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JPRS L/9877
;~0 July 1981
East Euro e Re ort
p p
SCIENTIFIC AFFAIRS
(FOUO 8/S 1)
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JPRS L/9877
30 July 1981
EAST EUROPE REPORT
$CIENTIFIC AFFAIRS
,
(FOUO 8/sl)
CONTENTS
BULGARIA
Study of Sea-Level Fluctuations on Bulgarian Coast ~
- (Georgi Mungov; KHIDROLOGIYA Y METEOROLOGIYA, No 2, 1981) � 1
Possibilities of Determining Crop Conditions by
Aerophotometric Data
(N. S. Slavov, et al.; KHIDROLOGIYA I METEOROLOGIYA,
No 2, 1y81) is
- a - [III - EE - 65 FOUO]
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BULGARIA
STUDY OF SEA-LEVEL FLUCTUATIONS ON BULGARIAN COAST
Sofia KHIDROLOGIYA I METEOROLOGIYA in Bulgarian No 2, 1981 pp 20-31
- [Article by Georgi Mungov: "Study of the Fluctuations of the Sea Level Along the
Bulgarian Coast,'a Mediuu~ Scale Frequency ltange"]
~Text] Sea-Ievel fluctuations are the reaction of the water masses to the influen~~e
of a complex set of external forces of various intensiveness and duration. ~or this
reason they cor.sist of a variety of elements with a fluctuating amplitude and a
d~iration ranging from several seconds to months and even years. The structure of
sea-level fliictuations with a cyclical duration ranging from dozei~s of minutes to
several days is of particular practical intErest. According to A. Monin's (7)
classification, this frequency range is part of the small scale (one cycle from a
fraction of a second to several dozen minutes) and the medium scale (one cycle from
several hours to several days) variability of oceanological fields. "art of this
range corresponds to the synoptic variability of the atmosphere. It inc~udes tides,
seiches (,~ree standin� -~aves), seich-like fluctuations (forced standing waves) and
storm surges. Excluding tides, the others directly depend on the development of
atmospheric processes. They represent various long-wave fluctuations which fre-
quently appear simultaneously and whose periodical nature is usually disturbed by
storm surges. That is why the use of spectral analysis effectively resolves the
problem of the detection of the individual fluctuations and the identification of
their characteristics. ~
So far no more than sporadic studies have been made of sea-level fluctuations along
our coast. Individual studies ha.ve been made of seiches in Varna and Burgas bays
(4,5,10), with studies of the fluctuations of average daily levels (5). The present
work uses data supplied by the maritime charting system of the Main Geodesy and
Cartography Administration (GUGK, f ig 1), with two steps of 2.5 minutes and 1 hour
as the selected periods and as indicated in Table 1. Periods of high quality marine
records from the corresponding stations were selected. Spectral and reciprocal spec-
tral densities were obtained with the help of Fast Fourier Transforms (BFT)from
autocorrelation and reciprocal correlation functions in accordance with the recom-
mendations of (1;3). The Tuckey cosine-filter was used to eliminate low frequency
components in the re~ults which, in this case, were the seasonal fluctuations. The
- Parzen filter was used for the sake of obtained statistically accurate spectraZ
evaluations. The upper zero level of the coherence coefficients (3) and the confi-
~ dence intervals (1) were computed for a P= 95 percent probability. The length of
the filters (2M + 1), the cutoff points based on the correlation functions L and
and the border frequencies F~ may be found in Table 1 alsc;.
1
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Table 1. Studied Periods and Parameters of Spectral Analysis
~I,~IlNCKp~TNOCT ~2~ QyHKT ~ ~3~ [tepnoa ~4~ [l~p~.w~rp~~---.__
(
I
5~ Bapea O1 � 04 : 1979 - 15 .10 . 1979 Na4T52
6~ Hp~x cz,u+~),.~z~
~7) Bypnc Ca360
( ) A:roaoa T-360 vua (9)
f~-0.500u~q~q10)
(11) 1 wac (5) Bapea ~ Ol .10. 1977 - 01 .05. 1978 N~S11Z
_ (7) 6ypnc I (2M+1)-721
(8) Aironoa ~ L~360
T~360 qaca
J~-0,500n~q~c
Bapea Ol . 10.196a - Ol .05. 1969 N-5112
( ) 6yprac (2M+1)-721
� Ls36U
T-360 yaca (9)
- J~~0,500u~v~c (10)
) 6~pnc 124. 30 .03 . 1977 - 12 w. 07 .04.1977 N~4608
Axronon (ZM+1)~769
L~384
T~9GO MNR (].5)
- J~-0,200n/wsa (16)
- (12) 2~5 ~~8. 63N i~a ~4. 19.06. 1975 44q.23.06. 1979
P
_ 7) 6yprac N-2880
Aironon (2M+1)~481
5) BapHa L=240
7) 6ypru ~ 12K.04.06. 1989 - 12~.09. 06. 1969 Ts604 Mxe (15)
I /e~~,ZII~NqH ~1()~
-i
5) Bap Na ~ 12q. Ol . l~.1969 - 1 Z y. 06 .12 .1969
- 7) 6YPrac I N=2880
(2M+1)~481 _
7 ) 6yprac L -240
~13~Z,5 MNH. B~Axroeo~ OUu� 13.04.1978-24q.17.04.1978 T=sOO MNB 15) .
f~~OrZII~MNH ~16~
5)Bapea 12y.01 .Ol .1979 - �06.01 . 1979
8 ) A:ronoa
1. Discreteness 10. cp/hour
- 2. Point 11. hour
3. Period 12. noon
4. Parameters 13. 2.5 minutes
5. Varna 14. midnight
6. Irakli 15. minutes
7. Burgas~ 16. cp/minute
8. Akhtopol 17. 2400 hours
9. Hours
Fig 2--a,b,c--shows in all autospectra the existence of fluctuations with a period
of T= 12.4 hours--the semidiurnal tide, and T= 24 hours--the diurnal tide (the
= first, the leftmost maximum in the spectra is Che result of the prelimina.ry sifting
of initial data) . Additionally, in the winter of 1977-1978 (fig b) fluctuations
- with a period ranging from 52 to 60 hours, which are only hinted at in the other
two sCudies, are clearly visible. In (2), as a result of similar studies along the
entire Soviet Black Sea coast, it was determined that the tides in this area are
2
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forced standir.g waves of the seich type. The semidiurnal tide represents a single
seich spreading from east to west, and a southern zero line which crosses the area
between Sebastapol and Yalta. That is why the amplitude of the semidiurnal tide is
substantially higher after a gale. Changes in the spectral energy of the semidiurnal
tide in the surveyed stations was consistent with the situation noted along the Soviet
coast. It is the highest in Burgas, the same ir. Trakli an3 Akhtopol, while in Varna
it is one-half of r.hat in Burgas. In the winter seasons no substantial changes are
noted with the exception of an incrp...ase in the winter of 1968-1969 (f ig 2c). The
greater stability of the spectral energy in Burgas is explained by local morpho-
- logical conditions--a bay which cuts into the shore, which contributes to the growth
of the amplitude, and its location along the longest axis of the spreading of the
tide wa~�e (11). This also explains the reduction of the spectral energy of the semi-
diurnal tide away from Burgas and its lowest value in Varna, compared with the other
stations.
