GIS and Remote Sensing Lecture Notes

  1. Introduction and Data Types
    1. what is a GIS?
    2. what a GIS does
    3. course goals
    4. GIS components
    5. 3 types of data
    6. Spatial data types
    7. raster vs. vector
    8. topology
  2. Maps: Projections and Datums
    1. Where did you say you were calling from?
    2. Projections create distortion
    3. Spheroids
    4. A datum
    5. UTM
  3. Spatial Overlays and Querying
    1. boolean logic
    2. overlay analysis (overview)
    3. feature overlay
    4. simplification
    5. complexity of combinations
    6. reclassification
    7. types of combinations
    8. Overlay querying (hind-casting or inverse modeling)
  4. Digital Terrain Analyses
    1. Data sources and DEMs, TINs, DLGs, DTMs  (geez, English please)
    2. manipulating and moving between DTMs
    3. map slope, aspect,  & curvature
    4. profiles and viewsheds
    5. perspectives and shaded relief .
    6. Watershed Analyses
  5. Modeling and Algorithms
    1. spatial modeling
    2. thinking through an analysis using an algorithm
  6. Location-related calculations
    1. Buffers
    2. "Rubber rulers" (dynamically-scaled buffers)
    3. Friction/Least Cost Paths
    4. Patch simplification and "clumping"
    5. Proximity and "near"ness
    6. Density
  7. Neighborhood Analyses
    1. Filters
    2. Creating surfaces by interpolation
  8. Shape Analyses
    1. Lines; length, azimuth, sinuosity
    2. Distribution of points, lines, and polygons
    3. Patch size, shape, connectivity
  9. Fuzzy Logic: Fuzzy Sets, Conditional Inclusion and Bayes Theorem
    1. A "fuzzy" boundary
    2. Fuzzy Inclusion set using distance data
    3. Bayesian Probability Modeling
  10. Remote Sensing Data
    1. The electromagnetic spectrum
    2. Spectral signatures
    3. Sensor Types
    4. Landsat
    5. LIDAR
  11. Image Processing
    1. Enhancement and Visualization
    2. What passive sensors mostly "see"
    3. Atmospheric Correction
    4. Ratios
    5. decorrelation
    6. Principal Component Analysis
    7. geolocating images
    8. other enhancements
  12. Image Classification
    1. general principles
    2. simple discriminants
    3. unsupervised classification
    4. supervised classification
    5. transferring a supervised classification
    6. using classification
  13. GPS / GNSS (global positioning system / Global Navigation Satellite System)
    1. The Satellite System
    2. Receivers and measurement types
    3. Using GPS
  14. Map Composition
    1. map composition