Abstract

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.

Details

Title
Assessment of Spatial Agglomeration of Agricultural Drought Disaster in China from 1978 to 2016
Author
Wang, Qian 1 ; Yang-yang, Liu 1 ; Yan-zhen, Zhang 1 ; Lin-jing, Tong 1 ; Li, Xiaoyu 1 ; Jian-long, Li 1 ; Sun, Zhengguo 2 

 Department of Ecology, School of Life Sciences, Nanjing University, Nanjing, China 
 College of Agro-Grassland Sciences, Nanjing Agricultural University, Nanjing, China 
Pages
1-8
Publication year
2019
Publication date
Oct 2019
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2301897268
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.