Spectral separability of riparian forests from small and medium-sized rivers across a latitudinal gradient using multispectral imagery

Abstract

Spectral discrimination between riparian forests is a challenging issue due to the inherent complexity of species composition and the high spatial structural variability of these vegetation types. This study aimed to evaluate spectral separability among riparian forests, in small and medium-sized river catchment areas, in three bioclimatic zones of Portugal (temperate, transitional, and Mediterranean). We also assess the spectral differences using only the dominant riparian woody species in each riparian forest class, namely Alnus glutinosa, Salix salviifolia, and Nerium oleander.

Pixel values were extracted from high-resolution airborne multispectral imagery (red, green, blue, and near-infrared, 50 cm pixels) of 26 riparian forests located in the three bioclimatic zones. Spectral separability was calculated using the transformed divergence (TD) distance. Discriminant analysis (DA) was used to select the bands that contribute most to the spectral separability and for the classification accuracy assessment of the riparian forests. Species composition and percentage of canopy closure were collected for all the riparian forests in a field campaign and subjected to hierarchical clustering in order to validate the spectral separability analyses. Optical traits derived from field data were used to interpret the spectral differences between riparian forest classes.

The greatest spectral separability was observed between the temperate and the Mediterranean riparian forest classes. Global classification accuracy for the DA was 86.3% for riparian forest classes along medium-sized rivers and 70.1% in small-sized ones. The high floristic and spatial structure variability was responsible for the misclassification errors that occurred between the transitional and the other riparian forest classes. The spectral separability using only the dominant species was greater than that obtained using the overall species assemblages of the riparian forests. Alnus glutinosa had the highest level of classification accuracy, and this may be related to its peculiar yellowish-green tone. DA also revealed that all spectral bands were needed in order to distinguish the riparian forest classes.

This study provided evidence that the spectral discrimination of riparian forests can be explained on the basis of differences in species composition and cover, and by a convergence of optical traits, at both leaf and canopy levels. Spectral signatures of these riparian forests and related spectral signatures of key species are useful tools for evaluating the floristic deviations of actual riparian forests from their near-natural benchmarks.

Acknowledgements

This study received backing from EU funds (ERDF) from the project RICOVER River Recovery in SW Europe (Interreg IVB-SOE1/P2/P248) and from the Forest Research Centre (CEF) through FEDER/POCI 2010. Maria R. Fernandes and Francisca C. Aguiar were supported by doctoral and postdoctoral scholarships from the Foundation for Science and Technology, Portugal, SFRH/BD/44707/2008 and SFRH/BPD/29333/2006, respectively. We acknowledge the assistance of Instituto Geográfico Português (IGP), which provided the airborne multispectral images through the FIGEE programme, and of the National Water Institute (INAG IP), which made the floristic data available to us.