technology of extracting information in this paper. The algae
bloom frequency index (AFI) and algae bloom sustainability
index (ASI) is important criterion which can show the
interannual and inter-monthly variation in the whole area or
the subregion of Taihu Lake. Utilizing the AFI and ASI from
2009 to 2011; it found some phenomena that: 1) the severity
of booming generally decreased from the north and west to
the East and South of Taihu Lake. 2) There are the annual
periodical changing rules of cyanobacterial blooms. The
circle this cycle includes four stages, that is operation of low
level, rising phase, high shock and fall period. 3) The
phenomenon that “beyond a year” in blooming circle
appears in 2010 and 2011 which could indicate the change of
external environment.
5. ACKNOWLEDGMENTS
We are grateful for the financial support provided by
International Institute for Earth System Science, Nanjing
University, and NASA for providing the MODIS surface
reflectance daily level 2 products, and Nanjing Institute of
Geography & Limnology, Chinese Academy of Sciences for
providing the blooming monitoring data in Taihu Lake from
2009 to 2011.
REFERENCES
Guo H, 2000. Theory and application of radar observations
[M].Beijing: Science Press.
Liao M, Lin H, 2003. INSAR - principle and signal
processing [M]. Beijing: the Mapping Publishing Company.
Oliver R L, Gang G, 2000. Freshwater blooms [C]. The
Ecology of Cyanobacteria. The Netherlands: Kluwer
Academic Publishers: 149-94.
Dekker A G, 2001. Imaging spectrometry of water. In: Meer
FD, Jong SM eds. Imaging spectrometry: Basic principles
and prospective applications [J]. Kluwer Academic:
307-359.
Huang J, Zhao R,1999. Satellite remote sensing monitoring
algae booming in Taihu Lake [J], Remote sensing
information (4):43-44.
Head, R. and R. Harris, 1999. A high frequency time series
at Weathership M, Norwegian Sea, during the 1997 spring
bloom: the reproductive biology of Calanus finmarchicus.
Marine Ecology Progress Series. 176: p. 81-92.
Ma R et al, 2008. Spatio-temporal distribution of
cyanobacteria blooms based on satellite imageries in Lake
Taihu, China. Journal of Lake Sciences (6): p.687-694.
Duan, H et al, 2009. Two-Decade Reconstruction of Algal
Blooms in China’s Lake Taihu. Environmental Science &
Technology. 43(10): p. 3522-3528.
Liu J et al, 2011. Characteristics of cyanobacteria bloom
granding and its temporal and spatial variation in Taihu Lake.
Resource and Environment in the Yangtze Basin [J]. (2):
p156-160.
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
Jin Y et al, 2009. Application of EOS/MODIS Data for
Research of Cyanobacteria Bloom Spatio-temporal
Distribution in Taihu Lake [J]. Environmental Science and
Technology (S2): p 9-11.
Qin, B. Q., P. Z. Xu, Q. L. et al, 2007.Environmental issues
of Lake Taihu, China. Hydrobiologia 581: 3-14.
Guo, L, 2007. Doing battle with the green monster of Taihu
Lake. Science, 317, 1166.
Yang, M, J. W. Yu, Z. L. Li, Z. H. Guo, M. Burch & T. F.
Lin, 2008. Lake Taihu not to blame for Wuxi's woes.
Science 319: 158-158.
Liu J et al, 2011. Risk evaluation method of cyanobacteria
bloom hazard in Taihu Lake[J] China Environmental
Science, (3): P 498-503.
Zhang, Y., et al, 2011. Temporal and spatial variability of
chlorophyll concentration in Lake Taihu using MODIS
time-series data. Hydrobiologia. 661(1): p. 235.
Duan, H., et al., 2009. Two-Decade Reconstruction of Algal
Blooms in China's Lake Taihu. Environmental Science &
Technology, 43(10): p. 3522-3528.
Kong W et al, 2009. Monitoring Cyanobacterial Blooms
Using MODIS Images in Taihu Lake, China [J]. Remote
sensing information (4): p80-84.
Ma R er al, 2010. The environmental remote sensing of Lake
water[M].Beijing: Science Press.
Hu C, Carder K L, 2000. Muller-Karger F E. Atmospheric
Correction of SeaWiFS Imagery over Turbid Coastal
Waters:: A Practical Method [J]. Remote Sensing of
Environment, 74(2): 195-206.
Hu C, 2009. A novel ocean color index to detect floating
algae in the global oceans [J]. Remote Sensing of
Environment, 113(10): 2118-29.
Piper M, Galloy M D, 2006. Solutions I V I. Introduction to
IDL [M]. ITT Visual Information Solutions.
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