Research and model construction on zonation of high standard farmland in low hilly land of Northeast China——Using Yilan County of Heilongjiang Province as an example
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DOI:10.7606/j.issn.1000-7601.2015.03.37
Key Words: high standard prime farmland  low mountains and hills areas  regional assignment  construction model  Northeast China
Author NameAffiliation
XING He-qun 沈阳农业大学土地与环境学院, 辽宁 沈阳 110866 
MENG Fan-kui 沈阳农业大学土地与环境学院, 辽宁 沈阳 110866 
SU Li 沈阳农业大学土地与环境学院, 辽宁 沈阳 110866 
LI Shuang-yi 沈阳农业大学土地与环境学院, 辽宁 沈阳 110866 
WANG Jing-kuan 沈阳农业大学土地与环境学院, 辽宁 沈阳 110866 
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Abstract:
      Based on the concept to construct high standard prime farmland in the Northeast of China, Yilan County was employed as an example to investigate the zonation and construction model of high standard farmland in low hilly land of Northeast China, using 10 selected indexes including the natural talent of the cultivated land and social economic condition, as well as the analytic hierarchy process and grey correlation analysis method. The results showed that a series of problems existed in the cultivated lands of Yilan County, including imbalance of arable land distribution, poor quality, low level utilization, low level of mechanization, small ratio of farmland protection area, and poor capability in shielding against natural disasters etc. The high standard farmland in Yilan County could be classified into four categories, most suitable, suitable, conditional, and unconditional. Area coverage of the first three categories was 196 200 hm2, accounting for 70% of the total arable land. The construction models of Yilan County could be set up as the following four types: plain soil conservation, soil fertility increase, hilly soil conservation, and hilly soil fertility. This could help to achieve a relative union of cultivated land, an improvement of mechanization on agricultural production, an enhancement of protection coverage on the farmland, an increase of magnetism thickness, an enrichment of organic matter content, and a promotion of comprehensive agricultural productivity.