Software Development

Dr. Goovaerts has developed executables for several projects:

  1. An automatic variogram modeling function was developed and included in SADA (Spatial Analysis and Decision Assistance) and SpaceStat software.
  2. For the ASARCO study, a computer program was written to allow employees at Ecology to compute for each block-group within the modeled area:
    • the mean arsenic concentration,
    • the average (expected) number of parcels that exceeds a given Threshold T’,
    • the probability that a fraction X’ of the parcels exceeds a given Threshold T’, and
    • the fraction X of the parcels for which the threshold T is exceeded with a given probability P.

    Both parameters X’ and T’ are specified by the user who can choose multiple fractions and thresholds per run. The parameters T and P can also be specified by the user but only one value is allowed by run.

  3. For the New York City DOHMH project, an approach was developed and implemented into an executable called outbreak-simulation.exe to:
    • compute outbreak magnitudes based on a parameterization of the Serfling base model for five different syndromes, the four seasons and three spatial distributions (Single zip code, zip code cluster, and citywide),
    • generate outbreaks for three different epidemic curves (single-day spike, point-source exposure, and propagated transmission) and three durations (3, 5, and 15 days),
    • add the simulated syndrome counts to the actual daily counts recorded for the period 1/1/2010-12/31/2011 accounting for the frequency of visits from ZIP codes to hospitals.
  4. Public-domain code was developed and published to perform Poison kriging of rate data. Goovaerts, P. 2005. Geostatistical analysis of disease data: estimation of cancer mortality risk from empirical frequencies using Poisson kriging. International Journal of Health Geographics, 4:31.
  5. Public-domain code was developed and published to perform multiple indicator kriging. Goovaerts, P. 2009. AUTO-IK: a 2D indicator kriging program for the automated non-parametric modeling of local uncertainty in earth sciences. Computers and Geosciences, 35, 1255-1270.
  6. Code was developed for a NASA project (PI, Dan Brown) to simulate the spatial distribution of land-cover types under various constraints using simulated annealing. Brown, D.G., Goovaerts, P., Burnicki, A., and M.Y. Li. 202. Stochastic simulation of land-cover change using geostatistics and generalized additive models. Photogrammetric Engineering and Remote Sensing, 28(10): 1051-1061.