大连市土地利用变化的人文因素

采用土地利用调查数据、社会经济统计资料等多种数据源,从定性与定量的角度进行大连市土地利用变化的人文因素研究。结果表明,应用因子分析方法可将影响大连市土地利用变化的因子归纳为经济发展和城市化水平因子、区域产业结构影响因子、农业产业结构影响因子、投资因子和人口因子等5个因子;应用多元回归分析方法可将土地利用面积变化率和土地利用变化强度表达为影响因子的函数关系,从函数关系可知各影响因子对大连市土地利用变化的影响作用大小不同,区域产业结构、经济发展与城市化水平因子的影响作用最大,人口、农业产业结构影响因子的作用其次,投资因子的影响作用最小。

Human dimensions of land use change in Dalian

With the deepening of global change researches, scientists have gradually realized that land use change caused by human dimensions is one of the essential factors and important components of global environmental change. Land use is in turn affected by human dimensions. So it necessary to reveal the relationship between land change and human dimensions. The Chinese Government energetically responds to the relevant research agenda jointly formulated by IGBP and human field research programme of global environmental change and tries to get in line with it as well as focuses on the Chinese characteristics. After a brief review of the studies on the human dimensions of the land use changes at home and abroad, this paper makes a thorough and careful study on the human dimensions that affect the land use changes in Dalian from the angles of qualitative and quantitative analysis by applying the SPSS statistic analysis techniques (such as the factor analysis and the regression analysis) together upon the data collected from the government materials, the statistical data and the on-the-spot investigation records. The findings indicate the tremendous impact of human behavior. First, using factor analysis, we identified five main factors affecting land use change in Dalian: economic development and urbanization, industrial structure, agricultural structure, investment factor and population. Then, using linear regression, we put the ratio of land use change and the intensity of land use change into functional relations. The result reveals that some factors have the same impact on land use change in Dalian. For example, the factors including industrial structure, economic development and urbanization have more impact on urban land use than the others.