DocumentCode
826889
Title
On the use of prior and posterior information in the subpixel proportion problem
Author
Kolaczyk, Eric D.
Author_Institution
Dept. of Math. & Stat., Boston Univ., MA, USA
Volume
41
Issue
11
fYear
2003
Firstpage
2687
Lastpage
2691
Abstract
Although the problems of classification and subpixel proportion estimation in remote sensing land cover characterization generally are held to be distinct (though related), often elements of the former are adopted in addressing the latter that blur this distinction - particularly, regarding the use of prior and posterior information. The author examines this issue in more detail, using simple, canonical versions of the two problems and, in the course of this examination, provides analytical expressions upon which to build discussion of improvements to subpixel proportion estimation from a statistical viewpoint.
Keywords
Bayes methods; image classification; vegetation mapping; Bayesian estimation; land cover classification; posterior information; prior information; remote sensing; statistical approach; subpixel proportion estimation; subpixel proportion problem; Ecosystems; Image processing; Interpolation; Mathematics; Monitoring; Pixel; Predictive models; Remote sensing; Satellites; Statistics;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing, IEEE Transactions on
Publisher
ieee
ISSN
0196-2892
Type
jour
DOI
10.1109/TGRS.2003.817194
Filename
1245258
Link To Document