Research Papers

Wavelet-based texture measures for semicontinuous stand density estimation from very high resolution optical imagery

[+] Author Affiliations
Frieke M. B. Van Coillie

Ghent University, Laboratory of Forest Management and Spatial Information Techniques (FORSIT), Coupure Links 653, 9000 Gent, Belgium, frieke.vancoillie@ugent.be; robert.dewulf@ugent.be

Lieven P. C. Verbeke

Ghent University, Department of Information Technology (INTEC), Gaston Crommelaan 8 bus 201, 9050 Ledeberg - Gent, Belgium

Robert R. De Wulf

Ghent University, Laboratory of Forest Management and Spatial Information Techniques (FORSIT), Coupure Links 653, 9000 Gent, Belgium, frieke.vancoillie@ugent.be; robert.dewulf@ugent.be

J. Appl. Remote Sens. 5(1), 053560 (October 21, 2011). doi:10.1117/1.3653269
History: Received February 21, 2011; Revised September 02, 2011; Accepted September 28, 2011; Published October 21, 2011; Online October 21, 2011
Text Size: A A A

Stand density, expressed as the number of trees per unit area, is an important forest management parameter. It is used by foresters to evaluate regeneration, to assess the effect of forest management measures, or as an indicator variable for other stand parameters like age, basal area, and volume. In this work, a new density estimation procedure is proposed based on wavelet analysis of very high resolution optical imagery. Wavelet coefficients are related to reference densities on a per segment basis, using an artificial neural network. The method was evaluated on artificial imagery and two very high resolution datasets covering forests in Heverlee, Belgium and Les Beaux de Provence, France. Whenever possible, the method was compared with the well-known local maximum filter. Results show good correspondence between predicted and true stand densities. The average absolute error and the correlation between predicted and true density was 149 trees/ha and 0.91 for the artificial dataset, 100 trees/ha and 0.85 for the Heverlee site, and 49 trees/ha and 0.78 for the Les Beaux de Provence site. The local maximum filter consistently yielded lower accuracies, as it is essentially a tree localization tool, rather than a density estimator.

Figures in this Article
© 2011 Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation

Frieke M. B. Van Coillie ; Lieven P. C. Verbeke and Robert R. De Wulf
"Wavelet-based texture measures for semicontinuous stand density estimation from very high resolution optical imagery", J. Appl. Remote Sens. 5(1), 053560 (October 21, 2011). ; http://dx.doi.org/10.1117/1.3653269


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.