interest are methods that work with spatio-temporal data sets that are messy and have missing data.

Most of the methods in spatio-temporal statistics have been implemented in research software environments such as R (open-source statistical computing software) and are not available in a commercial GIS package such as ArcMap. Thus, analysts must often analyze the data using many different tools (e.g., R, Excel, MATLAB) and import the results into a GIS package; this can create errors and also takes significant time and effort on the part of the analyst.

The goal of this effort is to develop and employ state-of-the-art spatio-temporal statistical methods to create an integrated software toolbox that will work with existing GIS packages. These tools must work seamlessly with the GIS software and should be implemented in Python or visual basic to allow for an efficient analytic process.

PHASE I: Research literature and GIS software capabilities, conduct an evaluation to determine best-of-breed spatio-temporal analysis techniques, and propose new analytic methods.

PHASE II: Design, develop and demonstrate prototype software to meet performance needs, such as the ability to seamlessly connect with a GIS package. This phase might also include creating and implementing new methods for analyzing spatio-temporal data sets that are messy and have missing data.

PHASE III: Integrate software with existing systems and demonstrate improved capability based on realistic scenarios.

PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: A software toolkit developed under this effort can be applied wherever geographical information systems are used. These include geographic criminology, epidemiology, city planning, environmental science, remote sending, and more.

REFERENCES:
1. Applied Spatial Data Analysis with R by Bivand, Pebesma, Gomez-Rubio, 2008, Springer-Verlag

2. Statistical Methods for Spatial Data Analysis by Schabenberger and Gotway, 2005, CRC Press

3. Statistics for Spatial Data by Cressie, John Wiley & Sons, 1993

4. Interactive Spatial Data Analysis by Bailey and Gatrell, 1995, Longman Scientific & Technical

5. CRAN website for R: http://cran.r-project.org/

6. Analysis of Incomplete Multivariate Data by J. K. Schafer, 1997, CRC Press

KEYWORDS: Spatial statistics; messy and missing data; spatio-temporal; modeling and simulation; software tools; algorithms

** TOPIC AUTHOR (TPOC) **

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