Return to the Remote Sensing Core Curriculum Home Page

Presented by
The International Center for Remote Sensing Education (ICRSEd)
Introduction to Photo Interpretation and Photogrammetry Overview of Remote Sensing of the Environment You are here! Applications in Remote Sensing K - 12 Education Links to Educational Resources Satellite Imagery Available on the Internet About the International Center for Remote Sensing E-mail the ICRSEd or the Webmaster

Table of Contents

Module 1 Introduction to Digital Image Processing of Remotely Sensed Data (Jensen, Eastman, Faust)

Module 2 Digital Image Data Collection (Jensen and Faust)
2.1 Analog (Hard-Copy) Image Digitization
2.2 Remotely Sensed Data Already In Digital Format
2.3 Digital Image Data Formats
2.4 Image Compression Alternatives and Media Storage Considerations

Module 3 Image Processing System Considerations (Jensen and Ramsey)
3.1 Digital Image Processing Hardware And Software Functions
3.2 Commercial And Publicly Available Digital Image Processing Systems
3.3 The National Spatial Data Infrastructure And Image Processing On The Internet

Module 4 Digital Scientific Visualization (Eastman and Faust)
4.1 Extracting Univariate and Multivariate Image Statistics
4.2 Scientific Visualization
-Black & White Hard-Copy Image Display
-Temporary Video Black & White And Color Image Display
-Three-Dimensional GIS
-Merging Different Types Of Remotely Sensed Data

Module 5 Image Preprocessing: Radiometric and Geometric Correction (Stow and Ramsey)
5.1 Radiometric Correction of Remotely Sensed Data
5.2 Geometric Correction of Remotely Sensed Data

Module 6 Image Enhancement (Faust, Jensen, Price)
6.1 Image Reduction and Magnification
6.2 Transects
6.3 Contrast Enhancement
6.4 Spatial Filtering to Enhance Low and High Frequency Detail and Edges
6.5 Special Transformations
-Band Ratioing, Principal Components Analysis, Vegetation Indices, and Texture Transformations

Module 7 Thematic Information Extraction Image Classification (Congalton, Eastman, Hodgson, Jensen, Ramsey)
 7.1 Supervised Classification
-Feature Selection
-Supervised Classification Algorithms
7.2 Unsupervised Classification
7.3 Knowledge-Based and Fuzzy Classification
7.4 Incorporating Ancillary Data In The Classification Process
7.5 Landuse Classification Map Accuracy Assessment
7.6 Lineage (Genealogy) Of Maps And Databases Derived From Digital Image Processing
Module 8 Digital Change Detection (Jensen and Eastman)
8.1 General Steps Required To Perform Change Detection
8.2 Major Change Detection Algorithms
Module 9 Interface of Remote Sensing and Geographic Information Systems (Ken McGwire)
 9.1 Introduction
9.2 Representation and Data Models
9.3 GIS Input and Update
9.4 Image Correction
9.5 Integrated Analysis
9.6 Integrated Computing Environments
9.7 Bibliography
9.8 Applications
-University of Nebraska National/Global Land Cover Application
EDC DAAC Global Land Cover Characterization
-Kansas/Kansas State University Agricultural Application
The Green Report
-University of Idaho/Utah State University Biodiversity Applications
Gap Analysis
Mojave Desert Ecosystem Initiative
Module 10 The Future of Digital Image Processing (Jensen and Faust)
10.1 Expert Systems
10.2 Parallel Processing
10.3 Neural Networks
John R Jensen, Ph.D.
Department of Geography
University of South Carolina
Columbia, South Carolina 29208

Direct Comments regarding Volume 3 to: jrjensen@sc.edu