The presentation is qualified during his (Ganbat Bavuudorj) master thesis work in 2012. The master program was sponsored by DAAD at NUM and Heidelberg University.

1. Ulaanbaatar
Inspector:
Ganbat Bavuudorj, Engineer of the Agro-meteorological section,
Institute of Meteorology, Hydrology and Environment
Supervisors:
Chuluun Togtokh, Professor of the National University of Mongolia
Troy Sternberg, Desert researcher, British Academy Postdoctoral Fellow, University of Oxford
Drought assessment in Mongolia using geometric VHI,
were TCI and VCI dissipative
MASTER THESIS
National University of Mongolia
School of the Earth Sciences
Department of the Geo-Ecology and Environmental Study
International Master Science program on Environmental
Science
21.May.2012

2. For Mongolia, the drought or lack of rain negatively impacts on vegetation cover, agriculture and social status, causing various
weather phenomenon in particular areas in long period. These negatively impact on aimags, where pasture farming plays as a major role.
Several Mongolian scientists considered the drought as anomaly of long term rainfall and temperature and estimated it by Ped’s index.
It is better to assess drought by one or more indicators, which are not dependent each other.
In most recent years, assessment of the agricultural or pasture conditions by satellite data at the bag level (smallest administrative unit in
Mongolia) is getting necessary.
We taken the surface temperature and plant condition into this study that organizing ecosystem healthy state.
Ecosystems are emerged due to self-organizing act which is resulted from gradient difference between sun and earth temperature.
Ecosystems structure has been developing to the path which decreased temperature gradient of the system. Due to this paradigm,
temperature has necessary and adequate to describing ecosystems health condition.
Prigogine and others have shown that dissipative structures self-organize through fluctuations and instabilities which lead to bifurcations and
new stable system states. Glansdoff and Prigogine (1971) have shown that these thermodynamic systems can be represented by coupled
nonlinear relationship i.e. autocatalytic positive feedback cycle, many of lead to stable macroscopic structures which exist away from the
equilibrium state (James Kay).
Wicken (1987) noted that living systems are a unique example of dissipative structures, because they are self creating, rather than a
product of only impressed forces. Life is a self-replicating system, operating through informed pathways of autocatalytic thermodynamic
dissipation (James Kay).
Thus, VHI (Vegetation health index) was congenial indices which expressed by two parameters those dependent each other. So to
offered suggestion using the geometric mean for vegetation health condition. Finally, VHI is calculated as the geometric mean of the two
indexes that replaced the arithmetic mean.
Unlike the old VHI, the new in case of VHI based on the geometric mean takes into account differences in achievement across two
dimensions. Lower value in any dimension is now directly reflected in the new VHI, which captures how well an area performance is across the
two dimensions. A low achievement in one dimension is not anymore linearly compensated for by high achievement in another dimension. The
geometric mean reduces the level of substitutability between dimensions and at the same time.
VHI has been calculated using VCI (Vegetation condition index) and TCI (Temperature condition index), which are able to identify
from 250 and 1000 meter MODIS data. LST (Land surface temperature) data had been used for calculation of TCI index, based on that
temperature of ground surface impacts on the biomass. VHI index of Shiluustei soum (soum – administrative unit in Mongolia) is good
indicated by ecosystem reduction and its momentum of geographical spreading and has middle sized area field in Mongolia and it determined
with 44608 grids. The result of this study showed that, VHI index had high (r=0.79) correlation with variation of biomass anomaly based on
data of Darkhan station from 2000 to 2011.
The results indicated the drought condition in Mongolia through VHI mapping.
Abstract

3. Outline
Source: Adapted from Wilhite (1999).
This study has two major goals.
The first goal is to assess drought using remote sensing
enhanced indices; Temperature condition index (TCI),
Vegetation condition index (VCI) and these entire Vegetation
health indices.
The second to produce other additional useful maps.

4. Introduction
Drought event in Mongolia
A phenomenon known in Mongolian as a 'Dzud' - severe summer
drought followed by heavy snow and extremely low winter
temperatures - has affected 19 of Mongolia's 21 provinces.
During the period from 1999 to 2002, Mongolia experienced a
series of droughts and severe winters that lowered livestock
numbers by approximately 30% countrywide. In the Gobi region,
livestock mortality reached as much as 50% with many
households losing entire herds.

