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The geodiv r package: Tools for calculating gradient surface metrics.
Smith, Annie C; Dahlin, Kyla M; Record, Sydne; Costanza, Jennifer K; Wilson, Adam M; Zarnetske, Phoebe L.
Afiliação
  • Smith AC; Department of Integrative Biology Michigan State University East Lansing MI USA.
  • Dahlin KM; Ecology, Evolution, and Behavior Program Michigan State University East Lansing MI USA.
  • Record S; Ecology, Evolution, and Behavior Program Michigan State University East Lansing MI USA.
  • Costanza JK; Department of Geography, Environment, and Spatial Sciences Michigan State University East Lansing MI USA.
  • Wilson AM; Department of Biology Bryn Mawr College Bryn Mawr PA USA.
  • Zarnetske PL; USDA Forest Service Southern Research Station Research Triangle Park NC USA.
Methods Ecol Evol ; 12(11): 2094-2100, 2021 Nov.
Article em En | MEDLINE | ID: mdl-35874973
ABSTRACT
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 an example application of geodiv to the fields of landscape ecology and biogeography. geodiv allows users to easily retrieve estimates of spatial heterogeneity for a variety of purposes, enhancing our understanding of how environmental structure influences ecosystem processes. The package works with any continuous imagery and may be widely applied in many fields where estimates of surface complexity are useful.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article