Research Papers

Evaluating airborne hyperspectral imagery for mapping waterhyacinth infestations

[+] Author Affiliations
Chenghai Yang, James H. Everitt

USDA-ARS

J. Appl. Remote Sens. 1(1), 013546 (November 15, 2007). doi:10.1117/1.2821827
History: Received August 27, 2007; Revised November 9, 2007; Accepted November 9, 2007; November 15, 2007; Online November 15, 2007
Text Size: A A A

Abstract

Waterhyacinth [Eichhornia crassipes (Mart.) Solms] is an exotic aquatic weed that often invades and clogs waterways in many tropical and subtropical regions of the world. The objective of this study was to evaluate airborne hyperspectral imagery and different image classification techniques for mapping waterhyacinth infestations on Lake Corpus Christi in south Texas. Hyperspectral imagery with bands in the visible to near-infrared region of the spectrum was acquired from two study sites and minimum noise fraction (MNF) transformation was used to reduce the spectral dimensionality of the imagery. Four classification methods, including minimum distance, Mahalanobis distance, maximum likelihood, and spectral angle mapper (SAM), were applied to the MNF-transformed imagery for distinguishing waterhyacinth from associated plant species (waterlettuce, mixed herbaceous species, and mixed woody species) and other cover types (bare soil and water). Accuracy assessment showed that overall accuracy varied from 79% for SAM to 96% for maximum likelihood for site 1 and from 84% for minimum distance to 95% for maximum likelihood for site 2. Kappa analysis showed that maximum likelihood was significantly better than the other three methods and that there were no significant differences in overall classifications among the other three methods. Producer's and user's accuracies for waterhyacinth based on maximum likelihood were 94% and 100%, respectively, for site 1 and 100% and 95% for site 2. These results indicate that airborne hyperspectral imagery incorporated with image transformation and classification techniques can be a useful tool for mapping waterhyacinth infestations.

© 2007 Society of Photo-Optical Instrumentation Engineers

Citation

Chenghai Yang and James H. Everitt
"Evaluating airborne hyperspectral imagery for mapping waterhyacinth infestations", J. Appl. Remote Sens. 1(1), 013546 (November 15, 2007). ; http://dx.doi.org/10.1117/1.2821827


Figures

Tables

Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Adaptive Nonlocal Sparse Representation for Dual-Camera Compressive Hyperspectral Imaging. IEEE Trans Pattern Anal Mach Intell Published online Oct 25, 2016;
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.