By Topic

Operational Two-Stage Stratified Topographic Correction of Spaceborne Multispectral Imagery Employing an Automatic Spectral-Rule-Based Decision-Tree Preliminary Classifier

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Baraldi, A. ; Eur. Comm. Joint Res. Centre, Ispra, Italy ; Gironda, M. ; Simonetti, D.

The increasing amount of remote sensing (RS) imagery acquired from multiple platforms and the recent announcements that scientists and decision makers around the world will soon have unrestricted access at no charge to large-scale spaceborne multispectral (MS) image databases make urgent the need to develop easy-to-use, effective, efficient, robust, and scalable satellite-based measurement systems. In these scientific and industrial contexts, it is well known that, to date, the operational performance of existing stratified non-Lambertian (anisotropic) topographic correction (SNLTOC) algorithms has been limited by the need for a priori knowledge of structural landscape characteristics, such as surface roughness which is land cover class specific. In practice, to overcome the circular nature of the SNLTOC problem, a mutually exclusive and totally exhaustive land cover classification map of a spaceborne MS image is required before SNLTOC takes place. This system requirement is fulfilled by the original operational automatic two-stage SNLTOC approach presented in this paper which comprises, in cascade, 1) an automatic stratification first stage and 2) a second-stage ordinary SNLTOC method selected from the literature. The former combines 1) four subsymbolic digital-elevation-model-derived strata, namely, horizontal areas, self-shadows, and sunlit slopes either facing the sun or facing away from the sun, and 2) symbolic (semantic) strata generated from the input MS image by an operational fully automated spectral-rule-based decision-tree preliminary classifier recently presented in RS literature. In this paper, first, previous works related to the TOC subject are surveyed, and next, the novel operational two-stage SNLTOC system is presented. Finally, the original two-stage SNLTOC system is validated in up to 19 experiments where the system's capability of reducing within-stratum spectral variance while preserving pixel-based spectral patterns (shapes) is - - assessed quantitatively.

Published in:

Geoscience and Remote Sensing, IEEE Transactions on  (Volume:48 ,  Issue: 1 )