Kennel P., Tramon M., Barbier Nicolas, Vincent Grégoire. (2013). Canopy height model characteristics derived from airbone laser scanning and its effectiveness in discriminating various tropical moist forest types. International Journal of Remote Sensing, 34 (24), p. 8917-8935. ISSN 0143-1161.
Titre du document
Canopy height model characteristics derived from airbone laser scanning and its effectiveness in discriminating various tropical moist forest types
Kennel P., Tramon M., Barbier Nicolas, Vincent Grégoire
Source
International Journal of Remote Sensing, 2013,
34 (24), p. 8917-8935 ISSN 0143-1161
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 (64mx 64 m and 32mx 32 m). Simple height distribution statistics achieve at best 70% classification accuracy in our sample set comprising 120 sampling units of 64mx 64 m. Using w avelet-based features, this accuracy increases to 79% but drops by 10% with smaller sampling units (32mx 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.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020]
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Etudes, transformation, conservation du milieu naturel [082]
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Télédétection [126]
