Eco-geographical Regionalization of China:An Approach Using the Rough Set Method

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Eco-geographical regionalization involves dividing land into regions by considering both intra-regional consistency and inter-regional disparity and is based on the pattern of differentiation of eco-geographical elements.Owing to the complexity of the land sur-face,and the limitation of data and appropriate methods,regions in China have hitherto been mapped manually,meaning that the pro-cess of mapping was non-repeatable.To make the regionalization technique repeatable,this study aimed to extract and quantify the ex-pert knowledge of regionalization using an automated method.The rough set method was adopted to extract rules of regionalization based on the existing eco-geographical regionalization map of China,as well as its corresponding meteorological and geological data-sets.Then,the rules for regionalization were obtained hierarchically for each natural domain,each temperature zone,and each humidity region.Owing to differences in zonal differentiation,the rule extraction sequence for the eastern monsoon zone and Tibetan Alpine zone was temperature zone first followed by humidity region,with the reverse order being applied for the northwest arid/semi-arid zone.Res-ults show that the extracted indicators were similar to those of the existing(expert-produced)regionalization scheme but more compre-hensive.The primary indicator for defining temperature zones was the≥10℃growing season,and the secondary indicators were the January and July mean temperatures.The primary and secondary indicators for identifying humid regions were aridity index and precip-itation,respectively.Eco-geographical regions were mapped over China using these rules and the gridded indicators.Both the temperat-ure zones and humidity regions mapped by the rules show≥85%consistency with the existing regionalization,which is higher than val-ues for mapping by the commonly used simplified method that uses the classification of one indicator.This study demonstrates that the proposed rough set method can establish eco-geographical regionalization that is quantitative and repeatable and able to dynamically up-dated.
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