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Exploring on the climate regionalization of Qinling-Daba mountains based on Geodetector-SVM model
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 schol...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605639/ https://www.ncbi.nlm.nih.gov/pubmed/33137142 http://dx.doi.org/10.1371/journal.pone.0241047 |
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author | Hu, Yufan Yao, Yonghui Kou, Zhixiang |
author_facet | Hu, Yufan Yao, Yonghui Kou, Zhixiang |
author_sort | Hu, Yufan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7605639 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-76056392020-11-05 Exploring on the climate regionalization of Qinling-Daba mountains based on Geodetector-SVM model Hu, Yufan Yao, Yonghui Kou, Zhixiang PLoS One Research Article 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. Public Library of Science 2020-11-02 /pmc/articles/PMC7605639/ /pubmed/33137142 http://dx.doi.org/10.1371/journal.pone.0241047 Text en © 2020 Hu et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hu, Yufan Yao, Yonghui Kou, Zhixiang Exploring on the climate regionalization of Qinling-Daba mountains based on Geodetector-SVM model |
title | Exploring on the climate regionalization of Qinling-Daba mountains based on Geodetector-SVM model |
title_full | Exploring on the climate regionalization of Qinling-Daba mountains based on Geodetector-SVM model |
title_fullStr | Exploring on the climate regionalization of Qinling-Daba mountains based on Geodetector-SVM model |
title_full_unstemmed | Exploring on the climate regionalization of Qinling-Daba mountains based on Geodetector-SVM model |
title_short | Exploring on the climate regionalization of Qinling-Daba mountains based on Geodetector-SVM model |
title_sort | exploring on the climate regionalization of qinling-daba mountains based on geodetector-svm model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605639/ https://www.ncbi.nlm.nih.gov/pubmed/33137142 http://dx.doi.org/10.1371/journal.pone.0241047 |
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