Title :
Blue-green algae discriminant model based on normalized variance of spectrum vector
Author_Institution :
Sch. of Hydropower & Inf. Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
Facing to the more and more serious eutrophication and frequent outbreak of blue-green algae event in inland lake, the early warning of them has become urgent affairs. To monitor them in large scale rapidly and improve the extraction accuracy by remote sensing technology, MODIS data is a kind of ideal data source for its free getting, high spectrum resolution and temporal resolution. In this paper, a novel blue-green algae discriminant model is adopted based on normalized variance of spectrum vector. Experiments show it has good extraction accuracy.
Keywords :
environmental monitoring (geophysics); lakes; remote sensing; water pollution measurement; MODIS data; blue-green algae; discriminant model; extraction accuracy; ideal data source; inland lake; normalized variance; remote sensing technology; spectrum vector; Algae; Lakes; MODIS; Monitoring; Pixel; Remote sensing; Temperature sensors; MODIS; blue-green algae; normalized variance; remote sensing; spectrum vector;
Conference_Titel :
Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9172-8
DOI :
10.1109/RSETE.2011.5964942