资源科学 ›› 2019, Vol. 41 ›› Issue (12): 2296-2306.doi: 10.18402/resci.2019.12.13

• 土地资源 • 上一篇    下一篇

不同经济发展水平地区耕地利用集约度比较

马聪, 刘黎明()   

  1. 中国农业大学土地科学与技术学院,北京 100193
  • 收稿日期:2019-06-02 修回日期:2019-10-09 出版日期:2019-12-25 发布日期:2019-12-25
  • 通讯作者: 刘黎明
  • 作者简介:马聪,女,山东德州人,博士研究生,主要研究方向为农户可持续生计与土地利用行为。E-mail:macong@cau.edu.cn
  • 基金资助:
    国家自然科学基金重点项目(41130526)

Cultivated land use intensity in regions with different economic development levels

MA Cong, LIU Liming()   

  1. College of Land Science and Technology, China Agricultural University, Beijing 100193, China
  • Received:2019-06-02 Revised:2019-10-09 Online:2019-12-25 Published:2019-12-25
  • Contact: LIU Liming

摘要:

揭示不同经济发展水平地区耕地利用集约度的时空差异及其驱动因素有助于了解农户土地投入行为对经济发展水平的响应状态,可以为实现耕地资源合理高效利用与农业可持续发展的政策制定提供参考。本文以上海市青浦区、长沙市长沙县和固原市彭阳县为例,运用实物形态法和综合指标法相结合的方法核算了不同经济发展水平地区2001—2016年的耕地利用集约度,然后采用岭回归模型分析了各地区耕地集约利用的驱动因素。结果表明:①2001—2016年,长沙县和彭阳县的耕地利用集约度呈波动上升趋势,而青浦区总体呈下降趋势,平均值从大到小为长沙县、青浦区、彭阳县;②耕地利用集约度包括资本集约度和劳动集约度,不同地区资本集约度在变化趋势和平均值大小顺序等方面与耕地利用集约度基本一致,而劳动集约度均呈波动下降趋势;③不同地区耕地集约利用的驱动因素存在差异,青浦区主要驱动因素为灌溉指数、农业政策和地均GDP,长沙县主要驱动因素是人均耕地面积、农业政策和地均GDP,而农业机械化水平是彭阳县主要驱动因素。不同地区的耕地利用集约度存在明显差异,并且其驱动因素也有所不同,政府相关部门应当根据当地实际情况采取相应措施以提高耕地集约利用水平。

关键词: 耕地利用集约度, 经济发展水平, 驱动因素, 实物形态法, 综合指标法, 岭回归模型, 比较研究

Abstract:

Revealing the spatial and temporal differences and driving factors of cultivated land use intensity in diverse regions with different economic development levels helps to understand the response of farmers’ land investment behavior to economic development levels. It could also provide references for the formulation of policies for realizing rational and efficient land resource use and sustainable development of agriculture. This study took Qingpu District of Shanghai Municipality, Changsha County of Hunan Province, and Pengyang County of Ningxia Hui Autonomous Region as the case areas. Cultivated land use intensity in different areas during 2001-2016 was calculated by the physical form method and comprehensive index method. A ridge regression model was used to determine driving factors of cultivated land intensive use. The results show that: (1) From 2001 to 2016, cultivated land use intensity in Changsha and Pengyang increased year by year, while that in Qingpu showed a decreasing trend. The order of their average values from high to low was Changsha, Qingpu, and Pengyang. (2) Capital intensity in different areas was basically consistent with cultivated land use intensity in terms of the change trend and the order of average values, while labor intensity declined year by year. (3) There were differences in the driving factors of cultivated land intensive use in different areas. The main driving factors in Qingpu were irrigation coverage, agricultural policy, and GDP per unit land area. Per capita cultivated land area, agricultural policy, and GDP per unit land area were the main driving factors in Changsha. Agricultural mechanization level was the main driving factor in Pengyang. In conclusion, there are differences in the cultivated land use intensity in various areas as well as in the driving factors. The relevant government departments should take corresponding measures to improve cultivated land use intensity according to local conditions.

Key words: cultivated land use intensity, economic development level, driving factors, physical form method, comprehensive index method, ridge regression model, comparative study