Analysis of temporal and spatial variation, driving factors and trend prediction of grain yield in Gansu Province
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DOI:10.7606/j.issn.1000-7601.2009.04.43
Key Words: grain production  grey correlation analysis  GM(1,1) model  Gansu Province
Author NameAffiliation
CHENG Ying College of Geography and Environment Sciences, Northwest Normal University, Lanzhou, Gansu 730070, China 
LIU Puxing College of Geography and Environment Sciences, Northwest Normal University, Lanzhou, Gansu 730070, China 
BAI Yang College of Geography and Environment Sciences, Northwest Normal University, Lanzhou, Gansu 730070, China 
MA Yalan College of Geography and Environment Sciences, Northwest Normal University, Lanzhou, Gansu 730070, China 
PAN Jingyuan College of Geography and Environment Sciences, Northwest Normal University, Lanzhou, Gansu 730070, China 
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Abstract:
      Based on temporal and spatial variation analysis of grain yield in Gansu Province in the past, the grey correlation analysis method was employed to explore the influential factors of grain yield and analyze quantitatively the degree of correlation between grain yield and its influential factors. The GM (1, 1) model was used to simulate and predict the variation trend of yield per unit area, year-end population and total grain yield. The results showed: (1) The grain yield of Gansu Province was increased in fluctuation, and the spatial distribution of annual average increase rate of grain yield had significant difference in each city and autonomous region. (2) The yield per unit area, year-end population, effective irrigated area, disaster-stricken area, cultivated area and grain planting area were the main driving factors of grain production. (3) The increasing degree of the total grain yield will not be apparent in the future, but the growth of population will get relatively faster. In order to promote sustainable development of grain production, the population should be controlled appropriately while grain production should be developed in a sustainable way.