GEO-SCI594Q Advanced Remote Sensing

3 cr, Spring 2007

 

Course Location:              Morrill IV South 271

Lecture Time:                    Tu 2:30PM - 5:15PM

Instructor:                           Dr. Qian Yu

Office:                                  Morrill IV South 267

Office Telephone:           413-545-2095

EMAIL:                                qyu@geo.umass.edu

Office Hours:                    M 2:30-3:30pm   W 1:30-2:30pm or by appointment

Purpose: To introduce the principles of image analysis for interpreting remotely sensed data for environmental, resource and urban studies.  Emphasis will be given to the processing and information extraction from optical and thermal imagery.

Format: 60% lectures and class discussions, 40% seminars and class exercises.  Take home exercises and lab practice will be assigned to students to get familiar with the concepts discussed in class.

Textbook:

Available in Textbook Annex

John R. Jensen, 2004.  Introductory Digital Image Processing, 3rd Edition, Prentice Hall, New Jersey. (Available through ASPRS as a member for $78)

John A. Richards and Xiuping Jia, Remote Sensing Digital Image Analysis, Springer, 2006

Gong, Peng, Remote Sensing and Image Analysis, http://www.cnr.berkeley.edu/~gong/textbook/

Course Evaluation: (tentative) Assignment 35%, Class Participation and one seminar 20%, Project 45%

Lab software: ERDAS IMAGINE 9.1

Topic: (tentative)

Topic

Reading

Jan 30

Lecture 1. 

 

Concepts in remote sensing

- platform, sensors,

Characteristics of digital Image data

- resolutions, processing flow

Remote sensing systems

Jensen's ch1. ch2

Feb 6

Lecture 2.

 

Image statistics

- Histogram

- Univariate descriptive image statistics

- Multivariate Image Statistics

- Geostatistical analysis

Jensen's ch4

Feb 13

Lecture 3. 

Radiometric correction

Atmospheric energy matter interactions
Terrain energy matter interactions
Path radiance
Correct remote sensing system detector error
Atmospheric correction
- Absolute atmospheric correction using empirical line calibration
- Relative radiometric correction of atmospheric attenuation
Topographic correction

Jensen's ch6

 

Assignment and lab 1

Due on Mar 6 before class

Feb 20

 

Feb 27

Lecture 4. 

Image geometric processing

Internal and external geometric error

Ground Control Points

Coordinates transform

Resample

Mosaicking

Jensen's ch7

 

Assignment and lab 2

Due on Mar 20 before class

Mar 6

Lecture 5. 

Image display and enhancement

-Radiometric enhancement

Histogram based operations

-Spatial , image filtering

-Multispectral enhancement

IHS transform, principal component analysis,

- Vegetation indices

K-T transform

Jensen's ch5 p157-172

ch8

 

Mar 13

 

Mar 27

Apr 3

Lecture 6. 

Classification

Supervised and unsupervised classification techniques.  Training and testing sample selection, accuracy assessment methods.

K-NN,  image segmentation, Object-based image classification

unmixing

 

Jensen's ch9

Apr 10

Lecture 7. 

Jensen's ch11

Apr 16

Holiday, Monday schedule, no class

  

Apr 23

Lecture 8. 

Case study1:  Guest speaker Prof. Charlie Schweik.

                  Remote sensing in conservation study

Case study2: Hyperspectral remote sensing for biophysical parameter extraction

 Jensen's ch 12
May 1 Case study3: Hyperspectral remote sensing for CDOM estimation  
May 8 Final project  
May 15 Final presentation  
May 24 Project report due