摘要
TM图象多波段数据作为遥感监测水体叶绿素a浓度的数据源,已有多种遥感定量模型与之对应,但主要还是以经验模型为主。利用TM数据首先采用特征波段比值方法,建立太湖水体合适的叶绿素a浓度反演的遥感定量模型。由于经验模型的缺陷性,还提出了基于TM数据的水体混合光谱分析模型,同时分析了端元光谱提取方法对模型求解的影响。通过计算叶绿素a浓度模型估算结果与实地测量数据的相关系数和均方根误差(RMSE),可以发现混合光谱分析模型也是水体叶绿素a浓度遥感估算的另一条佳径。
Thematic Mapper （TM） data can be used to estimate chlorophyll-a concentration of water body and monitor the quality of inland water. There are different models for TM estimating ChlorophyU-a concentration, and the major model is empirical regression model. In this paper we build chlorophyll-a models based on TM data, in which the traditidnal band ratio approach and mixing spectral analysis model were used. And we also analyzed the method of end-member extraction. The correlation coefficient and rooted mean square errors were calculated, and the results of chlorophyll-a concentration gained from these models and those gained from the analysis in lab were compared, the result shows that the mixing spectral model for estimating Chlorophyll-a concentration is a optimal method.
出处
《地理科学》
CSCD
北大核心
2007年第1期92-97,共6页
Scientia Geographica Sinica
基金
中国科学院知识创新新重要方向性项目CAS(KZCX3-SW-334
KZCX3-SW-338)资助
关键词
水质遥感
混合光谱分析
叶绿素A
TM数据
water quality remote sensing
mixing spectral analysis
chlorophyll-a
Thematic Mapper （TM） data
