Course Description:
Concepts of remote sensing including an introduction to radiation, remote
sensing instrumentation including multispectral and hyperspectral sensors,
earth resource satellites, and image interpretation and processing.
Applications of specific projects in biology, chemistry, civil engineering,
electrical engineering, forestry, geophysics, and physics will
be presented.
Students registered for PH3600 should also register for
UN4000.
Prerequisite: junior standing in above mentioned departments; or permission
of instructor.
This course is a prerequisite for
FW5560.
Discontinued effective Fall, 2004. Replaced by FW4540.
Text (Fall, 2003):
Typical Syllabus
| Topic | No. Of Classes | Chapter |
|---|---|---|
| History and Scope | 3 | 1 |
| Electromagnetic Radiation | 3 | 2 |
| Photographic Sensors | 3 | 3 |
| Digital Data | 3 | 4 |
| Image Interpretation | 3 | 5 |
| Land Observation Satellites | 3 | 6, Excer. 1 |
| Active Microwave Techniques | 3 | 7, Excer. 2 |
| Use of Thermal Radiation | 3 | 8, Excer. 3 |
| Image Resolution | 3 | 9, Excer. 4 |
| Hyperspectral Remote Sensing | 3 | 14 |
Typical Exercise Descriptions:
The four exercises below will develop a working familiarity with the major software packages utilized in diverse remote sensing disciplines, as well as in various discipline-specific image processing and data analysis techniques. Each exercise will be introduced in a class period; the exercise will be completed as a homework assignment due one week later.
Exercise 1: Exercise 1. Colordraping of Landsat Thematic Mapper (TM) imagery with digital elevation model (DEM) using ER Mapper. The term colordraping refers to the technique of draping one set of image data in color over another set of data. This allows the analyst to effectively view two or more different types of data in combined display. The technique is very useful for a wide range of processing applications. For example, draping TM imagery over a DEM illustrates the elevation's impact on the location of different types of vegetation. (Dr. Ann Maclean/class meets at School of Forestry).
Exercise 2: SAR Processing using ENVI. ENVI (Environment for Visualizing Images) is an image processing software package built on the widely used IDL software. It has a graphical user interface, and is functionally similar to ERDAS and ER Mapper (with perhaps fewer GIS capabilities), and includes specialized hyperspectral processing tools. (Dr. Drew Pilant/class meets at LARS lab).
This exercise will entail analysis of a SAT (Synthetic Aperture Radar) image of the Keweenaw Peninsula and surrounding ice and water. SAR is significantly different from optical or thermal data, and we will explore how these differences manifest in the appearance of a broad morphological and taxonomical range surface feature.
Exercise 3: Lake surface temperature mapping with AVHRR imagery. Using ERDAS Imagine, a color map will be generated showing surface temperatures for Lake Superior. Contouring vs. chloropleth mapping will be compared and contrasted for information content. A discussion on the use of color in mapping will be included. (Dr. Ann Maclean/class meets at School of Forestry).
Exercise 4: Volcanic cloud imaging and analysis. The
particles and gases which are lofted into the atmosphere
from volcanic eruptions produce distinctive spectral
signatures both in the infrared and the ultraviolet,
allowing researchers to discriminate and track clouds suing
satellite instruments. Recent work at Michigan Tech has
developed models to merge spatially, spectrally and
temporarily diverse datasets in order to gain better
understanding of volcanic clouds a potential hazard to
aircraft navigation. Here we will apply our new ENVI skills
to study the transport and fate of volcanic clouds as they
drift through and interact with the atmosphere. (Dr. Greg
Bluth/class meets in Geological Engineering and Sciences).
Course Rationale:
Introduction to Remote Sensing is the gateway pre-requisite course
for all additional courses in the Remote Sensing Minor, and
also serves as a stand-alone introductory treatment for students
interested in familiarizingt themselves with the fundamentals
of remote sensing. Topics which are covered are largely
discipline independent. The course also includes four computational
mini-projects, in which students utilize
IDL/ENVI, ER Mapper, and ERDAS Imagine to view and analyse
satellite remote sensing data. Students are also introduced to basic
imate handling and network utilization skills via exposure to the
remote sensing software packages mentioned above.