The document outlines Brian Scott Pfeiffer's Masters Degree program at the University of Denver which included courses in Geographic Information Systems, Cartography, Remote Sensing, Digital Image Processing, and Python Programming. It describes two of his final projects, one involving creating a grizzly bear habitat model for an intro GIS course, and another using Python to analyze cell tower coverage for water meters uploading data for a municipality. It also lists topics covered in his remote sensing and digital image interpretation courses.

1. Brian Scott Pfeiffer
University of Denver
Masters Degree in Geographic Information Systems
 Introduction to GIS
 Cartography
 Remote Sensing
 Digital Image Processing
 Python Programming
 Hydrologic Mapping

9. Final Project for Intro to Cartography

11. Grizzly Bear Habitat Model for Into to GIS

12. Citeria
 Mountain environment
elevation above 2500 meters
elevation below 3550 meters
 Forest Cover
 Within 5 miles of a major stream
 At least three miles from major roads
 Home range must be fifty square miles

13. Water Meter Cell Reception Project for Python Programming
A friend of mine works for a company that sells water meters that collect flow data every
fifteen minutes. At around 3:00 am every morning the water meters upload the days data
onto a main server via the Verizon cell network. While speaking with him one day he told me
that a municipality had concerns that all their water meters would be within good cell
coverage. Since Verizon does not disclose information about their cell coverage zones to
anyone, I decided that this would make an excellent final project for my Python programming
class.
For the input data for this project I would require the following:
1) A digital elevation model (DEM) of the area with enough overlap to account for cell towers
that could be as far as 24 kilometers outside my boundary AOI
2) A .csv file of Verizon cell towers locations by latitude and longitude and their height to use
for a viewshed analysis, which I found on a helpful site online
3) A .txt file of water meter locations by latitude and longitude with their street names that I
created in ArcMap as a shapefile and transferred to a .txt file
4) A boundary shapefile of my AOI
5) A few roads shapefiles to use as reference for the final maps.

16.  Georeferencing using control points
 Creating Orthoimages using tie points
 Mosaicking
 Creating 3D models from DEMs and imagery
 Ground measurements using shadow offsets
 Resampling and filtering imagery
 Image classification using auto-classification
methods
 Multiband spectral classification
 Manual land use classification
 Creating vector data
 Color manipulation
 Pan sharpening
 Co-occurrence chart interpretation for auto
classification
Digital Image Interpretation Projects

17.  Concepts and foundations of remote sensing
 Spectra analysis and identification
 Photogrammetry
 Areal photography including film, digital
image, video
 Spatial resolution of airborne remote sensing
systems
 Remote sensing platforms
 Multispectral, thermal, and hyperspectral
sensing
 Earth recourses satellites operating in the
optical spectrum
 GPS
 Microwave and lidar sensing
 Project planning
 Applications of remote sensing
Remote Sensing Topics