Prediction and Protection of Cultivated Land in China

Renyi Yang, Fenglian Liu and Zisheng Yang

Asian Agricultural Research, 2022, vol. 13, issue 02

Abstract: [Objectives] To protect cultivated land and ensure national food security and to forecast the cultivated land area of China and the provinces (cities) in 2030, 2035 and 2050. [Methods] Based on the cultivated land area data of the whole country and provinces (autonomous regions and municipalities) from 2009 to 2017, the OLS model is used to forecast the cultivated land area of China and the provinces (cities) in 2030, 2035 and 2050. [Results] The results show that the predicted area of cultivated land in 2030, 2035 and 2050 is 134.088 6 million ha, 133.785 6 million ha and 132.876 4 million ha, respectively, showing an obvious decreasing trend. The national cultivated land scale predicted in this paper can meet the requirements of the 2030 national cultivated land retention target set in the National Land Planning Outline (2016-2030).However, in the total area of existing cultivated land, there is still a certain area of sloping cultivated land (accounting for about 4% of the total cultivated land area, it is appropriate to gradually return farmland to forest).At the same time, nearly 20% of the cultivated land has been polluted, and the low-quality cultivated land accounts for about 22% of the total cultivated land. [Conclusions] The situation of cultivated land protection in the whole country is not rosy. For this reason, some measures and suggestions are put forward: strengthening land consolidation, striving to improve the quality of cultivated land, and appropriately increasing new cultivated land; strengthening the protection of cultivated land resources and strictly controlling the reduction of cultivated land.Key words Cultivated land, Scale, Prediction, Cultivated land protection, China, Ordinary least square (OLS) regression model

Keywords: Agribusiness (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:ags:asagre:316690

DOI: 10.22004/ag.econ.316690

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