5. Introduction
Although the temperature or evapo-transpiration are generally included in drought index calculation, and precipitation is most
important measurement.
For drought condition evaluation used the remotely sensed data which defines the greenness difference of plants. Drought is
anomaly of long term of climatic indicators such as, precipitation and temperature. So, some researchers taking the Ped’s index for
which choosing a criterion of drought.
Kogan.F and other researchers obtained vegetation health index which can consider multiple indicators in 1995. That offer to
opportunity approves vegetation stress so forth it can to release a drought from more than three decades. For classification of
agricultural drought used intensity of VHI and showed in Table 1. (Kogan.F 2001, Bhuiyan.C 2006)
Table 1. Drought intensity.
VHI is opportunity to evaluate for drought and early warning, higher indicate with plant growth condition, ecosystem
productivity, temperature and precipitation (Kogan.F, 2008).
Kogan.F, Jargalsaikhan.L, Dugarjav.TS and Tsooj.S whose figured out the correlation coefficient is 0.89 close up to 0.9
between VHI and anomaly of pasture biomass in four natural zones from NOAA/AVHRR it from 1985-1997.
VHI has a preeminence with two multiple parameter of precipitation and temperature than other remote sensing drought
indexes.

6. Study area
The Great Mongolian territory contains extensive region of several
landscape, and is located in the north part of the Russia and south-
eastern part of the China (Fig. 1). In the present study in the rectangle
which were included fraction of Russia and China. The rectangle area
locates in the central Asia in between 51° 53' N, 87° 18 E' to 51° 53'
N, 87° 18 E' and 41° 20' N, 89° 12 E' to 42° 23' N, 119° 48 E', covering
about 2,700,000 km2 area.
The country has approximately 257 cloudless days a year, and it is
usually at the center of a region of high atmospheric pressure.
Precipitation fall higher in the north (average of 200 to 350 millimeters
per year) and lower in the south regions which ranges between 100 to
200 millimeters annually. Most part of the country is hot in the
summer and extremely cold in the winter, with January averages
dropping as low as −30 °C (−22 °F).
Figure 1. Study area.
Figure 2. Climate graph, Mongolia.

7. Methodology and used data
The Land surface temperature (LST) was computed from the brightness temperatures in the
thermal channels by a split-window algorithm (Price, 1984) form:
Where,

8. Kogan (1994) has suggested the Vegetation Condition Index (VCI) for assess the vegetation condition.
Kogan (1995) adapted the VCI normalization approach to LST and developed the temperature Condition Index
(TCI).
Following the above-mentioned hypothesis, Kogan (2000) proposed another index, the vegetation Health Index
(VHI), which is used arithmetic mean for an additive combination of VCI and TCI.
The VCI, TCI and VHI indices estimating cumulative humidity, temperature and total vegetation health conditions
respectively on a scale from 0 (extreme stress) to 100 (favorable condition) with 50 corresponding to average condition
(Tab. 1).

9. The use of a geometric mean "normalizes" the ranges being averaged, so that no range
dominates the weighting, and a given percentage change in any of the properties has the same effect on
the geometric mean.
The geometric mean is always less than the arithmetic mean (except of case if all the data points have
an identical value).
Figure 2. Differences of geometric mean and arithmetic mean.
The application of the geometric mean is similar to
the compounding process of interest rates on a savings
account. The geometric mean is used any time several
quantities multiply together to produce a product. In the
above example the TCI=10, VCI=90 arithmetic mean is
55 but the geometric mean is 30. Two dimensions far
from the each other geometric mean consider their
dependence and give less value. Other way TCI and VCI
have similar value geometric mean gives close to their
arithmetic mean.
Chuluun Togtokh’s suggestion geometric mean fitting than mathematic mean in case of your study

10. The overall drought management process and decision sequence is described fully through the use of flowcharts. Figure
1.5 below shows the since pre-processing until to last products.
Figure 2. Flow chart showing the working scheme.

11. Results of the study
4.1 Temperature Condition Index (TCI)
Temperature is the main driver of many biological processes, namely chemical (enzyme-catalyze) reactions, which usually
increase plant maturation (Badeck et al. 2004).
Figure 2. LST/MODIS and observation temperature (a. mapping method Gantsetseg.B,
Ganbat.B, measured temperature by ground observation, b. LST from satellite).
The study of the LST is a very interesting subject for applications in many fields of
natural sciences, environment and agriculture. The surface temperature is a main
indicator of the surface energy balance of the Earth.

12. The weather station’s air temperature was compared with the LST in order to find a correlation
between the 2 m air temperature of 130 stations and satellite derived LST. That revealed result showed high
correlation with a linear regression and showed in the Figure 3.
Figure 3. The graphic representation of the correlation between Tair, and LSTmodis of 130 stations, respectively
Julian day 161, 193, 241 (09 June 2002, 11 July 2002, 28 August 2002).
The TCI derived from 500 meter resolution 8 days composited from the LST. TCI values close to 0 indicating a harsh weather
conditions due to high temperatures during the composite period, middle values reflecting normal favorable conditions as 50 and
high values close to 100 reflecting mostly favorable conditions.

