摘要
[目的]耕地资源是我国乃至世界重要的土地资源,保护耕地数量不减少、质量不降低是我们每个公民义不容易的责任和义务。当前国内外对耕地保护的研究大多仅停留在时间上的比较以及定量的分析,很少对指标因素和时间进行横纵向比较。[方法]文章基于乌鲁木齐市2004~2013年耕地面积,从全市人口、经济、政策投资及科技与城建等4个大类出发,选取18个指标,分析了乌鲁木齐市耕地面积的变化态势和规律。采用主成分和多元回归的分析方法,揭示了耕地面积变化的驱动机制;采用相应的指标体系构建耕地面积变化驱动模型。[结果]研究表明:近10年乌鲁木齐市耕地面积呈减少-增多-减少趋势,而GDP、居民储蓄存款、市区总人口及财政支出是影响耕地面积变化的主要因素。[结论]鉴于此,该研究为乌鲁木齐市土地资源的合理配置、土地利用规划以及耕地资源的科学利用提供决策依据,为实现当地资源、环境与经济的可持续发展提供了新的思路。
Cultivated land resource is the important land resources in China and even all over the world, to protect cultivated land quantity and quality is our responsibility and obligation of every citizenship. Most of the current do- mestic and international research on cultivated land protection only focused on the time comparison and quantitative analysis, there were very few horizontal longitudinal comparison on index factors and time. Based on the data of cultivated land from 2004 to 2013 in Urumqi, from four major categories, i.e. , the city＇s population, economy, policy, investment and technology, and the urban construction, this paper selected 18 indexes for the horizontal longitudinal comparative analysis to reveal the change of cultivated land in Urumqi. And then it summarized the cultivated land change driving mechanism using the principal components and multiple regression analysis method. The results showed that the cultivated land area was in the trend of deceasing - increasing in nearly a decade. The fiscal expenditure, GDP, and urban population were the main factors affecting arable land changes. The study can provide decision - making basis for the reasonable allocation of land resources, land use planning, and the scientif- ic utilization of cultivated land resources, so as to realize the sustainable development of local resources, environ- ment and economy.
出处
《中国农业资源与区划》
CSCD
北大核心
2017年第3期47-51,72,共6页
Chinese Journal of Agricultural Resources and Regional Planning
基金
国家社会科学基金项目"塔里木盆地矿-农复合区矿产资源利用补偿调控机制研究"(08BJY061)
关键词
乌鲁木齐市
耕地
驱动机制
变化态势
多元回归分析
Urumqi
arable land
driving mechanism
changes in the situation
multiple regression analysis
