Research Papers

Impact of discrete wavelet transform on discriminating airborne hyperspectral tropical rainforest tree species

[+] Author Affiliations
Azadeh Ghiyamat

Universiti Putra Malaysia (UPM), Institute of Gerontology, 43400 Selangor, Malaysia

Helmi Zulhaidi Mohd Shafri

Universiti Putra Malaysia (UPM), Department of Civil Engineering, Faculty of Engineering, 43400 Selangor, Malaysia

Universiti Putra Malaysia (UPM), Geospatial Information Science Research Centre (GISRC), Faculty of Engineering, 43400 Selangor, Malaysia

Ghafour Amouzad Mahdiraji

University of Malaya, Department of Electrical Engineering, 50603 Kuala Lumpur, Malaysia

Ravshan Ashurov

National University of Uzbekistan, Institute of Mathematics, 100095 Tashkent, Uzbekistan

Abdul Rashid Mohamed Shariff

Universiti Putra Malaysia (UPM), Geospatial Information Science Research Centre (GISRC), Faculty of Engineering, 43400 Selangor, Malaysia

Shattri Mansor

Universiti Putra Malaysia (UPM), Department of Civil Engineering, Faculty of Engineering, 43400 Selangor, Malaysia

J. Appl. Remote Sens. 8(1), 083556 (Sep 03, 2014). doi:10.1117/1.JRS.8.083556
History: Received February 7, 2014; Revised July 15, 2014; Accepted August 5, 2014
Text Size: A A A

Abstract.  Discriminating tropical rainforest tree species is still a challenging task due to a variety of species with high spectral similarity and due to very limited studies conducted in this area. We are investigating the effect of discrete wavelet transform (DWT) on enhancing discrimination of tropical rainforest tree species. For this purpose, airborne imaging spectrometer for applications (AISA) airborne hyperspectral data obtained from Malaysian’s rainforest area are used; six tree species were selected from the study area. For comparison purposes, the performance of DWT is compared with the original reflectance, first, and second derivative spectra by using five different spectral measure techniques. An overall discrimination accuracy of 74% is obtained with DWT using Euclidean distance, which outperforms the original reflectance and first and second derivatives by 16.6, 11.9, and 22.1%, respectively. The results suggest a significant impact of the DWT approach on improving tropical rainforest tree species discrimination.

© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Azadeh Ghiyamat ; Helmi Zulhaidi Mohd Shafri ; Ghafour Amouzad Mahdiraji ; Ravshan Ashurov ; Abdul Rashid Mohamed Shariff, et al.
"Impact of discrete wavelet transform on discriminating airborne hyperspectral tropical rainforest tree species", J. Appl. Remote Sens. 8(1), 083556 (Sep 03, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083556


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

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.