Overview

Description

CALENDAR DESCRIPTION:

Advanced remote sensing principles and techniques, including physics-based modeling, advanced classifiers, automated data processing, and integration of ancillary data products. Quantitative.

COURSE DETAILS:

Course Description:
Advanced remote sensing principles and techniques, including physics-based modeling, advanced classifiers, automated data processing, and integration of ancillary data products.

Course Content:
The course expands on the physical principles of remote sensing and introduces more advanced remote sensing methods used in current studies of earth surface processes. The focus will be on the extraction of quantitative information leading to the creation of scientific remote sensing solutions and products. Topics will include the general areas of: Digital image pre-processing and analysis, terrain analysis, spatial filtering, automated classification, thermal imaging, LIDAR imaging, and accuracy assessment. Images from various satellite sensors will be used.

Course Organization:
There will be one 2-hrs lecture per week. Students will learn about and practice advanced remote sensing techniques through formal lectures, computer labs, individual assignments, and analysis of public data. Data analysis software will be used to explore real world data from multiple sources. There will be a strong emphasis on problem-based and interactive learning. The textbook readings will enhance and extend understanding of the materials presented in the class lectures, and facilitate more meaningful participation during the classroom discussions.

There will be one 2-hrs lab session per week. The guided computer lab sessions will use sample and full data sets and software analysis to reinforce the theoretical concepts and methods presented in the class lectures. These labs will allow students to apply the remote sensing methods to a variety of data and problem contexts within geography and the environmental sciences. The software is available in the SIS lab (Win7 networked).

Lectures, Labs and Office Hours begin in the first week of the term.

Notes:
This course may be applied towards the SIS Certificate Program.
The contents are subject to minor changes depending on the number of students and available resources.

COURSE-LEVEL EDUCATIONAL GOALS:

On successful completion of this course, students should be able to:
* Develop a stronger understanding of the physical principles of satellite remote sensing
* Evaluate remote sensing methods in the context of real world applications
* Automate selected tasks in remote sensing image processing
* Demonstrate competence in using software tools for image analysis
* Creatively design and implement quantitative analysis projects for problem solving

Grading

Materials

RECOMMENDED READING: