摘要
有效地提取蓝藻水华信息对分析蓝藻动态分布有重要意义,然而低空间分辨率数据提取的蓝藻水华会产生尺度误差.本文以太湖为研究区,利用2005年10月17日和2010年12月3日两景MODIS(250和500 m)数据,采用浮游藻类指数(FAI)法提取太湖蓝藻水华面积;通过将FAI250均值化为FAImean(500 m),然后与FAI500比较,从像元角度定量评价FAI的尺度误差,分析引起提取误差的原因.结果表明,FAI500平均值偏大,造成提取出来的蓝藻水华面积增大;而太湖蓝藻水华监测结果的尺度差异是水体的空间异质性导致的,即存在水体和水华混合组成的像元导致提取面积有误差.
In order to study the spatio-temporal patterns of cyanobacteria blooms,it is important to detect and monitor them effectively by satellite observations.However,such detection and monitoring by low resolution data induces a scaling bias.Based on MODIS（250m and 500m） data at Oct.17,2005 and Dec.3,2010,the area of cyanobacteria bloom in Lake Taihu was derived by a approach named Floating Algae Index（FAI）.The low resolution FAI was then achieved in two ways： FAI500,was directly calculated from MODIS（500m）;and the FAImean was the mean of FAI250 which was directly calculated from MODIS（250m）.Results reveal a serious overestimation of FAI500 and the area of cyanobacteria bloom due to the scale error all over Lake Taihu.The causes for scaling error are discussed and it is found that the spatial heterogeneous is the key factor which may lead to the error in the detection and monitoring on cyanobacteria bloom.
出处
《湖泊科学》
EI
CAS
CSCD
北大核心
2011年第6期847-854,共8页
Journal of Lake Sciences
基金
中国科学院知识创新工程重要方向性项目(KZCX2-YW-QN311
KZCX2-EW-QN308)
国家自然科学基金项目(40871168
40801137)
国家水体污染控制与治理科技重大专项项目(2009ZX07528-005-02)联合资助
