基于高光谱影像的三江源区不同退化程度高寒草甸分类研究  

A Study on Classification of Different Degradation Level Alpine Meadows based on Hyperspectral Image Data in Three-river Headwater Region

作　　者：李双[1,2] 徐新良[1] 付颖[1,2] 

机构地区：[1]中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京100101 [2]中国科学院大学,北京100049

出　　处：《遥感技术与应用》2015年第1期50-57,共8页Remote Sensing Technology and Application

基　　金：国家科技支撑计划(2013BAC03B01);中国科学院西部行动计划项目(KZCX2-XB3-08-01);中国清洁发展机制基金赠款项目(1214115)

摘　　要：三江源地区是我国最重要的生态功能区之一。近年来,受全球气候变暖及日趋频繁的人类活动的影响,三江源地区高寒草甸生态系统退化现象明显。以三江源称多县清水河镇东北部地区为实验区,基于环境小卫星HJ-1A HSI高光谱数据,结合不同退化程度高寒草甸地面光谱采集和样方调查,采用MLC和SAM方法对不同退化程度的高寒草甸开展了分类研究。结果表明:基于高光谱数据的不同退化程度高寒草甸采用SAM方法分类总体精度达到75%以上,证实了分类方法的可行性,基于高光谱数据分类能有效区分盖度相近、退化程度不同的草地类型,其中SAM分类结果更加精细准确,优于MLC方法,SAM方法对中度退化草甸区分能力最高,对其他退化程度草甸区分能力稍弱。The Three-River Headwater Region is one of the most important ecological function areas in China.In recent years,due to the global warming and effect of frequent human activities,the degradion of grassland ecosystem becomes serious in the Three-river Headwater Region.Based on HJ-1A HSI data,field spectrum data and sample investigation data of different degradation level grasslands,using MLC and SAM methods,this paper studied the classification of different degradation level grasslands in the northeast area of Qingshuihe Town of Chengduo in Three-River Headwater Region.The results showed that the overall classifiction accuracy of SAM method was above 75% based hyperspectral image data and proved the feasibility of the classification approach.It performed effectively discriminating different degradation level grassland with similar vegetation coverage based on hyperspectral image data.SAM performed better than MLC in classification accuracy and fine degree.SAM worked best in distinguishing medium level degradation grassland,while performed weaker in distinguishing other degradation level grassland,which could be improved by introducing auxiliary parameters.

关 键 词：HJ-1A HSI 高光谱 植被光谱 草地退化 遥感分类 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]