Skip to main content
padlock icon - secure page this page is secure

Canopy height model characteristics derived from airbone laser scanning and its effectiveness in discriminating various tropical moist forest types

Buy Article:

$60.00 + tax (Refund Policy)

Mapping tropical forests to a sufficient level of spatial resolution and structural detail is a prerequisite for their rational management, which however remains a largely unmet challenge. We explore the degree to which a forest canopy height model (CHM) derived from airborne laser scanning (ALS) can discriminate between five forest types of similar height but varying structure or composition. We systematically compare various textural features (Haralick, Fourier transform-based, and wavelet-based features) and various classification procedures (linear discriminant analysis (LDA), random forest(RF), and support vector machine (SVM)) applied to two sizes of sampling units (64 m ×  64 m and 32 m ×  32 m). Simple height distribution statistics achieve at best 70% classification accuracy in our sample set comprising 120 sampling units of 64 m ×  64 m. Using w avelet-based features, this accuracy increases to 79% but drops by 10% with smaller sampling units (32 m ×  32 m). Classifier performance depends on the texture feature set used, but SVM and RF tend to perform better than LDA. High discrimination rates between forests types of similar height indicate that the ALS-derived CHM provides information suitable for mapping of tropical forest types. Wavelet-based texture features coupled with a SVM classifier was found to be the most promising combination of methods. Ancillary data derived from laser scans and notably topography could be used jointly for an improved segmentation scheme.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Affiliations: 1: Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM), UMR 5506–CC 477, 34095, Montpellier Cedex 5, France 2: Institut de Recherche pour le Développement (IRD), UMR AMAP, 34398, Montpellier Cedex 5, France

Publication date: December 20, 2013

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more