漫湾水电站库区土地利用变化社会经济因子的多变量分析

使用1991、2001和2004年3 a遥感影像数据,测定了漫湾水电站库区土地利用变化并利用多变量分析法定量分析了引起变化的驱动力。首先应用G IS和RS技术对漫湾水电站库区土地利用变化和社会经济数据进行空间尺度匹配,然后利用典范对应分析法(CCA)对各类型的土地利用变化与社会经济因素的相关性进行分析。研究发现,1991-2001年间,土地利用转移频繁与多个社会经济因子有紧密联系。人口(POP)、粮食总产量(GYC)、农业人口(A-POP)和人均耕地面积(PCAL)与土地利用变化转移之间有显著的相关性。而许多土地利用转移类型都与各个社会经济因素有紧密联系。2001-2004年期间,农业人口(A-POP)、粮食总产量(GYC)和畜牧业产值(LSP)与土地利用变化之间有显著的相关性。但土地利用转移类型中只有少数地类与农业人口(A-POP)、粮食总产量(GYC)和畜牧业产值(LSP)相关性显著;除此之外,其他土地利用变量与社会经济因子的相关性不明显。总的看来,从1991-2004年间土地利用变化都与农业人口(A-POP)和粮食总产量(GYC)有明显的相关性,说明该区域内农业人口(A-POP)和粮食总产量(GYC)的变化是驱动土地利用变化主要因素之一。该研究方法对土地利用变化驱动力的研究具有借鉴作用。

Multivariable analysis of socio-economic factors to drive the land-use changes in the area of Manwan Dam

Human activities are the one of major causes for land-use changes. The objective of this study is to detect the land-use changes in the area of Manwan hydropower station by using muhitemporal satellite image data, and the relationships between land-use changes and socio-economic factors were analyzed by using multivariate analysis. In order to achieve this objective, three different periods' land-use maps were derived from the Landsat image data which acquired in 1991,2001, and 2004. Moreover, the universal kriging interpolation was use to make the text file of socio-economic data into continuous surfaces raster data. A spatial database of land-use changes combining with soeio-economic factors was built in AreView program. With the help of multivariate analysis of CCA ordination method, the relationships between land-use changes and soeio-economie factors in the study area were conducted. The results show that the land-use changes are correlated with soeio-economic drivers both from 1991 to 2001 and from 2001 to 2004. Between 1991 and 2001, the landuse changes are strongly correlated with population (POP), gross yield of corps (GYC) , population of agriculture people (A-POP), and per capita arable land (PCAL). However, A-POP, GYC, LSP were identified as the main factors for landuse from 2001 to 2004 in the study area. The results also indicated that the multivariate analysis method can be adopted for the study of other types of land use change and in other regions.