remote sensing is easily influenced by cloud and rain, the
effective monitoring days and algal bloom days by
Monitoring was very different in each month in 2009, 2010
and 2011. In order to get comparable index to reflect the
intermonth variation, the month algae bloom frequency
index (MAFI) was used as a reference standard.
The figure 3(a) shows that the variation monthly of algae
bloom frequency about 2009, 2010 and 2011. The three lines
all formed the four stages: operation of low level, rising
phase, high shock, and fall period. In the period of high
shock, there are two peaks and a rock bottom, and the
difference of peak and the bottom is proportional to the
month of the bottom. There are also some obvious
differences in the annual variation. It is not same about the
time node of low level and rising phase stages. The peak and
bottom of the high shock appear in different month. At the
fall period, the line in 2009 fall fast so as to form the normal
distribution, but the lines in 2009 and 2010 are still at a
higher level in spite of falling. The January no zero value of
the line in 2011 could be seen the extension of the fall period
in 2010(the figure2 k shows the spatial space).
12
1 lh =
0.8 > db a 39 à s
; s M a —#— 2009
; i a : A
E 7 } AN 4 2010
0.4 o 3 2011
0.2 +
Fn m
0 Bom ei. am Là =
4003 04-5 6079594100112 month
a. variation monthly about 2009, 2010 and 2011
1.2
1 2009... 2010 2011
0.8
0.6
3
0
7/3 $7 01113 579114 3 5 7 9'11
Time(month from 2009 to 201 1)
b. the intermonth variation during 1998 to 1999
Figure 3 the month algae bloom frequency index from 2009
to 2011 in Taihu Lake
Figure 5 reflects the annual variation of MAFI from 2009 to
2010 years. Obviously, the Curve of 2009 has formed a
blooming cycle just only in the twelve month of 2009 year
(Some research material suggests that blooming cycle in
2008 and 2007 is similar to the situation in 2009) (Ma R et al,
2008; Duan H et al, 2009; Ma R et al, 2010). The blooming
cycle in 2010 had extended to the January, 2011. Similarly,
the value of December, 20110f Curve not fall to zero, which
could show that the blooming cycle had extended to the
January, 2012(In fact, the existing monitoring results in
January, 2012 show that the booming had happened).
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
3.4 The Time variation of algae booming in the
Subregion
Through the statistics of EBD and IBD using zoning
methods, it is easy to obtain the date of the first EBD and the
last IBD and the average of EBD and IBD in the subregion
(figure 4). The figure shows that the latest end blooming
date in any subregion is more than 350th days, which can
reflect the general phenomenon that the blooming circle is
beyond a year. The spasial distrubution subregion of the
earlier initial blooming date(8th days) is at the Central Lake,
Meiliang Bay and Gongshan Bay in 2011, that proof the
existing of lag trend in the blooming circle in recent years.
332
Westeexst o Zbheuhan — Seufhoxst Mobang — Dengshas Contreblake
a. the time variation of algae booming in the
Subregion of Taihu Lake in 2009
350
396
286 :
200
158
se.
Westecest Zhushan Southovest Meliang Gongshan Cantrailake |
b. the time variation of algae booming in the
Subregion of Taihu Lake in 2010
; 30 i i i i
Westcosit Zhuthan Southocast Melang —Gongshen Centealiake :
c. the time variation of algae booming in the
Subregion of Taihu Lake in 2011
Figure 4 the monthly algae bloom duration of each
subregion from 2009 to 2011 in Taihu Lake
Note: In the diagram, the top and low of each rectangle stand for the
average of EBD and IBD in the subregion. The top and low of each
vertical line indicate the date of the first EBD and the last IBD in this
subregion.
4. CONCLUSION
The temporal and spatial distributions information can be
fast and efficient obtained by means of the method and