i ti... i i . ~
~ r:: ~1bH~1ii
~
_
~~r:,.,
~
: h._.~,.~,:iti~ ~
~
~ J/
I B~PM~~~
/
_ ~ _ ~ ~ 1'
~ ' i ~C
I: .:r. ! . / . ' I
~ F~.-.;.. I
:
l I ( ~ ~
~)~~~r~JJi ~ i
t } ~
~ l
;
fy \
- ~ ~ ~
,
, , ~ c~ ;
, r : ~ i . _ 42�
1 '~,.J,~ ;r~ 1
' I I:~I~~i1~l~ I ~
2b~
Fig. 1. Location of Stations Along the Coast. 1. Marine Recording Station
During the winter the energy of the diurnal tides is less than that of the midnight
tide by a factor ranging from 2 to 4. In this cases differences among individual
stations are far less. The max imum values have been recorded in Varna. In the
summer season two fluctuations of different origins--breeze and tide--developed on
this frequency of f= 24-1 cp/hour. That is why in the summer spectral energy is
higher compared with the winter by a factor of 2-4.
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As we pointed out, togethex with spectral tides, we see not axticularly clearly
manif ested fluctuations in the frequency range f=36-1 to 52-~ and even to 60-1
cp/hour. Studies covPring many parts of the world's oceans (9) have shown that
such fluctuations are widespread and are of ineteorologic2l origin (hence described
as synoptic maxi.nu.ms in the spectra). Their amplitudes and periods depend on at-
mospheric dynamics, which is the reason for their fluctuations in the different
seasons. The frequency range of f= 10-1 cp/day has been broken down by some
authors (6) into two subareas, one of which is related to the approximate statis-
tical reaction on sea level of atmospheric pressure fluctuatians (in accordance
with local conditions, in varying extents, this represents the reverse barometer
law),. wh ile the second represents the gale tides and fluctuations of the sea level
of the type of global seiches and Rossby topographic waves (sh~elf waves, double
Kelvin waves, waves blocked by :ea bottom ridges, and others). The synoptic maxi-
mum in the spectra, related to the reaction of the sea bottom to the influence of
a variety of ineteorological factors, is described by some authors also as a
meteorolog~cal or gale tide. In some cases the period of these fluctuations fluc-
tuates within a 48 hour span (two-day variability). Along our coast their presence
is most clearly marked in the winter spectra for 1977-1978 (the period T= 52 hours
for Burgas and T= 60 hours for Varna and Akhtopol, fig 2b). In the second winter
season of 1968-1969 they were quite visible in Varna (fig 2c); in the summer.of 1979
(fig 'la), which had a weaker atmospheric activity, their energy de~lined and their
period fluctuated between 48 and 52 hours. In (5) the autocorrelation function
marks only the existence of a two-day variability for the period between .'~928 and
1948. Basically, such fluctuations have a lesser amplit~de compared with the others,
as a result of which they can be identified more clearly with the help of the co-
herence functions. The reciprocal spectral analysis shows that rhe coherence func-
tions, generally speaking, show very high values in terms of tide frequencies,
where their values are similar to each other, and in the frequency range of the syn-
optic maximum (Table 2, fig 3). Only in the case of Varna we have a lower coherence
both with Irakli and Burgas. Obviously, this is due to local morphological condi-
tions. In the frequency range of the synoptic maximum the reduction of the coherence
between Varna and the other stations is considerable. Essentially, the nonperiodical
fluctuations on the sea level along our coast are formed mainly as a result of the
distribution of the atmospheric pressure and the wind field over large areas of the
adjacent waters of the Black Sea. ~'ne~lesser dependence of the fluctuations on the
sea level in the synoptic range, which indicates differences in its development
along the northern and southern coastal areas, is probably due to the increased in-
fluence of local meteorolagical and morphometric factors. As to meteorological fac-
tors, let us note that in the crossing of small cyclones in the area, the northern
and southern coast occasionally falls within different garts of the cyclone's peri-
phery. The particular feature of this frequency range is the high coherence among
all stations at the frequency of f= 36-1 cp/hour. The same frequency prevailed
during all the studied seasons, changing in value only. The synoptic maximum in
the spectra appears mainly in the studied seasons within tlie frequency range of
f= 48-1 to 60-1 cp/hour. Probably the high coherence of f= 36-1 cp/hour is due ta
the existence of shelf waves. Such waves spread lengthwise along the shelf, from
north to south, along the coast, at an average speed of about v= 45 1~/hour. The
shelf waves are a multiple-modal dissemination of energy from the initial distur-
bance of the sea level, which appears as a result of the uneven distribution (hori-
zontal heterogeneity) of atmospheric pressure, and the wind field on a given water
area. Their type, velocity and direction are substantially affected by the form and
dimensions of the basin and the shelf. In areas with a more complex configuration of
the coast and the shelf and with the stratification of the water mas~ses, if the
~
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interact.ion among the various types o~ long-wave movements on the shelf is nonl~.near,
there are both main and secondary modes which spread lengthwise and crosswise. This
explains the high coherence of the follcswing clearer frequencies: 9.7-1 cp/hour;
0.5~1 cp/hour; 4.3-1 cp/hour; 4.1-1 cp/hour; 3.2-1 to 3.0-1 cp/hour~ 2.7-1 cp/hour;
2.3-1 cp/hour and 2.1-1 cp/hour. Depending on the specific conditions prevailing
when shelf waves develop, the secondary modes appear in different frequencies and
spread in different directions during the period under study. Along with the fluc-
tuations indicated so far in the coherence functions, unstable fluctuations are also
found in the frequency range f= 19.5'1 to 15.0-1 cp/hour. In all likelihood, these
are inertial fluctuations which period for geographic latitude from 42 to 44 degrees
is between 17.5 and 18 hours. The shorter frequency range which was recorded is ap-
parently also due to the influence of the shelf and the configuration of the shore
line. All in all, the morphometric conditions along the coast are a contributing
fact~r for the appearance of a number of unstable fluctuations covering limited
areas . , ~r ~,~:^~2~
~1` ittn~;~c�x-'7?fySa:1iP114.i:12 _ ~ S~fi �I.� a t.ri 3.3 J,0 :~d 2~fi ,2.4 :2.3 I.It
J ~
. r
. ~ ~ i
I
I
;t; !!.4 ~1.6 ~
^~.b ti I
~�~~i I~'+b I~ ni
(~'~'I
I
r , ~
, i
I j O 4 I I
~ ~ ~ ~1 d ;
. , ~ ~ t i _ ~ i ~ V : ~ ~t I I
i ~ j 1~� U i
t
i ! ~ ~ j _ ~
. 1 ` + ' ~ \~1 ' I
r
N/ ^I I~ ~ I
i ~ 1 ' ~ ii-~ ~ _ _ ~ ~ ~ I
l~ '~i ~~j I
I~ I I
'�u-ti y ~
" J~~ ' ~ ~
I ~ ~ - -
`
~,~1 ;~;~~a~ '(3)
Fig 2a. Autospectra for the Summer of 1979
1. G square cm/cp/hour for f igs 2a,b, and c:
2, f cp/hQUr; 1. Varna;
2. Irakli;
3. Burgas;
4. Akhtopol
5
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(1> l _ - .
