摘要
利用2000年和2006年TM影像数据、地面调查资料和气象台站观测数据,对玛曲县沼泽湿地进行了目视解译分析,对比研究了非监督分类、监督分类和专家分类的精度,初步探讨了玛曲沼泽湿地退化的原因。结果表明,该县沼泽湿地面积从2000年的19598.67hm2减少到2006年的14080.80hm2,沼泽湿地面积平均年递减率为4.69%。非监督分类结果由于受山体阴影、坡向、云的阴影等影响,多分误差高,总分类精度仅为31%;监督分类的总精度为54.1%;专家分类的总精度高达84.2%。因此,专家分类可以用于对玛曲县沼泽湿地的监测和自动提取。草场不合理利用和过度放牧是导致玛曲县沼泽湿地退化的主要原因,黄河干流、各支流径流量减少是导致流域内沼泽湿地退化的直接原因,当地气候变暖促进了这一过程的发生。
The research of wetland degradation has become a hot topic concerned by a lot of ecologists in recent years. Maqu wetlands, located in the upper area of Yellow River, have a special ecological function because of their special geographical location. However, it is confronted with a very serious problem due to the warming climate and land degradation. By use of Landsat TM images in 2000 and 2006, ground survey information and meteorological data, the marsh wetlands in Maqu County were classified by visual interpretation approach. The spectral characteristics of TM bands 2, 3,4 and 5 for the 6 major land cover types of water, grassland, non-grassland, residential area, marsh wetland and riverside area were analyzed using ERDAS IMAGINE 9.1 software. Combined with Digital Elevation Model （DEM）, the marsh wetland expert classification model was created, the classification accuracies of unsupervised classification, supervised classification and expert classification methods were compared, and the reasons of the marsh wetland degradation in Maqu County were discussed. The results showed that the area of marsh wetlands in the County reduced from 1 9598.67 ha to 1 4080.80 ha from 2000 to 2006, the annual decrease rate was 4.69%. Due to the effects of mountain shadows, aspect and the shadow area of clouds the commission error was high, the overall accuracy was only 31% for the unsupervised classification approach. The overall accuracy of supervised classification approach was 54.1% ; compared with the unsupervised and supervised classification approaches, the expert classification result can eliminate the effects of topography, water and riverside area on marsh wetland, its omission error was 7.8% , commission error was 16.6%. The major omitted type was the marsh wetland under degradation; the principal commissioned types were low coverage of grassland located in flat areas, seasonal river ways and the shadow areas of clouds. The overall classification accuracy of expert classification method was high at 84.2%, which can be used to automati-cally extract marsh wetland in Maqu County. The unreasonable utilization of grassland and excessive grazing were the principal reasons for wetland degradation, the runoff decrease of the Yellow River and its tributaries was one of most important reasons, and the climate warming and drying exacerbated the processes of marsh wetland degradation in Muqu County.
出处
《湿地科学》
CSCD
2008年第3期379-385,共7页
Wetland Science
基金
国家"863"计划数字农业专题项目(2007AA10Z232)资助
关键词
沼泽湿地
湿地退化
湿地提取
专家分类
玛曲县
marsh wetland
wetland degradation
wetland extraction
expert classification
Maqu county
