NASA-CW Project

NRS516: Advanced Remote Sensing

Overview

This course will focus on quantitative approaches to the analysis of satellite remote sensing data. Digital multitemporal, multispectral, multisensor remote sensing image, and the application of digital remote sensing in environmental and natural resource studies will be the main focus. Quantitative methods in digital remote sensing image rectification, georeference, enhancement, classification, thematic information extraction, integration of remote sensing with geographic information systems (GIS) will be addressed.

Textbook

Jensen, J.R., 1996. Introductory Digital Image Processing: A remote sensing perspective, 2nd Edition. Prentice Hall, New Jersey. ISBN: 0-13-205840-5.

ERDAS, 1997. ERDAS Field Guide, 4th Ed. ERDAS Inc. Atlanta, GA.

ERDAS, 1997. ERDAS Tour Guide, 4th Ed. ERDAS Inc. Atlanta, GA.

Other References

Campbell, J.B., 1996. Introduction to Remote Sensing, 2nd Edition. The Guilford Press, New York, ISBN: 1-57230-041-8.

Sabins, F.F., 1997. Remote Sensing: principles and interpretation, 3rd Edition. W.H. Freeman and Company, New York, ISBN: 0-7167-2442-1.

Course Grading

Laboratory exercise 40%;
Midterm 20%;
Final Exam 20%;
Project: 20%.

Comments about the Laboratory Exercise and Course Project

This course is structured to provide both theory and principles of digital remote sensing data analysis, and to do so in hands on laboratory environment. Series of Laboratory exercises will be arranged so that the students will be equipped with both knowledge and skills in digital remote sensing image analysis and problem solving. ERDAS Imagine software system will be used in the laboratory exercises. By the end of the semester, each student is required to complete a small project in land-cover mapping. The project is to enhance the knowledge and skill of the students in digital remote sensing applications.

Prerequisite: NRS415, or permission of instructor.

Course Outline

Week 1: History and development of remote sensing, EM Radiation
Spectral reflectance and concepts of multispectral remote sensing
Week 2: Characteristics and statistics of digital remote sensing imagery
Lab topic: digital image visualization; image import/export
Week 3: Digital remote sensing image processing
Lab topic: spatial image enhancement; spectral image
Week 4: Geometric rectification of satellite remote sensing images
Lab topic: image to image rectification
Week 5: Image classification and pattern recognition
Lab topic: unsupervised and supervised classification
Week 6: Classification accuracy and ground truthing
Lab topic: accuracy assessment
Week 7: Multitemporal and multisensor image analysis
Lab topic: Geo-referencing
Week 8: Mid. Term Examine
Land-cover mapping;
Lab topic: mosaics of digital images
Week 9: Spring Break
Week 10: Remote sensing and image mapping
Lab topic: map composer
Week 11: Remote sensing and land-cover change detection
Lab topic: detection of land-cover change
Week 12: Remote sensing and GIS; multisource data analysis
Lab topic: vector data display; GIS operations
Week 13: Digital remote sensing in earth science applications
Lab topic: remote sensing on the web (interested web sites)
Week 14-15: Land-cover mapping project
Week 16: Project Presentation, Semester Review

Please forward questions to yqwang@uri.edu.

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