G.-n ~ ui711 f~3.;~'31 Id~t4A,l: 9 7.: n S~a {~5 ~ 3~5 ].J �LU ~?.o :.i. 2~3 '.I 2.p C2,
] G
2`~Ui F /
. ~r j
' F. :s.a 2s:~ ^n.e iis i4.a ti.e ~
~ ~ IIW I!(M1 I
'l)N) ~
IUOU I 1000~~~ i
p ~ r 11 ; I
1 ~ 1 ~ ~
~ ~ ~ r ~
~ IF
f~~ I I I ~ I I
l
iJ~"_;I ' , i ~
I ~ :AY) 1 ' i
..i~: r~t ,
; ~
rII i ! ~ ~ ; ~
~ ~
r~ ~ j i
~ . ~
~
; ~ , j
:ux~ ~ , ~ ~ ~ ~ ~ i__..~~ ~
` ~ r ~
r,;, ~
, I FI - ' _
r! i
t
. ~ ~ (
~I i
~ ;
o`- ~~:i . -
~~3)
Fig 2b. Autospectra for the 1977-1978 Winter
. ~ . , s.e a.r a,~~ z.s Z.e i.,. -7 -~.i ~`.d (2)
~ '~-i-TTT
~ /
_ ~'~Iri~
r
7 I
I
r
! ~ I
.~.v , Ll.' Il.e I
. j. ~~~ti.~.-r"rrrr~ ifyC1 ,
~ I ~ ~
� II~ - ~
` ~ r I i
i i ' 1 I I
1 ~ ~ i
~ .11 . I jll~ ~ ilUr ~ ~ ~
I 1 ~ ~ ~ 1 �
I ~i ~
, ~ , r~, I � I I
. ~ ~ ~ ~ ; , , . ,�.'~I i
m!~ ' i I ' � I
~ I 1 I ' I s = ~ -n g ~
F I I _ C ~ c _
~ ~ _
0 fl,l l.: P,S 11,~ U~S
/u/.u ~3~
Fig 2c. Autospectra for the 1968-1969 Winter
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Tahle 2. Coherence Coe~fic~ent of Characteristic ~'xequencies for the Summer Period
o~ 1979 (Reliable Intervals for P= 95 Pexcent are Given Below Each Value)
~1~ X~aKrepe~ atrort (
is.~-~~ z~,o-i w.~3~ ae--~ ao ar~~]: ~
- ~ 2~ Cbtld 11� CTI~LLO I
( 5) B~pea - HpaKax 0,810 0,890 0,550
0,659-0,888 0,794-0,937 0,300-0,716
( 6) Bapaa - 6yprtc 0,810 0,860 0,615
0,659-0,888 0,742-0,919 0,378-0,761
( NpaKax - 6yprac _ 0,g70 0,980 0,900
0,942-0.983 0,961-.0.989 0,813-0,943
(g~ 6yprac-A:ronon 0,980 0,970 0,920
0,9fi1-0,989 0,94Z-0,983 0,848-0,954
Key:
1. Characteristic frequencies 5. Varna-Irakli
2. Neighboring stations 6. Varna-Burgas
~ 3. cp/hour 7. Irakli-Burgas
4. 36-1 *_0 52-1 cp/hour 8. Burgas-Akhtopol
The situation with the series with 2.5 minute discreteness is similar. Studies con-
ducted so far of the seiches and seich-like fluctuations in Varna and Burgas bays
(4,5,10) show the following: (5), without considering the subtotal of existing fluc-
tuations, the median period of the seiches in Varna bay in 1935-1936 was 26.27
minutes, fluctuating between 10 and 65 minutes, and an average height of 20 cm with
a maximum recorded value of 107 cm (probably oi' seismic origin); in Burgas bay the
average period was 88 minutes, fluctuating between 10 and 190 minutes, with an ave-
rage height of 18 cm with a maximum registered height of 53 cm.(4) We note for both
bays four individual seiches whose interco~nection was not studied, for two non-
coinciding observation times were used. Their periods were as follows: for Varna
- bay, 23.2 minutes, 30.6 minutes, 40.0 minutes, and 138 minutes; for Burgas bay, re-
spectively, they were 94.7 minutes, 1:8.4 minutes, 121.3 cninutes and 146.2 minutes.
The first seiches resembled the fluctuations of the water masses in the bays. No
explanation is given about the others.
The spectral data analysis established the following: In all studied cases there
were a number of powerful fluctuations in the frequency range f= 170'1 to 150-1
cp/minute. The next most powerful were the fluctuations with a basic frequency
f= 100-1 cp/minute (figs 4a, 4b and fig 5). In some cases they were equal to the
previous ones and were even higher. It is within these two frequency ranges that
most of the spectral energy of the studied developments was concentrated. The other
fluctuations were considerably weaker and less stable. The cross-spectral analysis
shows t~.at the coherence functions at frequency f= 100-1 and 150-1 cp/minute also
increase going from north to south. Between Varna and the other stations they are
usually lower than the upper zero level of coherence or are sli~htly higher. For
the frequency f= 150-1 cp/minute the coherence between Irakli and Burgas was 0.397;
it was considerably higher between Burgas and Akhtopol, changing from 0.659 to
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~~ii
~ a,
Il,j '
~
- i, . .
~.o b ~
U.J ~
~ . �
~ . C~
' � i
0,5 �
0~0
t.o � d~ .
u~s '
. ' �
o.~ 'a 2~ L'r s. s 3 ~ 6 9� ~
'3. J6. ~ ~ ~ ~ -,Z @ ~ ~ ~ ~ ~ ??1::n ~ -e..~ 1 ~i-
~ Q t o.~ 4,~ . 4,l-~~L~- .
