dents to some of the more recent and innovative approaches to remote sensing. A hands 
on component to this course is essential, as well, but a bit more difficult to standardize 
because of the often expensive and sometimes unavailable computer equipment and 
digital data required. However, there are low cost image analysis software systems that 
operate on vanilla flavored microcomputers that are very effective vehicles for such 
training. Also, industry (i.e., EOSAT, SPOT) might be encouraged to provide educational 
data sets that would be available to all instructors and students participating in such a 
course. These data could be representative of forestry, agricultural, rangeland, water re 
sources, geology or other situations and could be selectively incorporated into the 
course by the instructor to reflect the emphasis of the host department and correspond 
ing application discipline. 
Below is a suggested outline for a course in quantitative remote sensing: 
■ Review of EM Radiation 
■ Review of Spectral Reflectance Properties 
■ The Landsat Multispectral Scanner & Thematic Mapper 
■ The SPOT Panchromatic and Multispectral HRV Sensors 
■ Characteristics of Digital Remote Sensing Imagery 
■ Multispectral Image Display & Contrast Enhancement 
■ Elementary Statistics for Quantitative Remote Sensing 
• Elementary Linear Algebra for Quantitative Remote Sensing 
■ Overview of Correction and Enhancement of Digital Remote Sensing Data 
■ Geometric Correction of Digital Remote Sensing Data 
■ Pattern Recognition Principles 
■ Supervised Classification 
■ Training the Classifier 
• Parallelpiped, Euclidean Distance & Maximum Likelihood Classification 
■ Unsupervised Classification: Cluster Analysis 
■ Land Cover Mapping Accuracy Assessment 
• Alternative Approaches to Image Classification: Extraction and Classification of Ho 
mogeneous Objects, Layered Decision Tree, Knowledge-based Expert Systems 
• Radiometric Correction and Calibration of Remote Sensing Data 
■ Spatial Transformations: Image Filtering & Warping 
■ Spectral Transformations: Band Ratioing, Principal Components & Vegetation Indices 
■ Multitemporal Remote Sensing 
■ Land Cover Change Detection 
■ Generation of Image Products, Map Information, and Summary Data 
■ Integration and Utilization of Remote Sensing and GIS Data 
• Course Three: Case Studies in Remote Sensing 
This course, open only to those students who have completed the first two parts of the 
core curriculum, would draw upon real world examples of the application of remote 
sensing. It would cover a broad array of topics and applications. Its structure would be 
most flexible and in fact modular allowing for customization by individual instructors. The 
lecture materials, including slides and overheads, for this course could be elicited from 
selected speakers from professional society conventions such as the Spring and Fall 
meetings of the ASPRS/ACSM or various meetings of the ISPRS. Required readings 
would include the published papers from the proceedings of those conventions. 
The laboratory component of the course would be in the form of an independent study 
or practicum to be conducted by individual or groups of students. A semester-long 
project, or perhaps several of shorter duration, wouid involve the identification of a par 
ticular problem area, the formulation of objectives, the design of an experiment, the ac 
tual implementation of the work, and the presentation of the results. The core curriculum 
should suggest a number of possible project topics and guidelines for the actual work. 
Naturally, other courses could be developed or adapted for this core curriculum. These 
would be most likely be very technical and highly specialized, and might include topics such 
as (a) radiation physics for remote sensing, (b) remote sensing optics (c) remote sensing