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基于 Geodetector-SVM 模型的秦巴山区气候区划研究。

Exploring on the climate regionalization of Qinling-Daba mountains based on Geodetector-SVM model.

机构信息

State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, China.

University of Chinese Academy of Sciences, Beijing, China.

出版信息

PLoS One. 2020 Nov 2;15(11):e0241047. doi: 10.1371/journal.pone.0241047. eCollection 2020.

DOI:10.1371/journal.pone.0241047
PMID:33137142
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7605639/
Abstract

Qinling-Daba Mountains (QDM), which are located in central China, are considered as a significant climatic boundary delimiting north and south. However, the influence of complex topographic and climatic features makes it challenging to identify the exact location of the boundary, and different scholars delimit the boundary with significant differences. In addition, there is a gradual transition between climate zones, and no real dividing line exists. To explore the climate regionalization of the QDM, we focused on the identification of the transition zone rather than the exact location of the boundary between subtropical and temperate zones. Thus, we proposed a new workflow for climate regionalization based on the Geodetector-SVM model (a combination of Geodetector and support vector machines). First, we selected the spatial distribution data of six vegetation types (including typical subtropical and temperate vegetation) to represent the spatial distribution of climatic zones. Environmental factors (such as topography, temperature, precipitation, and soil) were used as explanatory variables for the spatial distribution of vegetation. Second, using the Geodetector-SVM model, the distribution characteristics and suitable environment of typical vegetation in different climatic zones are comprehensively explored. By analyzing the multiple boundaries between subtropical and temperate vegetation, the location of the transition zone of the QDM was identified. The results revealed the following: (1) The new workflow for climate regionalization based on the Geodetector-SVM model is powerful for the identification of the transition zone. The q-statistics are generally greater than 0.35, indicating that the transition zone between subtropical and temperate zones can highly reflect the character of the QDM; (2) From west to east, the transition zone mainly passes through the cities of Heishui County, Kang County, Liuba County, and Yichuan County and is approximately 30 km wide.

摘要

秦岭-大巴山(QDM)位于中国中部,被认为是划分南北气候的重要界限。然而,复杂的地形和气候特征使得确定该界限的确切位置变得具有挑战性,不同的学者对该界限的界定存在显著差异。此外,气候带之间存在逐渐过渡,不存在真正的分界线。为了探索 QDM 的气候区域化,我们专注于识别过渡带,而不是亚热带和温带之间的边界的确切位置。因此,我们提出了一种基于 Geodetector-SVM 模型(Geodetector 和支持向量机的组合)的气候区域化新工作流程。首先,我们选择了六种植被类型(包括典型的亚热带和温带植被)的空间分布数据来代表气候带的空间分布。环境因素(如地形、温度、降水和土壤)被用作植被空间分布的解释变量。其次,利用 Geodetector-SVM 模型,综合探讨了不同气候带典型植被的分布特征和适宜环境。通过分析亚热带和温带植被之间的多个边界,确定了 QDM 过渡带的位置。结果表明:(1)基于 Geodetector-SVM 模型的气候区域化新工作流程对于识别过渡带非常有效。q 统计量普遍大于 0.35,表明亚热带和温带之间的过渡带能够很好地反映 QDM 的特征;(2)自西向东,过渡带主要经过黑水县、康县、留坝县和宜川县等城市,宽度约为 30 公里。

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引用本文的文献

1
Correction: Exploring on the climate regionalization of Qinling-Daba mountains based on Geodetector-SVM model.更正:基于地理探测器-支持向量机模型的秦岭-大巴山气候区划探究
PLoS One. 2021 Feb 3;16(2):e0246774. doi: 10.1371/journal.pone.0246774. eCollection 2021.

本文引用的文献

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PLoS One. 2011;6(6):e21427. doi: 10.1371/journal.pone.0021427. Epub 2011 Jun 27.
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Determination of World Plant Formations From Simple Climatic Data.
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Science. 1947 Apr 4;105(2727):367-8. doi: 10.1126/science.105.2727.367.