Bray-Curtis dissimilarity matrices generated from NEON data using biodivMapR for DSNY, JERC, and OSBS sites - Kevin M Robertson (PANGAEA, 2023)
These data were generated for a project seeking to test the effect of spatial resolution (pixel size) of remote sensing reflectance data on the capacity for the R algorithm biodivMapR to accurately map beta biodiversity (in this case different natural communities) on natural landscapes within the southeastern U.S. Coastal Plain. The project used 1 m resolution hyperspectral data (402-2,500 nm) collected in September 2021 from airborne sensors at three National Ecological Observatory (NEON) sites aggregated to coarser resolutions for each test (1 m, 5 m, 15 m, 30 m, 40 m, 60 m, and 90 m pixels sizes). The NEON sites used were Disney Wilderness Preserve (DSNY), Jones Ecological Research Station (JERC), and Ordway-Swisher Biological Station (OSBS). Point locations within the remotely sensed scenes were established to represent known locations for specific natural community types. BiodivMapR produced Bray-Curtis dissimilarity matrices composed of pairwise comparisons of point locations within each NEON site. Dissimilarity represented that of spectral species (pixel categories based on reflectance spectra) within mapping windows containing a set number of pixels and centered on each point. MRPP analyses using the dissimilarity matrices were used to determine the degree that point locations were successfully clustered by community type at each spatial resolution (pixel size). Analyses were run using assignments of 50 spectral species versus 20 spectral species per scene. The data archived are the shapefiles with geographic point data and their corresponding community types used in analyses, as well as the Bray-Curtis dissimilarity matrices for each site, pixel resolution, mapping window size, and number of spectral species used in each analysis.