In-track multi-angle model portability of multispectral land-cover classification using very high spatial resolution data

Nathan Longbotham; Fabio Pacifici; William Emery

doi:10.1117/12.919581

24 May 2012 In-track multi-angle model portability of multispectral land-cover classification using very high spatial resolution data

Nathan Longbotham, Fabio Pacifici, William Emery

Author Affiliations +

Proceedings Volume 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII; 83901V (2012) https://doi.org/10.1117/12.919581
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

In this paper, we present a method to analyze the impact of data space normalization on spectral classification model portability using multi-angle very-high spatial resolution imagery. In-track multi-angle data provide images of a single scene, from different observation angles, during a very short period of time. This creates a sequence of images with relatively static atmospheric and illumination conditions. With this data, the only changes in the scene are due to observation angle and surface reflectance properties. Using this information, we present an analysis of both the impact of surface anisotropy and data space normalization on spectral classification accuracy and model portability.

Citation Download Citation

Nathan Longbotham, Fabio Pacifici, and William Emery "In-track multi-angle model portability of multispectral land-cover classification using very high spatial resolution data", Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83901V (24 May 2012); https://doi.org/10.1117/12.919581

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available