GIS and Remote Sensing Lecture Notes

  1. Introduction and Data Types
    1. what is a GIS?
    2. what a GIS does
    3. extends "research" to the real world
    4. a GIS is not....
    5. course goals
    6. GIS components
    7. 3 types of data
    8. Spatial data types
    9. raster vs. vector
    10. topology
  2. Maps: Projections and Datums
    1. Where did you say you were calling from?
    2. Projections create distortion
    3. Spheriods
    4. Datums fix the zeros
    5. UTM
  3. Modeling and Algorithms
    1. spatial modeling
    2. thinking through an anlysis using an algorithm
  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. Spatial Overlays and Querying
    1. simplification
    2. overlay complexity
    3. reclassification
    4. boolean logic
    5. querying theme tables and vector "spatial arithmetic"
    6. types of combinations
    7. Overlay querying (hindcasting or inverse modeling)
  6. Location-related calculations
    1. Buffers
    2. "Rubber rulers" (dynamically-scaled buffers)
    3. Friction/Least Cost Paths
    4. Simplification and "clumping"
  7. Neighborhood Analyses
    1. Density
    2. Proximity
    3. Filters
    4. surface creation
  8. Shape Analyses
    1. Lines; length, azimuth, siusosity
    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 electormagnetic spectrum
    2. Spectral signatures
    3. what satellites mostly "see"
    4. Sensor Types
    5. Landsat
    6. LIDAR
  11. Image Processing
    1. Enhancement and Visualization
    2. Atmospheric Correction
    3. Ratios
    4. RGB images
    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 classificaiton
    6. using classification
  13. GPS System
    1. The System
    2. Receivers and measurements
  14. Map Composition
    1. map composition