Fig 3. Coherence Functions Between Individual Stations for the Summer of 1979.
a. Varna and Irakli;
b. Varna and Burgas;
c. Irakli and Burgas;
d. Burgas and Akhtopol.
0.794. A si:milar situation was that of frequency f= 100'1 cp/minute, with the
differenc~ that the coherence between Irakli and Burgas was a random one. Some~
times, ~nstead of the fluctuations we mentioned, we find fluctuations at ~requency
f= 75 cp/minute. We must point out that in the case of Irakli, as a xesult o~
the short period of high quality observations, we have at our disp~sal only a
single period, for which reason the results must not be absolutized.
8
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/11 ~7.;m'lr,~_�~r ' Gi~~ ?.~t: l~,(i .~.i' 1�' . !:,~i , . `2~
\ / . . , ~-----�__T~_ ,
_ ~ _
~ _ i
' 1 ~
,.,~.1 1 J i
, ~
~I i
~i
. I
. i
. :i
~I ~
. � i
i~
. ~ i
- ~ ~
i ; ~
r I~ 1
_ ~ 'r~~
gi ~
I~ ~ ~
~ii~.,~~ ~ I
I
li~u~~ i
~ M~ I .
1
11~.~ ~ I
Itxh~ F I
!q~~~~
~4U jl
;W ~
tMh1 ~
I ,
~i I
~
4~~~ l ~
i
3~!~ ~
i
~ i
IV;
~ � `..r..i._.....
u ~~.~y v.l~~ u,~! 0.16 30,U
;~~r~,,~~~ ~g~
Fig 4a. Autospectra for the Period 00 hours 19 June 1979-00 hours 24 June 1979.
1. G, square cm/cp/minute-1 1. Varna;
2. T minutes 2. Irakli;
3. f cp/minute; 3. Burgas;
4. Akhtapol
In the range of the high spectral frequencies we find an entire gamut of unstable
and weaker fluctuations concentrated in the following frequency ranges: from 80-1
to 75'1 cp/minute; from 44.0-1 to 39.1-1 cp/minute; from 35-1 to 33-1 cp/minute;
_ from 22-1 to 20-1 cp/minute; 15.6-1 cp~minute, and the range from 15-1 to 11-1
cp/minute. With the exception of the first two, the others indicate a low and ran-
dom coherence between neighboring stations. In the frequency ranges from 80-1 to
75-1 cp/minute and 66-1 cp/minute, the coherence is quite high: in those cases,
between Varna and Burgas, it is 0.317 and 0.465; for Irakli and Burgas it is 0.560.
9
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..~.~~t
, ~ i �o r
~ a)
;
?;t . _ ~ti ~~.i ,ti
~....~~~+1+tiy~4�%~ /~j ;~~~1.;s:~%~.~':~.-nt~-_~. . r.~~~vJ ~
I~u
b)
~ .
u.:, ` 1 .
i �
~ - - - -
1
I~U
C~
�5
u.S
o ~ ~
~.U :~!.`~:A IS.J l?U IO.U ~~o i~.; ~i~,- 7`O J.J j~l) T min
~ I'~1
U OAi V.~ki , Q~1? 0.16 0~"0 /urmin
Fig 4b. Coherence Functions for thP Period 00 hours 19 June 1979-~0 hours 24 June 1979.
- , a. Varna and Irakli;
b. Irakli and Burgas;
c. Burgas and Akhtopol.
' This indicates that such �luctuations are probably due to secondary modes o~ sfiel~
waves spreading lengthwise along tha shore. Thei~ directi n changed 3.n the ~ndiv~d--
ual study periods. At the frequency range of 13 to 11' cp/minute, in botF~ cases,
the coherence was relatively high: 0.308 for Varna-Burgas and 0.351 for Buxgas-~
Akhtopol. The final fluctuations for Burgas represent a broad peak covering a
rather wide frequency range. In (5) we also note that they frequently appear simul-
taneously in Varna and Burgas bays. This can be explained by the different ranges
of the fluctuations in atmospheric pressure which cauaed them and the sudden wind
gusts.
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7 mm
~1.~ O,ao�~u/min'~ 96.0 48,0--J2A Y1A 19.2 16A IJ,7 1_'J~ 10.i 9.6' R.7 6.U i.q 6.a fi,q 6~(~ ~5~~~2~3 5 -
3~OU ,
J610' ~ __--3
~ � ~ ~
1 '
~ ~ 1
330p ' ~
' ~A
- ~ iil
3J000 i I I~
(b00 a ~ u .
~G ~i ~ u ~
eod i M ~
700 '1 i 1 ~ r
b(1(j :1~ ~ ~I
' ~ tl
~o ; I ~ i -
� ~oci i = ~ i ~
~ : ;I ~i?~
200 ; ~ ~
.r_: i
IOd 'i.:,R V j ~�~/`b^\
d ~ r
i:b
0,3
0,0
0 0.02 i 0.050 0.075 Qllp 0.125 Q150 0.175 0.'!00
/Wmin ~3~
- Fig 5a. Autospectra and Coherence Functions for the Period Between 1200 hours
30 March 1977-1200 hours 7 April 1977.
3. Burg;as;
4. Akhtopol.
The results of these studies may be summed up in the following moxe ;Ita~oxtant con~
clusions:
1. In the present study, on the basis of extensive empirical data, fluctuations on
the sea level along the Bulgarian coasC with a length of cycle ranging ~xom sevexa].
minutes to several days were studied. Their changes in the various seasons :in all
stud~ed stations were covered.
2. The semidiurnal tide is more clearly expressed along our coast. Its energy ex--
ceeds from a factor of 2 to.a factor of 4 the energy of the diurnal tides. Tn the
su~er, the diurnal tides are affected by fluctuations caused by the breezes, as a
. result of which at this frequency the energy hecomes commensurate with that of the
semidiurnal tides.
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- '
- - -
-
r (
G.cm~/~!nin-',:R~J :U,U 9;;1 I,.J I'!.U 10.0 ~tl,n 7,~ 6� 6.0 5.9 ~.b~2~ ,
1
~gpp ' ~ F
~n
~ A t
~a~w ~iu
. 38W , ti
37W I ~
I
~I I ~
350U ~ I
`
. gW ~
~ I ,
I
I
eao I ~J ,
500 ~ ~ ~VI
~ ~ I ~ �
III
300 ~ ,
1~
I 1
2W ~ I~
ipp l ~ I
0 ' / ~
I.U '
r%,V)
.
o,s
r
' ~ ~1 0,08 Url2. U,16 � O~YO
~"~"'m ~'3)
Fig 5b. Autospectra and Functions of Coherence Between Individual Stations for the
Period Between 1200 hours 4 June 1969 and 1200 hours 9 June 1969.
