Virginia Lynn Kalb

While my work here at Goddard has varied widely over the years, my strengths in computer programming and data analysis have been the common threads running through all of the projects. My background in mathematics and computer science has proven to be valuable for many diverse applications for NASA. Recently my time has been split between support of MODIS and VIIRS geolocation and data processing algorithms, including the VIIRS Day/Night band, and interdisciplinary work with Code 670. The latter work is supported by the Science Innovation Fund, and we are currently evaluating the synergy among multiple data sources: the Day/Night band data, aurora forecast model data, in situ electromagnetic field data, and citizen science aurora observations. Previous SIF support has enabled the development and validation of a vortex identification algorithm for data-mining of magnetosphere model data.

Notable previous work includes GUI, client-server programming, and graphics for the Federal Ecosystem Dynamics Project, and, in collaboration with Thomas Goff, design and implementation of the original Global Inventory Monitoring and Modeling System (GIMMS) production level mapping and image processing system for the study of land processes on global and continental scales using satellite data.

M.S. Geographic Information Systems, Johns Hopkins University. 2017
  "Evaluating a Vegetation Adjusted Nighttime Lights Urban Index"
Ph.D. Applied Mathematics, University of Maryland, College Park. 2004
  "Low-Dimensional Models for Fluid Flow"
M.A. Mathematics, University of Maryland, College Park
  "A derivation of the Wallpaper Groups"
B.A. Mathematics, University of Maryland, Baltimore County
 

Mathematica for prototyping and data analysis;
ArcGIS for GIS spatial analysis;
Python, especially useful for a programmable interface with ArcGIS;
‘C’ programming language