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Research Articles

Deciduous forest mapping using change detection of multi-temporal canopy height models from aerial images acquired at leaf-on and leaf-off conditions

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Pages 517-525 | Received 27 Apr 2015, Accepted 07 Dec 2015, Published online: 08 Feb 2016
 

ABSTRACT

Discrimination of deciduous trees using spectral information from aerial images has only been partly successfully due to the complexity of the reflectance at different view angles, times of acquisition, phenology of the trees and inter-tree radiance. Therefore, the objective was to evaluate the accuracy of estimating the proportion of deciduous stem volume (P) utilizing change detection between canopy height models (CHMs) generated by digital photogrammetry from leaf-on and leaf-off aerial images instead of using spectral information. The study was conducted at a hemi-boreal study area in Sweden. Using aerial images from three seasons, CHMs with a resolution of approximately 0.5 m were generated using semi-global matching. For training plots, metrics describing the change between leaf-on and leaf-off conditions were calculated and used to model the continuous variable P, using the Random Forest approach. Validated at sub-stands, the estimation accuracy of P in terms of root mean square error and bias was found to be 18% and −6%, respectively. The overall classification accuracy, using four equally wide classes, was 83% with a kappa value of 0.68. The validation plots in classes of high proportion of coniferous or deciduous stem volume were well classified, whereas the mixed forest classes showed lower classification accuracies.

Acknowledgements

The authors are grateful to the Hildur and Sven Wingquist's foundation for forest research, which has financed the Remningstorp field data surveys. Special gratitude is directed to Lantmäteriet, which provided the DMC data and gave support. The authors are also grateful to the developers of R (R Core Team Citation2013), a free software environment for statistical computing and graphics, which was used for the statistical analyses. This work was financially supported by the Kempe Foundations and the Forestry Society's Estate Management Company (Skogssällskapet). Finally, the authors would like to thank the reviewers for their comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

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