13. Stress
Favorable
2003 оны157 дахь өдрийн зураг нь 2000-2011 оны хоорондох 12
жилийн хугацааны боломжит халалт, сэрүүсэлтийг харуулна.
0-6 extreme hot /equal to last twelve year maximum/,
6-12
12-36
36-60 Optimal , on average
60-84
84-100 favorable condition
Optimal

14. TCI
2000201
TCI
2000185
TCI
2000193
TCI 2000185-2000201
TCI2000185-2000201 зураг нь 2000 оны 7.3-7.23-ны
хооронд 24 өдрийн турш халсан өдрийн зураг
Dry year
Composition
of 8 days
Temperature condition index during a month

15. TCI
2008201
TCI
2008185
TCI
2008193
TCI 2008185-2000201
TCI2008185-2008201 зураг нь 2008 оны 7.3-7.23-ны
хооронд 24 өдрийн турш халсан өдрийн зураг
Favorable year
Temperature condition index during a month

16. VCI is expected to be a better indicator of drought than NDVI for it
reflects the vitality of the vegetation in comparison with the best and
worst conditions over the same period in different years. Also was
observed in the present study for individual Darkhan station.
VCI time series is better along with series of the pasture biomass
anomaly and in Figure 8 figured VCI and Biomass of the Darkhan
station. The VCI characterizes moisture conditions and it has slightly
larger correlation with a biomass anomaly than TCI. It can be indicated
that the 2008 was considerable a biomass due to much higher rainfall
(favorable), in opposite the insufficient biomass with low rainfall
observed in 2005 (stress or drought).
4.2 Vegetation Condition Index (VCI)
The NDVI data have been extensively used for the drought monitoring in various areas of the world and good correlations
have been established between NDVI or VCI and precipitation (Karabulut, 2003; Wang et al., 2003).
STRESS FAIR FAVORABLE

17. 2005193
2000193
2008193
wide
stress
cool year
Figure 7. The spread comparison between TCI and VCI
conditions in 11 July (a, b are dry and c is favorable).
TCI VCI
TCI
VCI
hot optimal chilly
Stress fair high biomass
y = 1.0329x
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
TCI
VCI
Regression of the VCI, TCI grassland in Mongolia
Figure 8. Correlation between TCI and
VCI, sampling in Mongolia
Correlation and regression analysis are related
in the sense that both dimension with
relationships among variables. Correl=0.83

18. stress fair favorable
Figure 11. VHI and summer condition evaluation in 11 July 2000
(dry, lack of precipitation).
2000193
In this year highest damage
caused in agricultural, pasture
among 1999-2005. lost 15.3% of
livestock.

19. 2002193
In this year 77 soums extremely drought, 174 soums involved
slightly drought and overall 251 soums affected by drought,
most of soums affected such as most of Uvs, Arkhangai,
Zavkhan, Uvurkhangai, souht of Huvsgul, Bulgan, some of
Dundgovi, Dornogovi, Umnugovi which was most wide area
affected among the last twelve years. Temperature anomaly
1.1-6.20c higher than average in most of territories of the
Mongolia (Уур амьсгалын өөрчлөлтөнд мал аж ахуй өртөх
байдал, 2005).
stress fair favorable

20. stress fair favorable
Figure 11. VHI and summer condition in 11
July 2008 (relatively favorable with high
precipitation and chilly).
If the indices are below 40 indicating different levels of vegetation stress, losses of
crop and pasture products might be expected or if the indices above 60 (favorable
condition) might be expected plentiful products.
2008193

21. stress fair favorable
Figure 11. VHI and summer condition in 11
July 2011.

22. 4.3 Vegetation Health Index (VHI)
Vegetation Health products has been calculated only for 193rd Julian day of 2000-2011 from the MHD (Moisture,
Heat, Drought) database, which built in this work for a drought assessment purposes. Mentioned that here are only
193rd products composited by eight days were used, therefore it will not express the vegetation health for a month or
whole summer (Fig. 7).
Over the past eleven years, many major droughts and
dry spells have had significant an economic, social, and
environmental impacts for Mongolia. The biggest
drought of the 2000, 2002, 2007 lack of precipitation
and extreme hot period affected major regions of
Mongolia and its economy for several years.
Differences in the VCI and TCI dynamics were further
investigated during the several years with the extreme
values of the biomass at the Darkhan station where
average a biomass 10.1 centner/ha is during these
eleven years (green background is express an amount
of biomass).

