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利用空间扫描统计方法对森林健康指标进行地理分析。

Geographic analysis of forest health indicators using spatial scan statistics.

作者信息

Coulston John W, Riitters Kurt H

机构信息

Department of Forestry, North Carolina State University, Southern Research Station, Forestry Sciences Laboratory P.O. Box 12254, Research Triangle Park, North Carolina 27709, USA.

出版信息

Environ Manage. 2003 Jun;31(6):764-73. doi: 10.1007/s00267-002-0023-9.

Abstract

Geographically explicit analysis tools are needed to assess forest health indicators that are measured over large regions. Spatial scan statistics can be used to detect spatial or spatiotemporal clusters of forests representing hotspots of extreme indicator values. This paper demonstrates the approach through analyses of forest fragmentation indicators in the southeastern United States and insect and pathogen indicators in the Pacific Northwest United States. The scan statistic detected four spatial clusters of fragmented forest including a hotspot in the Piedmont and Coastal Plain region. Three recurring clusters of insect and pathogen occurrence were found in the Pacific Northwest. Spatial scan statistics are a powerful new tool that can be used to identify potential forest health problems.

摘要

需要具备地理明确性的分析工具来评估在广大区域内测量的森林健康指标。空间扫描统计可用于检测代表极端指标值热点的森林空间或时空集群。本文通过对美国东南部的森林破碎化指标以及美国太平洋西北部的昆虫和病原体指标进行分析来演示该方法。扫描统计检测到四个破碎森林的空间集群,包括皮埃蒙特和沿海平原地区的一个热点。在太平洋西北部发现了昆虫和病原体发生的三个反复出现的集群。空间扫描统计是一种强大的新工具,可用于识别潜在的森林健康问题。

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