Journal
GISCIENCE & REMOTE SENSING
Volume 49, Issue 6, Pages 873-894Publisher
TAYLOR & FRANCIS LTD
DOI: 10.2747/1548-1603.49.6.873
Keywords
-
Categories
Funding
- Chinese Academy of Sciences [KZCX2-EW-QN308, KZCX2-YW-QN311]
- National Natural Science Foundation of China [41171271, 41171273]
- National Projects of International Cooperation and Exchanges of the Ministry of Science and Technology of China [2010DFA90960]
- Hong Kong Research Grants Council (RGC) General Research Fund (GRF) [CUHK459210]
- Hong Kong Innovation & Technology Fund (ITF) [GHP/002/11GD]
- ESA-MOST Dragon Cooperation Programm [10561]
Ask authors/readers for more resources
Three artificial neural network (ANN) processors available as plug-in modules for the Basic ERS & ENVISAT (A) ATSR and MERIS Toolbox (BEAM) were validated in Lake Taihu, China. Mean deviations of reflectance derived from Lakes\Boreal and Lakes\Eutrophic were 10-90%, while reflectance from the -FUB-WeW processor showed larger errors. All processors showed underestimates of chlorophyll a (Chl-a), total suspended matter (TSM), and phytoplankton pigment absorption, while particulate scattering values were severely overestimated. None of the readily available MERIS processors is currently able to separate atmospheric and water-leaving radiance over Lake Taihu, while the retrieval of phytoplankton biomass through ANN processors shows promise.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available
Share Paper
