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利用数值地图和分类地图来绘制景观生态格局。

Mapping landscape ecological patterns using numeric and categorical maps.

机构信息

United States Department of Agriculture, Forest Service, Research Triangle Park, North Carolina, United States of America.

European Commission, Joint Research Centre, Ispra, Italy.

出版信息

PLoS One. 2023 Nov 15;18(11):e0291697. doi: 10.1371/journal.pone.0291697. eCollection 2023.

DOI:10.1371/journal.pone.0291697
PMID:37967129
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10651036/
Abstract

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.

摘要

生态过程与景观格局的相互关系是景观生态学的基础。景观生态学家传统上使用栅格地图来描绘分类特征,如土地利用或土地覆盖类别,以及斑块-走廊-基质模式概念模型所建议的指标。对景观梯度概念模型以及描绘数值特征(如绿色度或植被覆盖百分比)的栅格地图的关注较少。我们引入了开源工具 GraySpatCon,该工具可使用分类或数值地图,从这两个概念模型中计算和映射各种景观格局指标。这 51 个指标主要来自景观生态学和图像处理文献,是根据输入像素值的频率和/或分析区域中的像素值邻域计算得出的。GraySpatCon 可以进行移动窗口分析,从而生成一个连续的模式指标地图,也可以进行全局分析,生成一个单一的指标值。我们在 GuidosToolbox 桌面应用程序中描述了一个实现,允许新手用户交互式探索 GraySpatCon 功能。在 R 桌面环境中,我们使用树木覆盖百分比的示例地图演示了几个指标,并说明了多尺度移动窗口分析以识别尺度域。计算效率的比较表明,GraySpatCon 在 R 环境中的相关软件具有显著的优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cbf/10651036/e1011b4a1e68/pone.0291697.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cbf/10651036/d9496e45c314/pone.0291697.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cbf/10651036/d46b36380ba9/pone.0291697.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cbf/10651036/1b21dbb36aa6/pone.0291697.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cbf/10651036/6983b36b7372/pone.0291697.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cbf/10651036/a451b179f9a3/pone.0291697.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cbf/10651036/e1011b4a1e68/pone.0291697.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cbf/10651036/d9496e45c314/pone.0291697.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cbf/10651036/d46b36380ba9/pone.0291697.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cbf/10651036/1b21dbb36aa6/pone.0291697.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cbf/10651036/6983b36b7372/pone.0291697.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cbf/10651036/a451b179f9a3/pone.0291697.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cbf/10651036/e1011b4a1e68/pone.0291697.g006.jpg

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本文引用的文献

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