Semester Offering: January

The course aims at providing RS/GIS image analysis tool through pre and post processing on satellite images. There will be special emphasis on images registration, extraction, classification and accuracy assessment. Students will be trained to develop a case study project at last.


Image Registration, Image Classification, Image Understanding, Accuracy Assessment and Cartographic Design.


AT7609 (Digital Image Processing in Remote Sensing) or permission from instructor.


I.      Introduction
1.        ERDAS and its component
2.        IMAGINE capability
3.        IMAGINE Quick Look

II.     Image Preparation
1.        Data Type
2.        Image Enhancement
3.        Image Rectification
III.  Image Processing
1.        Single Orthorectification
2.        Mosaic
3.        Subset
IV.  Image Processing
1.        Unsupervised Classification
2.        Supervised Classification
3.        Post Classification
V.    Accuracy Assessment
1.        Statistical Consideration
VI.   3D Surface Model
1.      Virtual GIS
2.      Scene Component
3.      Raster TIN into ERDAS
VII. Project
1.        Case study presentation


Lecture Notes


Gustavo Camps – Valls and Professor Lorenzo Brizzpme:
        Dernel Methods for Remote Sensing Data Analysis, 2009.

John A. Richards and Xiuping Jia:
        Remote Sensing Digital Image Analysis, 2005

Andrew S. Milman:
        Mathematical Principles of Remote Sensing: Making Inferences from Noisy Data, 2007

Jian-Guo Liu and Philippa Mason:
        Essential Image Processing and GIS for Remote Sensing, 2009.


ISPRS Journal


The final grade will be computed according to the following weight distribution: 

Lab assignment 60%
Case study project 40%.