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山东省县域粮食生产格局演变及其影响因素
引用本文:李明杰,王国刚,张红日.山东省县域粮食生产格局演变及其影响因素[J].农业现代化研究,2018,39(2):248-255.
作者姓名:李明杰  王国刚  张红日
作者单位:山东科技大学/测绘科学与工程学院,中国农业科学院农业经济与发展研究所,山东科技大学/测绘科学与工程学院
基金项目:国家自然科学基金项目(41401203)
摘    要:利用1995—2015年山东省县域粮食产量等数据资料,运用ESDA、重心迁移模型和多元回归模型等方法,分析山东省粮食生产格局演变及其地理集聚特征,探索影响粮食生产格局变迁的关键因素。结果表明:研究时段内,山东省粮食生产波动较大,粮食产量由1995年的4 245万t减少到2002年的3 293万t,然后通过十三连增,到2015年达到4 713万t;县域尺度上,山东省粮食生产的空间集聚程度不断增强,但西部地区产量增长明显快于东部地区,重心向西移动显著,逐步形成了"西热东冷"的空间格局。研究表明,农业机械总动力、有效灌溉面积和年末总人口等因素对粮食产量有着显著地正向影响,而人均地区生产总值和农村用电量表现为负向影响,共同推动粮食生产及其空间格局的演变。因此,提出加强高标准农田建设、推动土地适度规模化发展和建立粮食主产县利益补偿机制等建议,有效保障粮食产能。

关 键 词:粮食生产  格局变迁  影响因素  地理集聚  适度规模
收稿时间:2017/9/20 0:00:00
修稿时间:2018/1/17 0:00:00

Spatio-temporal dynamics of grain production in Shandong Province and its impacting factors at county-level
LI Ming-jie,WANG Guo-gang and ZHANG Hong-ri.Spatio-temporal dynamics of grain production in Shandong Province and its impacting factors at county-level[J].Research of Agricultural Modernization,2018,39(2):248-255.
Authors:LI Ming-jie  WANG Guo-gang and ZHANG Hong-ri
Institution:Shandong University of Science and Technology Geomatics College,Shandong Qingdao,Institute of Agricultural Economics and development,CAAS,Shandong University of Science and Technology Geomatics College,Shandong Qingdao
Abstract:Based on the data of county grain yield in Shandong Province from 1995 to 2015, and applying the methods of ESDA, center of gravity migration, multiple regression models, this paper analyzed the evolution and spatial pattern of grain production in Shandong Province. The authors further explored key factors that affected changes of grain production pattern using multiple regression models. The results show that the grain yield of Shandong Province fluctuated greatly during the study period. It decreased from 42.45 million tons in 1995 to 32.93 million tons in 2002. The production had grew for 13 consecutive years, reached 47.13 million tons in 2015. At the county scale, the spatial agglomeration of grain production increased continuously. The output in the western region increased obviously faster than that in the eastern region. The center of gravity had moved significantly westwards. The results indicate that the total power of agricultural machinery, effectively irrigated area and the total population at the end of the year have a significant positive impact on grain output. In contrast GDP per capita and rural electricity consumption had a negative impact on grain production. Lastly, some suggestions such as strengthening the construction of high-standard farmland, promoting the proper scale development of land and establishing the compensation mechanism for the interests of major grain-producing counties were put forward to sustain the grain production capacity.
Keywords:grain production  pattern change  impact factors  geographical agglomeration  moderate scale
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