Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Life Sciences
Towards Mapping Biodiversity From Above: Can Fusing Lidar And Hyperspectral Remote Sensing Predict Taxonomic, Functional, And Phylogenetic Tree Diversity In Temperate Forests?, Aaron G. Kamoske, Kyla M. Dahlin, Quentin D. Read, Sydne Record, Scott C. Stark, Shawn P. Serbin, Phoebe L. Zarnetske
Towards Mapping Biodiversity From Above: Can Fusing Lidar And Hyperspectral Remote Sensing Predict Taxonomic, Functional, And Phylogenetic Tree Diversity In Temperate Forests?, Aaron G. Kamoske, Kyla M. Dahlin, Quentin D. Read, Sydne Record, Scott C. Stark, Shawn P. Serbin, Phoebe L. Zarnetske
Biology Faculty Research and Scholarship
Aim: Rapid global change is impacting the diversity of tree species and essential ecosystem functions and services of forests. It is therefore critical to understand and predict how the diversity of tree species is spatially distributed within and among forest biomes. Satellite remote sensing platforms have been used for decades to map forest structure and function but are limited in their capacity to monitor change by their relatively coarse spatial resolution and the complexity of scales at which different dimensions of biodiversity are observed in the field. Recently, airborne remote sensing platforms making use of passive high spectral resolution (i.e., …
The Geodiv R Package: Tools For Calculating Gradient Surface Metrics, Annie C. Smith, Kyla M. Dahlin, Sydne Record, Jennifer K. Costanza, Adam M. Wilson, Phoebe L. Zarnetske
The Geodiv R Package: Tools For Calculating Gradient Surface Metrics, Annie C. Smith, Kyla M. Dahlin, Sydne Record, Jennifer K. Costanza, Adam M. Wilson, Phoebe L. Zarnetske
Biology Faculty Research and Scholarship
The geodiv r package calculates gradient surface metrics from imagery and other gridded datasets to provide continuous measures of landscape heterogeneity for landscape pattern analysis. geodiv is the first open-source, command line toolbox for calculating many gradient surface metrics and easily integrates parallel computing for applications with large images or rasters (e.g. remotely sensed data). All functions may be applied either globally to derive a single metric for an entire image or locally to create a texture image over moving windows of a user-defined extent. We present a comprehensive description of the functions available through geodiv. A supplemental vignette provides …