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Assessment of Spatial Agglomeration of Agricultural Drought Disaster in China from 1978 to 2016

Drought disaster space agglomeration assessment is one of the important components of meteorological disaster prevention and mitigation. Agriculture affected by drought disaster is not only a serious threat to world food security, but also an obstacle to sustainable development. Additionally, China...

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Autores principales: Wang, Qian, Liu, Yang-yang, Zhang, Yan-zhen, Tong, Lin-jing, Li, Xiaoyu, Li, Jian-long, Sun, Zhengguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779736/
https://www.ncbi.nlm.nih.gov/pubmed/31591457
http://dx.doi.org/10.1038/s41598-019-51042-x
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author Wang, Qian
Liu, Yang-yang
Zhang, Yan-zhen
Tong, Lin-jing
Li, Xiaoyu
Li, Jian-long
Sun, Zhengguo
author_facet Wang, Qian
Liu, Yang-yang
Zhang, Yan-zhen
Tong, Lin-jing
Li, Xiaoyu
Li, Jian-long
Sun, Zhengguo
author_sort Wang, Qian
collection PubMed
description Drought disaster space agglomeration assessment is one of the important components of meteorological disaster prevention and mitigation. Agriculture affected by drought disaster is not only a serious threat to world food security, but also an obstacle to sustainable development. Additionally, China is an important agricultural import and export country in the world. Therefore, we used the global Moran’s I and the local indicators of spatial autocorrelation (LISA) to reveal the spatial agglomeration of agricultural drought disaster in China from1978 to 2016, respectively. The results showed that China’s agricultural drought disaster presents local spatial autocorrelation of geographical agglomeration at national level during the study period. The spatial agglomeration regions of China’s agricultural drought disaster were in Inner Mongolia, Jilin province, Heilongjiang province, Liaoning province, Shanxi province, Hebei province, Shandong province, Shaanxi province and Henan province, indicating that agricultural drought disaster mainly distributed in North and Northwest China, especially occurred in the Yellow River Basin and its north areas. We also found that the overall movement direction of agricultural drought disaster agglomeration regions was northwest, and the maximum moving distance was 722.16 km. Our results might provide insight in early warning and prevention for drought disaster.
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spelling pubmed-67797362019-10-16 Assessment of Spatial Agglomeration of Agricultural Drought Disaster in China from 1978 to 2016 Wang, Qian Liu, Yang-yang Zhang, Yan-zhen Tong, Lin-jing Li, Xiaoyu Li, Jian-long Sun, Zhengguo Sci Rep Article Drought disaster space agglomeration assessment is one of the important components of meteorological disaster prevention and mitigation. Agriculture affected by drought disaster is not only a serious threat to world food security, but also an obstacle to sustainable development. Additionally, China is an important agricultural import and export country in the world. Therefore, we used the global Moran’s I and the local indicators of spatial autocorrelation (LISA) to reveal the spatial agglomeration of agricultural drought disaster in China from1978 to 2016, respectively. The results showed that China’s agricultural drought disaster presents local spatial autocorrelation of geographical agglomeration at national level during the study period. The spatial agglomeration regions of China’s agricultural drought disaster were in Inner Mongolia, Jilin province, Heilongjiang province, Liaoning province, Shanxi province, Hebei province, Shandong province, Shaanxi province and Henan province, indicating that agricultural drought disaster mainly distributed in North and Northwest China, especially occurred in the Yellow River Basin and its north areas. We also found that the overall movement direction of agricultural drought disaster agglomeration regions was northwest, and the maximum moving distance was 722.16 km. Our results might provide insight in early warning and prevention for drought disaster. Nature Publishing Group UK 2019-10-07 /pmc/articles/PMC6779736/ /pubmed/31591457 http://dx.doi.org/10.1038/s41598-019-51042-x Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Wang, Qian
Liu, Yang-yang
Zhang, Yan-zhen
Tong, Lin-jing
Li, Xiaoyu
Li, Jian-long
Sun, Zhengguo
Assessment of Spatial Agglomeration of Agricultural Drought Disaster in China from 1978 to 2016
title Assessment of Spatial Agglomeration of Agricultural Drought Disaster in China from 1978 to 2016
title_full Assessment of Spatial Agglomeration of Agricultural Drought Disaster in China from 1978 to 2016
title_fullStr Assessment of Spatial Agglomeration of Agricultural Drought Disaster in China from 1978 to 2016
title_full_unstemmed Assessment of Spatial Agglomeration of Agricultural Drought Disaster in China from 1978 to 2016
title_short Assessment of Spatial Agglomeration of Agricultural Drought Disaster in China from 1978 to 2016
title_sort assessment of spatial agglomeration of agricultural drought disaster in china from 1978 to 2016
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779736/
https://www.ncbi.nlm.nih.gov/pubmed/31591457
http://dx.doi.org/10.1038/s41598-019-51042-x
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