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  • 标题:Comparison of Geographically Weighted Regression of Benthic Substrate Modeling Accuracy on Large and Small Wadeable Streams
  • 本地全文:下载
  • 作者:Ken R. Sheehan ; Stuart A. Welsh
  • 期刊名称:Journal of Geographic Information System
  • 印刷版ISSN:2151-1950
  • 电子版ISSN:2151-1969
  • 出版年度:2021
  • 卷号:13
  • 期号:2
  • 页码:194-209
  • DOI:10.4236/jgis.2021.132011
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:Aquatic habitat assessments encompass large and small wadeable streams which vary from many meters wide to ephemeral. Differences in stream sizes within or across watersheds, however, may lead to incompatibility of data at varying spatial scales. Specifically, issues caused by moving between scales on large and small streams are not typically addressed by many forms of statistical analysis, making the comparison of large (>30 m wetted width) and small stream (2 values of large and small stream streams. Results also provided a much needed method for comparison of large and small wadeable streams. Our results have merit for aquatic resource managers, because they demonstrate ability to spatially model and compare substrate on large and small streams. Using depth to guide substrate modeling by geographically weighted regression has a variety of applications which may help manage, monitor stream health, and interpret substrate change over time.
  • 关键词:Stream Habitat Modeling;Geographically Weighted Regression;Spatial Scale;Habitat Interpolation;Geographic Information System
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