作　　者： ; ; ; ; ;

机构地区： 华南农业大学信息学院

出　　处： 《干旱区地理》 2012年第4期615-622,共8页

摘　　要： 依据草地退化国家标准和黄河源区草地退化的实际情况,选取草地覆盖度、植株高度、地上生物量、牧草可食率、土壤有机质5个重要指标建立黄河源区玛多县草地植被退化监测和评价指标体系。利用遥感影像和GIS技术,结合实地调查和采样测定,对5个评价指标在遥感影像上进行反演,并进行图层的加权叠加,得出玛多县草地退化的时空特征。结果表明:玛多县草地在1994年已经出现了较为严重的退化现象,退化草地的空间分布格局已经基本形成,并且草地的退化过程一直在继续。2009年草地退化空间特征显示在气候变化较为敏感区域、河道两侧、鼠害严重以及靠近居民点等区域草地退化较为严重。通过对4期草地退化情况进行对比分析,发现1994-2001年间玛多草地植被退化情况最严重,重度退化面积高达1 355 943.30 hm2,占草地面积的86.53%。2001-2006年间和2006-2009年间重度退化、较大退化和中度退化草地的面积都下降较大,同时退化的速度已经有了较大缓和,黄河源头地区草地生态系统得到初步恢复。 The Yellow River source region, as the headwater of the Yellow River, where the ecological environment is sensitive and vulnerable, is located in hinterland of the Qinhai - Tibet Plateau. It is of significant importance to protecting and constructing natural protection of ＂Three-River Headwater＂ by using remote sensing to monitor dynamically the grassland degradation in different temporal and spatial scale in this region. Grassland degradation refers to the overall reduction in grassland productivity as a consequence of human activities and natural processes. It represents the decline of grassland quality, density of grass cover, productivity, service function, or an increase in unpalatable grass species, and even as denudation of underlying soil. Compared with conventional grassland degradation researches, which are through field investigation to identify contributing factors and then each of the factors was graded and combined, remote sensing is much more efficient in assessing grassland degradation. Accorded to the national standard of China（ GB19377 -2003） and actual condition of grassland degradation in the Maduo County in the source region of the Yellow River, this study selected vegetation cover, pasture plant height, aboveground biomass, palatable pasture proportion, soil organic matter as the 5 evaluation indices. Then the calculation models were established based on the remote sense and in situ measured data, to monitor and evaluate grassland degradation in that region. Because of differential sampling sizes on the ground and space, the 5 evaluation indices cannot be directly quantified from TM imageries based on concurrently collected samples over 1 m^2 plots. So, significant regression models were used to set relation between in situ measured data and TM bands-derived index values. However, for the evaluation indices of pasture plant height and palatable pasture proportion, there is weak correlation between in situ measured data and remote sensing. In order to solve this problem, the calibrati

关 键 词： 草地退化 遥感监测 时空特征 黄河源区 玛多县

领　　域： [农业科学] [农业科学] [农业科学] [自动化与计算机技术] [自动化与计算机技术]