Extraction and Dynamic Spatial-Temporal Changes of Grassland Deterioration Research Hot Regions in China

doi:10.5814/j.issn.1674-764x.2017.04.006

Abstract

Abstract: The authors use a web crawler to retrieve all periodical articles from CNKI between the 1950s and 2016 and then parse the abstracts of 293368 articles about grassland deterioration by word segmentation, location matching and other methods. The authors also construct a research hot regions extraction model of grassland deterioration in China based on a comprehensive research hot regions index of toponyms and then analyze the spatial pattern and dynamic change in research hot regions of grassland deterioration in China. The research shows the following: (1) The spatial heterogeneity of grassland deterioration in China can be effectively described by a model of grassland deterioration based on the comprehensive research hot regions index. (2) The research hot regions of grassland deterioration are mainly distributed in most regions of Inner Mongolia, Xinjiang, Qinghai, Tibet, Gansu and other provinces. The northeastern region of Inner Mongolia (such as Hulunbeier) and the eastern region of Inner Mongolia (such as Xilin Gol, Chifeng and Wulanchabu) are significant hot regions in the study of grassland deterioration. (3) The number of high research hot regions increases from 81 in the 1950s to 99 in the 2000s; the area increases from 1.038 million km² to 1.146 million km². The degree of hot for grassland deterioration research in 197 counties showed an upward trend. This paper also discusses the relationship between the region of research hot regions and the region of grassland deterioration and then indicates the differences between them in time matching, space matching and concept matching.

Key words: dynamic change, grassland deterioration, hot regions analysis, knowledge engine, region extraction, spatial distribution

HU Yunfeng, HAN Yueqi, ZHANG Yunzhi, ZHUANG Yuan. Extraction and Dynamic Spatial-Temporal Changes of Grassland Deterioration Research Hot Regions in China[J]. Journal of Resources and Ecology, 2017, 8(4): 352-358.

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