- 1. Varna;
3. Burgas
3. In the frequency range from 52-1 to 36-1 cp/hour we have a.:rather complex pictuxe.
It is probable that in the frequency of 48-1 cp/hour the reaction o~ the
sea level is most closely dependent on atmospheric dynamics. The synopt~c maximum
in the spectra for the individual seasons we studied shifts along the f~requency axis
in a range from 60-1 -48-1 cp/hour. In some atations it either entirely disap~eaxs
in some seasons or else its energy drops considerably. At frequency 36-1 cp/houx we
should expect the existence of shelf waves with a large quantity of secondary modes ,
spreading longitudinally and transversely along the coast.
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4. The fluctuations at the following 6asic frequencies are cleaxly seen: 150-1,
gp'1 -75-1 and 66'1'cp/minute. Th~ f irst two are the most powerful in terms of
spectral energy. They were found simultaneously in all the studied periods for the
- four stations and are probably due to secondary longitudinal modes of shelf waves.
The coherence of these frequencies is considerably above the upper zero leve~. Be-
tween Varna and the other atations it is lower ~han between Irakli and Burgas and,
particularly, between Burgas and Akhtopol. This proves that south of Cape Eaiine
the fluctuations at sea level are considerably more heterogenous.
S. We note in each station a number of other weaker and less stable fluctua-
tions, including fluctuations in the inertial frequencies. Unlike the former,
however, they are caused by the secondary modes of ahelf waves spreading trans-
versely along the coast.
BIBLIOGRAPHY
1. Bendat, J. and Piersol, A. "Izmereniye i Analiz Sluchaynykh Protsessov" [The
Measurement and Analysis of Random Processes]. Mir, Moscow, 1974.
2. German, V. "Spectral Analysis of Fluctuations on the Level of the
Black and Caspian Seas in the Frequency Range from One Cycle Over Several Hours
to One Cycle Over Several Days." TR. GOIN, No 103, 1970.
3. Jenkins, H. and D. Watts. "Spektral'nyy Analiz: Yego Prilozh~niya" [Spectral
- Analysis and Its Applicationa]. Mir, Moscow, No 1, 1971; No 2, 1972.
4. Kostichkova, D. and Cherneva, Zh. "Long Period Fluctuations on tlle Sea:Level
in Varna and BurgaL Bays." OKF:ANQLOGIYA, No 6, Sofia, 1980.
5. Krusteva, E. Rezhim na Nivoto na Cherno More Okolo Bulgarskoto Rraybrezhie"
[Regimen of the Black Sea Level in the Vicinity of the Bulgarian Coast].
Dissertation. Sofia, 1978.
6. Lappo, S. "Srednemasshtabnyye Dinamicheskiye Protsessy Okeana, Vozbuzhdayetnyye
Atmosferoy" [Medium Scale Dynamic Ocean Processes, Triggered by the Atmosphere].
Nauka, Moscow, 1979.
7. Monin, A. "Classification of Nonstationary Processes in the Ocean." IZV. AN
SSSR, Earth Physics Series, No 7, 1972.
_ 8. Mungov, G. "Determination of Maximum Sea Levels Along the Bulgarian Coast."
KHIDROLOGIYA I METEOROLOGIYA, No 6, 1980.
9. Prival'skiy, V. "On the Spectrum of Irregular Sea Level Fluctua.tions." TR. GOIN,
No 103, 1972.
10. Rozhdestvenskiy, A. "Changes in the Water Level in Varna Bay." IZV. PO
RIBOWDSTVO I RIBOLOV, V, 1964.
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11. Knauss, J. "Introduction to Physical Oceanography." ~rentice-Hall, New
Jersey, 1978.
Received by the editors on 20 September 1980.
Copyright: Glavno upravlenie "Khidrologiya i Meteorologiya" 1981
c/o Jusautor Sofia
5003
CSO: 2202/14
1~
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.BULGARIA
POSSIBILITIES OF DETERMINING CROP CONDITIONS BY AEROPHOTOMETRIC DATA
Sofia KHIDROLOGIYA I METEOROLOGIYA in Bulgarian No 2, 1981 pp 76-83
[Article by N. S. Slavov, A. D. Kleshchenko, Kh. B. Spiridonov, 0. V. Virchenko and
N. G. Vulkov: "On the Possibilities of Detezmining the Condition and Productivity
of Farm Crops Based on Aerophotometric Measurement Data"]
[Texe] The agrometeorological observations, which are currently used, provide
- information on the condition of farm crops._for a specific spot only. Because of
the great spatial variability of agrometeorological elements, such information does
not off er a precise idea of the size of these elements in accordance with the area
they occupy. Furthermore, the existing methods used in agrometeorological observa-
tions are mostly visual, for which reason they are rather subjective (8,13,14). This
calls for the elaboration of remote control methods which will enable us to obtain
information for the entire area in crops.
f~.
/~,i~fl1) ~ O',~
o., r ,
,
; ~3 ~ .
o,a I ; ~
ll ~ .
u.~~ ' ~ : ~ �
~
- I ~ / ~ ~ ~~'11' I . ~ I ~ �
~,,i ~ ~ I I ~
_ . -o ~ � ~ ~ I
: ~
O - . _ ~ ' ` _ __i ~ 0 40 60 l00 P. i
;lk~ :wG .,a~ ~~s, e ~a ~.!i: ! ' ~
Fig 1. Spectral Brightness Curves for .Fig 2. Aspect of the Correlation Be-
Some Farm Crops tween Spectral Brightness and
Plant . P% Cover of Desert and
1. Corn; Semi-Brush Vegetation with h0=
2. Potatoes; 30-35 in the 590-680 nm spectrum
3. Winter wheat; zone.
4. Meadow-podzolic soils;
5. Chestnut-color soils;
5. Ordinary chernozem ~5
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The remote control methods for ohtaining infot~nation on the condition o~ the surface
are based on measuring the energy o� reflection and radiation in the various sectors
of the electromagnetic spectrum. Virtually any natural formation has its own speci-
fic spectrum and a plant com~nunity has a specific course of spectral reflection char-
acteristics. They are determined by the ecological structure of agrophytocenosis,
the phenological development of the plants, the structure and entrophytopathological
condition of the agrophytocenosis, the color of the soil, the brightness and other
factors. This enables us to use spectral reflection characteristics in resolv~ng a
number of problems such as def ining the structural characteristics of the phytoceno-
sis, the assessment of its phytopathological condition, the identif ication of vegeta-
' tion and others.
