Thomas Bilintoh

  • M.S. in Geography

  • Email: bilintoh@msu.edu
  • Geography Building
    673 Auditorium Rd., Rm. #116
    East Lansing, MI 48824
  • Areas of interest: Spatial Data Analysis, Error propagation in geospatial data, and . Modelling the spatial distribution of crop pest through remotely sensed data and GIS
M.S. in Geography

Research Synopsis:

I consider myself a GIS & Remote Sensing analyst at core.  However, my main concentration is how users and experts of geospatial data handle uncertainty. My approach basically revolves around using probability, statistics and fuzzy set theory to depict how uncertainty can be handed in geospatial data in the field of GIS and Remote Sensing.

I have applied these methods in a variety of research involving: site suitability such as landfill selection, electric pylon route selection and my most recent work which is focusing on using remotely sensed images and statistical models to characterize the extent of damage on maize as a result of Amyworm infestation in Brong Ahafo-Ghana.