Research Papers

Modified vegetation indices for Ganoderma disease detection in oil palm from field spectroradiometer data

[+] Author Affiliations
Helmi Z. M. Shafri

Geomatics Engineering Unit, Department of Civil Engineering, Universiti Putra Malaysia, Faculty of Engineering, Serdang, Selangor 43400 Malaysia

M. Izzuddin Anuar

Institute of Advanced Technology, Universiti Putra Malaysia, Serdang, Selangor 43400 Malaysia

M. Iqbal Saripan

Computer and Communication Systems Engineering Department, Universiti Putra Malaysia, Serdang, Selangor 43400 Malaysia

J. Appl. Remote Sens. 3(1), 033556 (October 12, 2009). doi:10.1117/1.3257626
History: Received February 12, 2009; Revised October 6, 2009; Accepted October 7, 2009; October 12, 2009; Online October 12, 2009
Text Size: A A A

Abstract

High resolution field spectroradiometers are important for spectral analysis and mobile inspection of vegetation disease. The biggest challenges in using this technology for automated vegetation disease detection are in spectral signatures pre-processing, band selection and generating reflectance indices to improve the ability of hyperspectral data for early detection of disease. In this paper, new indices for oil palm Ganoderma disease detection were generated using band ratio and different band combination techniques. Unsupervised clustering method was used to cluster the values of each class resultant from each index. The wellness of band combinations was assessed by using Optimum Index Factor (OIF) while cluster validation was executed using Average Silhouette Width (ASW). 11 modified reflectance indices were generated in this study and the indices were ranked according to the values of their ASW. These modified indices were also compared to several existing and new indices. The results showed that the combination of spectral values at 610.5nm and 738nm was the best for clustering the three classes of infection levels in the determination of the best spectral index for early detection of Ganoderma disease.

© 2009 Society of Photo-Optical Instrumentation Engineers

Citation

Helmi Z. M. Shafri ; M. Izzuddin Anuar and M. Iqbal Saripan
"Modified vegetation indices for Ganoderma disease detection in oil palm from field spectroradiometer data", J. Appl. Remote Sens. 3(1), 033556 (October 12, 2009). ; http://dx.doi.org/10.1117/1.3257626


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
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.