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EEG 260 – GIS & Remote Sensing

David Harbor, 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
      • Map Overlays and Boolean Logic
      • Overlay Analysis
      • Feature Overlay
      • simplification
      • complexity of combinations
      • reclassification
      • types of combinations
      • 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

Fuzzy Logic: Fuzzy Sets, Conditional Inclusion and Bayes Theorem

  1. A “fuzzy” boundary
  2. Fuzzy Inclusion set using distance data
  3. Bayesian Probability Modeling
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