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Mapping landscape ecological patterns using numeric and categorical maps

The reciprocal relationships between ecological process and landscape pattern are fundamental to landscape ecology. Landscape ecologists traditionally use raster maps portraying classified features such as land use or land cover categories, and metrics suggested by the patch-corridor-matrix conceptu...

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Autores principales: Riitters, Kurt, Vogt, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10651036/
https://www.ncbi.nlm.nih.gov/pubmed/37967129
http://dx.doi.org/10.1371/journal.pone.0291697
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author Riitters, Kurt
Vogt, Peter
author_facet Riitters, Kurt
Vogt, Peter
author_sort Riitters, Kurt
collection PubMed
description The reciprocal relationships between ecological process and landscape pattern are fundamental to landscape ecology. Landscape ecologists traditionally use raster maps portraying classified features such as land use or land cover categories, and metrics suggested by the patch-corridor-matrix conceptual model of pattern. Less attention has been given to the landscape gradient conceptual model and raster maps portraying numeric features such as greenness or percent vegetation cover. We introduce the open-source tool GraySpatCon to calculate and map a variety of landscape pattern metrics from both conceptual models using either categorical or numeric maps. The 51 metrics, drawn mostly from the landscape ecology and image processing literatures, are calculated from the frequencies of input pixel values and/or the pixel value adjacencies in an analysis region. GraySpatCon conducts either a moving window analysis which produces a continuous map of a pattern metric, or a global analysis which produces a single metric value. We describe an implementation in the GuidosToolbox desktop application which allows novice users to interactively explore GraySpatCon functionality. In the R desktop environment, we demonstrate several metrics using an example map of percent tree cover and illustrate a multi-scale moving window analysis to identify scale domains. Comparisons of computational efficiency indicate a substantial GraySpatCon advantage over related software in the R environment.
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spelling pubmed-106510362023-11-15 Mapping landscape ecological patterns using numeric and categorical maps Riitters, Kurt Vogt, Peter PLoS One Research Article The reciprocal relationships between ecological process and landscape pattern are fundamental to landscape ecology. Landscape ecologists traditionally use raster maps portraying classified features such as land use or land cover categories, and metrics suggested by the patch-corridor-matrix conceptual model of pattern. Less attention has been given to the landscape gradient conceptual model and raster maps portraying numeric features such as greenness or percent vegetation cover. We introduce the open-source tool GraySpatCon to calculate and map a variety of landscape pattern metrics from both conceptual models using either categorical or numeric maps. The 51 metrics, drawn mostly from the landscape ecology and image processing literatures, are calculated from the frequencies of input pixel values and/or the pixel value adjacencies in an analysis region. GraySpatCon conducts either a moving window analysis which produces a continuous map of a pattern metric, or a global analysis which produces a single metric value. We describe an implementation in the GuidosToolbox desktop application which allows novice users to interactively explore GraySpatCon functionality. In the R desktop environment, we demonstrate several metrics using an example map of percent tree cover and illustrate a multi-scale moving window analysis to identify scale domains. Comparisons of computational efficiency indicate a substantial GraySpatCon advantage over related software in the R environment. Public Library of Science 2023-11-15 /pmc/articles/PMC10651036/ /pubmed/37967129 http://dx.doi.org/10.1371/journal.pone.0291697 Text en https://creativecommons.org/publicdomain/zero/1.0/This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Riitters, Kurt
Vogt, Peter
Mapping landscape ecological patterns using numeric and categorical maps
title Mapping landscape ecological patterns using numeric and categorical maps
title_full Mapping landscape ecological patterns using numeric and categorical maps
title_fullStr Mapping landscape ecological patterns using numeric and categorical maps
title_full_unstemmed Mapping landscape ecological patterns using numeric and categorical maps
title_short Mapping landscape ecological patterns using numeric and categorical maps
title_sort mapping landscape ecological patterns using numeric and categorical maps
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10651036/
https://www.ncbi.nlm.nih.gov/pubmed/37967129
http://dx.doi.org/10.1371/journal.pone.0291697
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