Abstract
A radiometric normalization technique for compensating illumination and atmospheric differences between multi-temporal images should allow classification of the images with a single classification algorithm. This allows a simpler approach to land cover change detection. Land cover classification of Landsat Thematic Mapper Imagery with and without Pseudo Invariant Feature Normalization was performed to demonstrate the effect on classification and change detection accuracy. A post-classification change detection method using two separate classification algorithms, one for each date, was performed as a baseline comparison. Land cover classification using one classification algorithm was attempted with and without gain and offset correction to serve as another comparison. Accuracy verification was performed on the classification results by comparing random samples against ground truth.
Library of Congress Subject Headings
Landsat satellites; Artificial satellites in remote sensing; Remote sensing--Mathematics; Electromagnetic waves
Publication Date
9-1-1987
Document Type
Thesis
Department, Program, or Center
Chester F. Carlson Center for Imaging Science (COS)
Advisor
Schott, John
Advisor/Committee Member
Granger, Edward
Recommended Citation
Hawes, Tim, "Land cover classification of landsat thematic mapper images using pseudo invariant feature normalization applied to change detection" (1987). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/2821
Campus
RIT – Main Campus
Comments
Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in December 2013.
Physical copy available from RIT's Wallace Library at G70.4 .H387 1987