Effects of Pixel Resolution, Mapping Window Size, and Spectral Species Classification on Remote Sensing of Plant Beta Diversity Using biodivMapR and Hyperspectral Imagery

Abstract

Using imaging spectroscopy (hyperspectral imaging), we sought to assess the effects of image pixel resolution, size of mapping windows composed of pixels, and number of spectral species assigned to pixels on the capacity to map plant beta diversity using the biodivMapR algorithm, in support of the planned NASA Surface Biology and Geology (SBG) satellite remote sensing mission. BiodivMapR classifies pixels as spectral species, then calculates beta diversity as dissimilarity of spectral species among mapping windows each composed of multiple pixels. We used NEON airborne 1 m resolution hyperspectral images collected at three sites representing native longleaf pine ecosystems in the southeastern U.S. and aggregated pixels to sizes ranging from 1-90 m for comparative analyses. Plant community composition was groundtruthed. Results show that the capacity to detect plant beta diversity decreases with fewer pixels per mapping window, such that pixel resolution limits the size of mapping windows effective for representing beta diversity. Mapping window size in turn limits the spatial resolution of beta diversity maps composed of mapping windows. Assigning too few pixels per window, as well as assigning too many spectral species per image, results in overestimation of dissimilarity among locations that have plant species in common. This overestimation undermines the capacity to contrast mapping window dissimilarity within versus among community types and reduces the information content of beta diversity maps. These results demonstrate the advantage of maximizing spatial resolution of hyperspectral imaging instruments on the anticipated NASA SBG satellite mission and similar remote sensing projects.

Native and exotic vegetation cover shape avocado pollinator communities at the landscape scale

“…Based on a study done by Roberston et al, (2022) who investigated the effects of the different window sizes and spectral species selected, we used pixel window of 9 and 20 spectral species. From the map created by the BiodivMapR model, we calculated alpha and beta diversity metrics using the different sized buffers around each sampled orchard.…”