三峡库区土地利用变化与影响因子分析

利用1995、2000和2005年的Landsat TM遥感数据解译结果分析了三峡库区的土地利用格局，三峡库区建设用地总量上升，各类建设用地的增长率不一致，库区水面在增加；运用单一土地利用动态度分析了相关地类的变化速度和分布，各地类的动态度与变化速度存在空间上的差异；采用景观生态学的方法分析了土地利用变化的景观特征，景观的多样性在增加，而景观的破碎度有一个先减小后增加的趋势，同时景观优势度的变化不大，耕地景观的优势逐渐被多样性景观特征所替代。然后采用典型相关分析的方法，计算典型载荷，找出各典型变量在分析过程中的作用，借此分析了土地利用变化与社会经济影响因子之间的关系。

LAND USE CHANGE AND INFLUENTIAL FACTORS IN RESERVOIR AREA OF THREE GORGES

Regional land use change is an important part of global change.The research on land use change in the reservoir area of Three Gorges has attracted a lot of attention.The reservoir area has become one of the important research areas.Based on the Landsat TM datum in 1995,2000 and 2005,the land use change in the reservoir area of Three Gorges was monitored with the support of RS and GIS.Using the present land use map in 2005,the land use pattern was analyzed in 2005.It is indicated that most cultivated land is distributed in the upper reach area and the forestry land is aggregated in the belly area and lower reach area.Based on the land use change matrixes in 1995~2000 and 2000~2005,most cultivated land changed into construction land,with a decrease by 1 369.61 hm2 and 7061.05 hm2 respectively.In addition,river areas increased by 8 421.06 hm2 because of the rising of the water level.The dynamic degree of single land use change was used in order to describe certain land use change rate and the distribution of dynamic degree of single land use change using GIS.The theory of landscape ecology was adopted to illuminate the traits of land use change.Cultivated land decreased rapidly with the trend of fragmentation,and landscape diversity increased with the decrease of the land dominance.The canonical correlation analysis was used to understand the relationship between the land use change and social economic factors,and to identify primary social economic factors from the quantitative analysis.The increase of construction land is relative with the capital investment and the development of the first industry.It is considered that the present study is helpful for the land use forecasting and successive land use.