The course takes approximately 104 class hours. 
Formally, but usually it takes much more due to 
the field work. 
Bibliography: 
The basic bibliography is the same that in course 
III.1.2. The recent papers (published in the 
main Journals related with Remote Sensing, GIS 
and the specific subject, i.e., Ecology) are 
fundamental. 
III.1.4. Microwave Remote Sensing. 
  
It is an introductory graduate course on Microwave 
Remote Sensing with 56 hours for Theory and 48 
hours for Seminar and Practical Activities. 
The program is: 
I. Introduction. 
II. Microwave Interaction with Atmospheric 
Constituents. 
III. Passive Microwave Radiometry. 
IV. Radar Fundamentals and Scatterometers. 
V. Imaging Radar Systems. 
VI. Advanced Systems. 
VII. Analysis of Radar Imagery. 
It was taught for the first time in 1989, to 
prepare young people for the new microwave 
sensors aboard of satellites (i.e., ERS-1 from 
ESA, among others). Images of SEASAT and for 
SAR airborne sensors are used in the exercises. 
Bibliography: 
The references used in this course are listed 
under the next names: Ridenour Ed., 1965; Kerr 
Ed., 1965; Ulaby, Moore & Fung, 1981; Ulaby, Moore 
& Fung, 1982; Ulaby, Moore & Fung, 1983 and 
Colwell Ed., 1983. 
III.1.5. Digital Image Processing. 
It is an Interdisciplinary Graduate course with 40 
hours of Theory and 48 hours for Laboratory. 
‘The themes are: 
A. Theory 
I. Fundamental Concepts. 
Introduction. 
Digital Images. 
What is Image Processing? 
What is Classification? 
Mathematical Basis for Image Processing. 
Mathematical Basis for Classification. 
OU BON# 
II. Digital Image Processing. 
Fundamental Elements. 
Digitizing Images. 
The Gray Level Histogram. 
Contrast and Dynamic Range Indication. 
Spatial Filtering. 
Image Restoration. 
NN WN = 
222 
7. Spatial Registration. 
8. Geometrical Manipulation. 
9. Color Processing. 
III. Pattern Recognition & Classification. 
Image Segmentation. 
Multispectral Classification. 
Classification Training. 
Atmospheric Correction. 
Multispectral Ratios. 
Principal and Canonical Components. 
Vegetation Indexes. 
Spatial Information: Texture. 
Classification Algorithms. 
Post-classification Considerations. 
O00N0OURON# 
m" 
B. Laboratory 
I. Computer Practices. 
Digitization. 
Gray Level and Color Display. 
Algebra of Images. 
Enhancements. 
Extraction of Information. 
Classifications with Different Algorithms. 
Geographic Information Systems. 
Editing Images. 
Printing Images. 
v9 00-0 Uli» 00 IN 
II. Seminar on 
Applications. 
Digital Image Processing 
1. Natural Resources. 
2. Astronomy. 
3. Medicine. 
4. Urbanism. 
5. Environmental Impact. 
6. Agricuiture. 
7. Global Monitoring. 
8. Pollution. 
9 to 12. Free themes for student proposals. 
Bibliography: 
The suggested references for this course are. 
listed under the next authors: Schowengerdt, 1983; 
Castleman, 1979; Ruiz-Azuara, 1990; Ruiz-Azuara & 
Pizá, 1990; Colwell, 1983; Muller Ed., 1988; 
Baxes, 1984; Sabins, 1987; Ripple Ed., 1987 and 
article from the PE&RS, RSE and others Journals. 
This course was taught for the first time in 1990. 
It is offered from the Graduate Program on 
Physics. From 1991, our course was included also 
in the Geophysics Graduate Program sponsored 
by the Institute of Geophysics of the UNAM and 
for CCH (Colegio de Ciencias y 
Humanidades). This program pays the salary of one 
Assistant Professor. 
III.1.6 Sede Ensenada. 
The main Mexican Astronomic Observatory is located 
in San Pedro Martir, Baja California Norte. In 
Ensenada, Baja California Norte, the Institute of 
Astronomy of the UNAM has installations also. For 
the term August - December 1992, the Digital Image 
Processing Course for graduate level will be 
offered in the CICESE Research Center, located 
also in Ensenada. Then, some of the activities of 
the Interdisciplinary Laboratory (related with the 
project IN-303389) will start in the Ensenada Area 
(during the Research Stay of the author in 
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