Ground and aerial spectrometric studies ~3) indicate that the structural characteris-
tics of the vegetal cover (projected coverage, leaf-density indicator, height and
others) properly correlate with the spectral brightness (fig 2).
The photometric methods developed by the USSR (1) is based on the correlation among
spectral brightness coefficients (SKYa), i.e., on the ratio between the brightness
on the surface of an ob~ect in a given direction and the brightness of an ideally
~ dispersing surface of the standard used for the specific soil system--the vegeta-
tion within the parameters of the vegetation cover, the vegetation mass above a11.
The analytical formula which describes the physical nature of the correlation be-
tween the spectral brightness coefficients and the vegetal mass, providing that the
plant co~unity may be considered the approximation of a'.disperston enviro~ent stra-
tum, has the following aspect (2):
_ ro~/r?s- 1)+~rv-rs)e-~mo
rvf (fn~s-l~~-(~v-~s)~ve Ema '
In which:
r~S is the SKYa of the soil-vegetation system;
r is the SKYa of the vegetation;
rs is the SKYa of the soil;
m is the ground vegetal mass per unit area. quintals per hectare;
a is the constant for a given plant co~unity,
1-ro .
E _ ,o
The closeness of the ties between the reflection charac+ceris~tics of the vegetal
cover and,consequently, the error of this method, depenci on the size of the contrast
between soil and vegetation. With contrasts of 0.5 or more, the link between the
brightness coefficients and the parameters of the veget~~l cover may be expressed with
the help of the formula we cited. In order to reduce thp influence of the brightness
conditions, the condition of the atmosphere and the level of cultivation and moisture
of the soil an this dependence, we use the correlation bet~:teen the brightness coeffi-
cients in two sectors of the spectrum (10,12) instead of th~~ brightness coefficient.
The most effective sectors within the spectral range of 400-1v200 nm are thoae with
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wavelengths o~ 670 and 750 nu~. In such cases the dependence o~ the correlation
between the br~ghtness coe~~~cients o~ the soil-vegetation ~ and the parameters
of the vegetal cover may be expressed with the formula (10,1
Kos = K~-{- (K, - K~)e-d^ ,
in which Ky is the ratio between the brightness coefficients of the vegetal cover
in two sectors of the spectrum;
KS is the ratio between the brightness coefficients of the soil in two spectral sec-
tors;
m is the parameter of the vegetal cover;
a is a constant.
Calibration is used in the application of the soil method. It consists of the simul-
taneous determination of I~S, KS and m covering the same areas and the charting of
_ graded curves on the basis of such data. An instrument aboard an aircraft is used
to measure the Kys and K for each territory and the curves are used in determining
the productivity of the ~arm crops. Their identification from the air is done
visually by the operator who determines the beginning and the. end of the measure-
ment in accordance with the length of the field planted in a specif ic crop. The
remaining recording process is automated and offers us data saitable for operative
processing aboard the aircraft (5).
Currently aerophotometric surveys of farm crops and desert-pasture vegetation are
regularly conducted in central Asia, Kazakhstan, and the European part of the USSR.
The data are transmitted to the operative organs of the Hydrometeorological and
Environmental Control Administrations and the USSR Hydrometeorological Center. The
photometric method is used in defining parameters such as the size of the vegetal
mass and the area of the leaf surface, which are closely correlated with farm crop
yields. This is confirmed by studies conducted in the USSR for determining the
correlation of average oi~last values of yields and average oblast values of the vege-
tal mass, obtained as a result of the surveys conducted by the VNIYSKhM (6).
Table 1. Coefficient of Correlation r, Average Error of the Regression Equation sy
and Constants k and b for Winter a and Spring b Wheat in the Ear Forming
Stage in the Various Parts of the European Territory of the USSR
~1~ P~Aonr r I SY K I "
I
_ a I 6 I a I 6 a I 6 I c I 6
i i
~2~ LI~8Tpa11NH I
eevepaoaeLxw o6nactN 0,75 0,73 i 2,4 3,0 0,15 0,18 i 2,32 2,23
(3) Uearp~nH~ I
vep�oaes+Nx o6nacrx ~ 0,91 0,81 l 2,~ 3,9 0,09 0,21 I 9,15 j 2,29
- Key:
l. Area
- 2. Central nonchernozem oblasts ~
3. Central chernozem oblasts
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Under the existing agrotechnology the link between the vegetal mass and grain yields
is of a linear nature. Tatale 1 shows the values of the correlation coefficients and
the mean errors in the regression equations for winter and spring wheat for the
chernoze~ and nonchernozem zones of the liSSR. These correlations are used for fore-
casting winter and spring wheat yields. These correlations, together with data of
aerophotometric surveys arorrelationshhave beentobtainedsfor~othernareascofdthe~USSR
- of farm crops (7). Such c
as well (9,11).
In 1979 a number of inethodical oper.ations were carried out to enable Bulgaria to use
� the photometric method for determining the parameters of the vegetal cover over large
areas, based on the soil and weather conditions of our country. The initial opera-
tions were carried oua Okruhe tTheicharacterist csIofLtheseSprojectsc ere astfollows�
plex in Knezha, Vrats $
1. Levent wheat, 400-450 plants per squ~re meter (p/m2) in the full maturity stage,
with plants entirely yellow. Heavy weed infestation. Flattened crop.
2. Kubrat wheat, with more than 500 p/m2. Mature plants, yellowish. Low weed infes-
tation and slight flattening.
3. Levent wheat, with more than 450 p/m2. Ripe plants, yellowish. Low week infesta-
- tion but heavily flattened.
4. tllpha-stubble barley, low weed infestation.
S. Knezha 2 1-611 hybriden rlantsth L weweedninfestations Per decare, 14th-15th
leaf stage, healthy, gre p
6. Knezha 2 1-611 hybrid colantsCh Loweweedninfes~tationts per decare, 12th-14th
leaf stage, healthy green p
7. Peredovik sunflower, ~aith more than 4,000 plants per decare, in the blossoming
stage, not~eal healthy plants. Low weed infestation.
- 8. Knezha 2 1-611 hybrid corn with 2,500 plants per decare, 14th-16th leaf stage.
Healthy plants, no weeds.
9. Knezha 2 1-611 hybrid corn with 4,000 plants per decare, 14th-lSth leaf stage.
Normal plants, weed free.
10. Knezha 2 1-611 hybrid corn with 5,500 plants per decare, 14th-15th leaf stage.
Weed free, normal plants.
11. Knezha 2 1-611 hybrid corn with 7,000 plants per decare, 14th-15th leaf stage.
Weed free, healthy plants.
