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EEG 316 – GIS & Remote Sensing

Washington and Lee University

  • All Course Notes
    • Introduction and Data Types
      • What is a GIS?
      • What does a GIS do?
      • Course Goals
      • GIS Components
      • 3 types of data
      • Selecting data types
      • Topology of vector datasets
    • Maps: Projections and Datums
      • Where did you say you were calling from?
      • Projections
      • Geoid and reference ellipsoids
      • A datum
      • UTM
    • Spatial Overlays and Querying
      • Overlay Analysis
      • Map Algebra
      • Feature Overlay
      • simplification
      • complexity of combinations
      • reclassification
      • types of combinations
      • Spatial Joins
      • Overlay Querying
    • Digital Terrain Analyses
      • Digital Topography Data
      • Digital Topography 2
      • Converting DTMs
      • Digital Terrain – slope
      • Digital Terrain – curvature
      • Digital Terrain – aspect
      • Digital Terrain – viewsheds
      • Digital Terrain – hillshade
      • Watershed Analyses
    • Modeling and Algorithms
      • Analysis Algorithms
    • Location-related calculations
      • buffers, distance, & proximity
      • rubber rulers
      • Friction and least-cost paths
      • Patch simplification and “clumping”
      • location and nearness…..
      • Density
    • Neighborhood Analyses
      • Filters
      • Creating surfaces by interpolation
    • Shape Analyses
      • Lines: length, azimuth, sinuosity
      • Distribution of points, lines, and polygons
      • Patch size, shape, connectivity
    • Fuzzy Logic: Fuzzy Sets, Conditional Inclusion and Bayes Theorem
      • A “fuzzy” boundary
      • Fuzzy Inclusion set using data
      • Bayesian Probability Modeling
    • Remote Sensing Data
      • The electromagnetic spectrum
      • Spectral signatures
      • Sensor Types
      • Landsat
      • LIDAR
    • Image Processing
      • Enhancement and Visualization
      • Illumination
      • Haze Correction
      • Ratios
      • decorrelation
      • Principal Component Analysis
      • Geolocating Images
    • Image Classification
      • General Principles
      • Simple Discriminants
      • Unsupervised Classification
      • Supervised Classification
      • using classification
    • GPS / GNSS (global positioning system / Global Navigation Satellite System)
      • The Satellite System
      • GPS receivers and signal corrections
      • Using GPS
    • Map Composition
      • Map Composition

Modeling and Algorithms

  1. modeling vs. analysis
  2. spatial modeling principles
  3. thinking through an analysis using an algorithm
  4. types of models
  5. multicriterion models
  6. testing models
  7. vocab
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