Identification of functionally distinct plants using linear spectral mixture analysis

Abstract

The quantification of functional variations in vegetation aids in understanding the response of ecosystems to the changing environment. The determination of variations in the plant functional traits of different plants can help in identifying functionally distinct plants or plant functional types. This chapter discusses the importance of plant functional traits (FTs) in ecosystem functioning. Further, it discusses the classification of species based on these FTs into plant functional types and the potential of hyperspectral data in determining these plant functional types or functionally distinct plants. Additionally, a case study carried out to map functionally distinct plants in the Shoolpaneshwar Wildlife Sanctuary using Earth observation data is discussed in this chapter. Hyperion data combined with spectral mixture analysis are used for mapping functionally distinct plants. Four different FTs of dominant plant species of the study area, namely Tectona grandis, Butea monosperma, and Bambusa bambos, were estimated, which showed the significant functional variability amongst these plants. Additionally, the canopy spectra of these plants were collected from Hyperion images with high-dimensional spectral information. Pixel purity index was used to derive the endmembers from the Hyperion data based on field data of pure patches of these species. Linear spectral mixture analysis was carried out using determined endmembers and a set of fractional abundance images for each functionally distinct plant was obtained. Higher fractions of T. grandis and B. bambos endmembers were observed in the study area compared to B. monosperma. The case study highlights the potential of hyperspectral data and spectral mixture analysis in adequately characterizing functionally distinct plants. © 2020 Elsevier Ltd All rights reserved.