12. Knezha 2 1-611 hybrid corn with 8,500 plants per decare, 14th-16th leaf stage.
Weed free, normal plants.
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The measurements weace made from an airplane ~rotn points 1 to 7 and on the ground from
points 8 to 12. On the ground.measurements were made to detezmine the dependence be-
tween the correlation of the brightness coefficients in the two sectors o� the spec-
trum and for different parameters of the vegetal cover: thickness of the crop, leaf
area and ground biomass, used for charting the curves.
_
~.R 4 i,
~ ia . ~
. ~
~oI ~ ro ,
i ~ .
p~ � . � 8 . .
1 ~ � �
oj � � , 6 . � �
I
aj ' ~ � ,
2
~
, o.~. ~.u S.u C10 L m~lm� 0 I : J , .i o " a 4 10
n~~
Fig 3. Relation Between the Correlation Fig 4. Graphic Representation of the
- of the Brightness Coefficients Correlation Between the Bright-
of the Soil-Vegetation and the ness Coefficients of the Soil-
Area of the Leafy Surface of the Vegetation and the Density of
Corn ~ the Corn Crop
K� ~ . , .
I � '
~ ~ .
_ ~ ~
.
i~~ ~ � . ~
i � ~ �
. . .
r= �
~ . � � . .
r, .
.
; t'
a. .
L_~_"'~_.'~- i~~._1 Lr
` ~ _ ~ i ~ ~ y 1 u 1 I 1_ hA'
- Fig S. Connection Between the Correlation of Brightness Coefficients Between the
Vegetation and the Biomass of the Corn Crop
The measurements were made with a DTF-1 twin-chanr~el photoelectric photometer. The
optical design of the photometer is described in the methodical instruction (10).
The photoelectric current of the photoelements was measured on the ground with the
help of the M-194 microamperemeter, and aboard the aiz~craft with a single channel
KSP-4 potentiometer. The photoelements and light filters were selected in such a
way that the effective wavelength of the first channel would be in the red part of
the spectrum 650 while the other channel was in the in�rared section of
r.he specr.rvm ( 7~ = 750-850 nm). Fine sand laid on a sticky surface with known
brightness coefficients was used as a standard.
The charts of the relationship between the correlation of the brightness coeffi-
cients of the soil-vegetation system and the parameters of the vegetal cover of the
corn were based on ground measurement data: crop density, plant height and size of
19
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the leafy surface. The amount of the vegetal biomass was not measured. That is
why the product of the height of the plant and the density of the crup was taken as
a characteristic of this value.
The graphs showing the connection between the ratio of the brightness coefficien~
and the area of leafy surface are shown on fig 3. We can see that the connection.
is quite close in a correlation relation of n= 0.81 and a correlation ratio error
of + 0.06. Fig 4 shows the graphic connection between the brightness coeff icient
correlation and the density of the crop. But this is the closest connection with a
correlation ratio of n= 0.82 with an error of + 0.05. Fig 5 shows the graphic
connection between the correlation ot the brightness coefficients and the computed
vegetal biomass. This is the least close connection, with a correlation ratio of
n= 0.72 and an error of + 0.09. The curves were computed on the basis of these
data. The values for the area of the leafy surface, crop density and size of the
vegetal biomass can be computed on the basis of the curves and the values of the
_ brightness coefficients of other corn crops, and crop predictions can be made.
Aircraft measurements with a twin channel DTF-1 photometer installed aboard an AN-14
airplane were conducted at heights of 100, 200 and 500 meters and recorded with the
help of a single channel KSP-4 potentiometer. The most successful results were ob-
tained at a 500-meter altitude. Table 2 indicates the results of these measurements.
Using the ratio between the brightness coefficients as given in the table and the
curves in figs 3, 4 and 5, we obtained Che values for the area of the leafy surface,
crop density and ~ize of the vegetal biomass,: shown in the last graphs of Tab1e 2.
All of this leads to the following conclusions:
l. The experiments conducted in our country, in the area of the scientific and pro-
duction complex in Knesha, conf irm the possibility of using the photometric method
in determining the parameters of the vegetal cover. A close correlation was ob-
tained between the ratio of +�he brightness coefficients and the size of the area of
the leafy surface and the de:~nsity of the crop. These correlations may be used in
determining the area of the leafy sur1.'ace and the density of the crop on the basis
of determined brightness coefiicient~, from an airplane.
- 2. Further studies must be made on the influence of the various factors in obtain-
ing correlations influenced by the amount of light, soil moisture, type of soil,
fertilizer, phases of plant development, parameters of the vegetal cover and others
in formulating a method for determining the parameters of the vegetal cover with
the help of photometry under the conditiona prevailing in our country.
20 .
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Table 2. Results of Aircraft Measurements of Brightness Coefficients for Some Farm
Crops _ _
1~. G ~ ~ �
~ + r e ~ N
~ 8 ~D O N N
Z --aC00- v = 3
. 7~A uj T a e n o
_ A S S
_ a o ~ '
- N ~ ' N ~O R V p N
I"~7 ',fi` ~.r ~ j S L y V
~ ~ 'l}' ~ ~ - ~ e : '1 Y
Y a Q
7 f ~ V
~ ~ u y a
I~..~'~M I~ Nu~N'J'~) ws y Z o
I~^ a' 7' C:D ~ ,s. u ~ F u
I ~ �
i1 S G Y' M O
1~ h M ~
O q ~ x p,o
`/~w ~ M~ONJ~ q~. ~ ~ ~
Z ~ '~l 1~ = u v y~
6; C7 'V' V' F y ~~V ZTTI
~ O S ~ ~
71 r} � -
v . ~ ~ ~ i
I ~ u
~OOOCV ~ u Y
c M M tf~ YL y= ~
I r ` ~
1 I . ~ Y S
~ _ ]I � '
> > e O
_ ~ N V N V~+~� Y
- ~.s~ _ cO M N 01 i ~ _ ~ ~
Clu~~lat ~ ~ ~
J:' r. CV N f'1~ ~ ? o
~ ~
v= M A = L
S h
~ _
4 V F G ~ Y~
6 w Y Y ~
Y. Y ~ CO?ftnYQ~OJ h~ a~ 4 G
z Y G? CV t0 t~ M M u ~ C s: I
~ :'7 ~A N h:C 40 00 - ~ v z ~ ~
~ n T q
= O 4 i a O
I~~ a as
~ Y' �~00^~~0000 ~u a~~ n
s
I~j L~~ 070000CCC ga d=~ u
Y � ~ ~ u ~ ~
I - i � ~ u 7 !
