Understanding the spatial distribution patterns (SDPs) of natural disasters plays an essential role in reducing and minimizing natural disaster risks. An integrated discussion on the SDPs of multiple global disasters is still lacking. In addition, due to their high quantity and complexity, natural disasters constitute high-dimensional data that represent a challenge for an analysis of SDPs. This paper analyzed the SDPs of global disasters from 1980 to 2016 through biclustering. The results indicate that the SDPs of fatality rates are more uneven than those of occurrence rates. Based on the occurrence rates, the selected countries were clustered into four classes. (1) The major disasters along the northern Pacific and in the Caribbean Sea and Madagascar are storms, followed by floods. (2) Most of Africa is mainly affected by floods, epidemics, and droughts. (3) The primary disaster types in the Alpine-Himalayan belt and the western Andes are floods and earthquakes. (4) Europe, America, Oceania, and South and Southeast Asia are predominantly influenced by floods. In addition, according to the fatality rates, the selected countries were clustered into eight classes. (1) Extreme high temperatures mostly result in high fatality rates (HFRs) in developed countries. (2) Epidemics lead to HFRs in parts of Africa. (3) Droughts produce HFRs in East Africa. (4) Earthquakes result in HFRs along the eastern Pacific coastline and the Alpine-Himalayan belt. (5) Tsunamis mainly cause HFRs in Thailand, Indonesia, and Japan. (6) Storms result in scattered but distinct HFRs along the coastal regions of the Pacific and Indian Oceans. (7) Floods cause concentrated HFRs in South Asia and northeastern South America. (8) Finally, volcanoes cause HFRs in Colombia, while extreme low temperatures cause HFRs in Ukraine and Poland.
Natural disasters Biclustering Spatial distribution Multiple disasters
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We would like to thank the anonymous reviewers for their constructive comments on the manuscript. This work was supported by National Natural Science Foundation of China [Grant Number 41771537], National Key Research and Development Plan of China [Grant Number 2017YFB0504102], and the Fundamental Research Funds for the Central Universities.
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