~O z = ~ {
0
a e c e, '
vL : o e 3
x ~nnx-ra~-raoa~x ;o � =
Q~ ? Q' 1'7 C'7 7 V~ P~A S� � u J v
~ 0~0000000 =7 = - i
Y ~'1 � ' ,F', ~ o a
I ~w ~ 3 O 6= a
I , w y '
M = G ~ ~0
~ 9 S 1 0 ~ t
y."x~ ~ MNM~NC~~~r oa~ s = ~ ~
I ~ I GOCOOCO00 pa = ~
' =s u a ~ _
~ A N S S ~ ~
I ~ I ~ u ~ '
av i ~ryT00nS NMtOaO Ay$J~~ 6
I Y Y+ I O t ~ y a
S iS �
s g Y
~ - ~ o r
t - w r ~r~j~~....~` z
~ I N~~v~~GOhN =s Y @ _
~~,M Y ~ OnOiMcocDNV;t~ F=~ ~a~ _
i ~ _ 0~ ~ ~
_ y J~ u o F
~ i 0.r.h1n~~ ~ Y f~j u y ~
~S ! O~ONtGOiCVC.00 y ~
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! I __r ~Y Y ; o s'Y
I I = ~ ~ ~ .I
~y F _ s
' I �
~ s~ o~ s e o=
x
i a ~ q ~ ~ u '
: e I ~a 7~ iG.. I a q i~ s
' � ~ - ~ = s z ' s O Y O � S ~
~ = Y ~ S= m'~7 m]~ ? = F~ � y
G, v v u^- s< s
' uia,,q aaa A � ~+~a ~
I l~ io io ~ a~q N t s-
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v ~iw~~v~r~~
- ~ ~~u1 ~O~O~O I~
~--I r-~I r-i ~'-1 r-~I r-I ~-Ir-I ~--I
vw`iw~~~~
21
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Key:
1. Crop 10. Density of the crop determined
2. Brightness coefFicient of the according to the curves
vegetal cover in the infrared 11. Actual crop density
part of the spec~crum 12. Biomass determined from the curves
3. Brightness coefficient of the 13. Biomass determined on the bas~s of
vegetal cover in the red part actual data
of the spectrum 14. Wheat
4. Brightness coefficient of the 15. Stubble
soil standard in the infrared 16. Corn
part ~f the spectrum (26.0) 17. Sunflower
- 5. Brightness coefficient of the
soil standard in the red part R~- _
of the spectrum (30.0) r --correlation of the
- 6. Brightness coefficient of the brightness coefficients
sand standard in the infrared in the soil-vegetation
part of the spectrum (0.393) system
7. Brightness coefficient of the
sand standard in the red part
of the spectrum (0.330)
8. Leaf surface, determined from
- the curves
_ 9. Actual leafy sur�ace
BIBLIOGRAPHY
l. Belyayeva, N. P., Rachkulik, V. I. and Sitnikova, M. V. "Method for Determining
Crops of Desert-Pasture Vegetation." Authorship Certificate No 185142, 1965.
IZOBRETENIYA, PROMYSHLENNYYE OBRAZTSY, TOVARNYYE ZNAKI, No 16, 1966.
~
2. Belyayeva, N. P., Rachkulik, V. I. and Sitnikova, M. V. "Connection Between
the Brightness Coefficient of the Soil-Vegetal Cover System and the Amount of
Vegetal Mass." METEOROLOGIYA I GID80LOGIYA, No 8, Moscow, 1965.
3. Vinogradov, B. V. "Remote Control Indication o� P~ant Productivity in the
Visible Area of the Spectrum." Collection "Problemy Fiziki Atmosfery" [Problems
of Atmospheric Physics], No 9, Leningrad State University, I,eningrad, 1971.
4. Kovalenko, V. A., Kleshehenko, A. D. and Virehenko, 0. V. "Automated Systems
for Remote Control Measurements in Agrometeorology." METEOROLOGIYA I
GIDROLOGIYA, No 9, Moscow, 1974.
5. Kleshchenko, A. D. et al. "Metodicheskoye Posobiye po Opredeleniyu Parametrov
Rastitel'nogo Pokrova Aerofotometricheskim Metodom s Pomoshch'yu Automatizi-
rovannoy Sistemy Registratsii'.' [Methodical Aid for Determining the Parameters
of the Vegetal Cover Through Aerophotometry, with the Help of an Automated Re-
cording System]. Gidrometizdat, Moscow, 1975.
_ 22 ,
r
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6. Kleshchenko, A. D. "Link Between the Ground Vegetal Mass of Grain Crops and
Grain Crop Yields." TR.UDY IEM, No 7(66), 1976.
7. Kleshchenko, A. D. and Yemil'yanova, L. I. "Assessing the Condition of Grain
Crops in Terms of Grain Yields." TRUDY IIIK, No 13(91), 1979.
8. "Instruction to Hydrometeorological Stations and Posts,"~No II, Leningrad, 1973.
9. Rachkulik, V. I. and Sitnikova, M. V. "Connection Between the Brightness Coeffi-
cient of a Cotton Field and the Cotton Crop Yield." METEOROLOGIYA I GIDROLOGIYA,
No 11, Moscow, 1966.
10. Rachkulik, V. I. and Sitnikova, M. V. "Metodicheskiye Ukazaniya po Opredele-
niyu Paxametrov Rastitel'nogo Pokrova Metodom Otnosheniya Koeffitsientov
Yarkosti v Ilvukh Uchastkakh Spektra" [Methodical Instructions for Determining
the Parameters of the Vegetal Cover Through the Method of the Correlation ~
Between the Brightness Coefficients of ~ao Sectors of the Spectrum]. Tashkent,
1972.
11. Rachkulik, V. I. and Sitnikova, M. V. "On the Relation of the Green Wheat Mass
and the Grain Crop Yield." TR. SARNIGMI, No 64(79), 1972.
12. Rachkulik, V. i. and Sitnikova, M. V. "Some Problems of Determining From Air-
craft and Satellites the Biomass of Desert Pastures and Farm Crops."
METEOROLOGIYA I GIDROLOGIYA, No 6, Moscow, 1976.
13. "Rukovedstvo po Provedeniyu Visual'nykh Aviomarshrutnykh Agrometeorologicheskikh
IbsledQVaniy" [Manual for Visual Agrometeorological Studies from the Air].
~ GIDROMETIZDAT, Mascow, 1971.
14. "Uputvane za Agrometeorologichni Nablyudeniya" [Instruction for Agrometeorologi-
, cal Observations]. UR1iM, Sofia, 1960.
Received by the editors on 26 June 1980
Copyright: Glavno upravlenie "Rhidrologiya i Meteorologiya" 1981
c/o Jusautor Sofia
5003
CSO: 2202/14 ~D
23
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