23. VHI
2011
.Sep
VHI
2010
.Aug
Measurement
Figure 13. Measurement of
the CO2, biomass and
environmental parameter in
2009, 2010, 2011 field
study at the Tuv, Dundgovi,
Khentii aimags

24. Year
Biomass
anomaly
Interpolated grids value of VCI VCI Interpolated grids value of TCI TCI VHI
2000 -3.1 52 53 96 89 90 46 94 84 75.5 52 50 93 64 83 73 94 58 70.8 73.6
2001 -5.6 24 17 18 17 5 20 31 5 17.1 36 45 50 47 55 52 47 47 26 21.5
2002 -4.1 38 10 11 10 23 28 16 10 18.2 42 45 56 52 77 73 76 52 59.1 38.6
2003 0.1 25 24 43 29 19 17 36 24 27.1 5 10 12 11 27 26 23 17 80 53.5
2004 -2.5 11 16 27 33 12 8 23 16 18.2 36 40 56 58 61 63 58 58 53.7 36
2005 -3.0 35 0 12 8 9 18 21 0 12.8 0 25 0 0 11 10 5 0 6.3 9.6
2006 0.7 45 42 42 24 36 27 47 55 39.7 0 0 0 0 0 0 0 0 0 19.8
2007 -2.5 14 38 22 19 0 11 25 38 20.8 26 30 37 35 50 47 52 35 39 29.9
2008 15.5 100 100 100 100 86 100 100 100 98.2 89 80 100 100 100 100 100 100 96.1 97.1
2009 1.5 48 29 55 59 50 51 13 29 41.7 57 60 75 70 83 78 76 76 71.8 56.8
2010 2.0 50 79 74 82 42 53 59 79 64.7 36 40 50 47 61 57 47 58 49.5 57.1
2011 0.9 32 59 60 73 43 46 60 59 54 21 25 31 29 44 42 23 35 31.2 42.6
Table 3. TCI, VCI, VHI and biomass anomaly of the Darkhan station in 11 July, 2000-2011.
Usually TCI value 8% higher than on average VCI, it
would be indicate a plant stress influenced several
indicators such as the atmospheric processes include
hot, chilly condition and rainfall.
-10.0
-5.0
0.0
5.0
10.0
15.0
20.0
-20
0
20
40
60
80
100
120
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Biomassanomaly,gram
VCI,TCI,%
Time series
VCI
TCI
Biomass anomaly
Figure 8. Time series of TCI, VCI (left) values and pasture
biomass anomaly (right), gradient background above to below
same to stress to favorable condition.
88.6
58.6
75.8
20.4
73.2
8.8
70.5
24.4
126.7
34.1
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
temperature,0C
precipitation,mm
Precipitation VHI Temperature
average decades temperature between 1984-2009 18.7
0C
average decades summery precipitation between 1984-2009 52
mm
Figure 9. Temperature, precipitation and VHI of Darkhan, 1984-
2009 (deep blue is 2000-2009 using this study).

25. 4.4 Differences
It is possible to show the vegetation health differences from the VH of time ordered by last year or eight days. The VH
changes can be indicate a plant growth or losses, plant damage, pasture degradation from the last time.
stress fair favorable
Figure 12. Vegetation health differences of period from 2008 to 2011 in 11 July.

26. 4.5 Drought assessment
This equals to the drought definition that a combinational situation of the meteorological condition, which is consists of low
precipitation and high temperature periods, along with an agro-meteorological condition, which is soil moisture deficiency due to
enlarged evapo-transpiration by atmospheric demand (Natsagdorj L, 2009).
The drought assessment was done based on the VHI, VCI and TCI. If their values are below 40, drought is “Exceptional
condition” which has included various intensity; if the indices are between 0-5 - “Extreme”, 6-15 - “Severe”, 16-25 - “Moderate”,
26-35 - “Abnormally”, 35-40 – dry condition .
Figure 13. Drought assessment map in 11 July
2002 over the Mongolia.

27. The drought assessment must consider the time period longer than month (four times eight day). Below maps are
calculated for more than a month period, that eliminate the first eight days and add the last eight days.
Figure 14. Drought
dynamics of the year,
2003.

28. Number Number of day
(Julian calendar)
Calculating 8 days
(Gregorian
calendar)
Number Number of day
(Julian calendar)
Calculating 8 days
(Gregorian
calendar)
1 121 Apr.30-May.8 11 201 Jul.19-Jul.26
2 129 May.7-May.16 12 209 Jul.27-Aug.3
3 137 May.17-May.24 13 217 Aug.4-Aug.11
4 145 May.25-Jun.1 14 225 Aug.12-Aug.19
5 153 Jun.1-Jun.8 15 233 Aug.20-Aug.27
6 161 Jun.9-Jun.16 16 241 Aug.28-Sep.4
7 169 Jun.17-Jun.24 17 249 Sep.5-Sep.12
8 177 Jun.25-Jul.2 18 257 Sep.13-Sep.20
9 185 Jul.3-Jul.10 19 265 Sep.21-Sep.28
10 193 Jul.11-Jul.18 20 273 Sep.29-Oct.6
TCI, VCI, VHI are begin in Apr.30 and drought in Jun.01
Product schedule
Table 4. Time schedule of products.

29. The next step in our proposed methodology is to use the VCI and TCI drought monitoring indices to derive drought frequency
map of the July during last twelve years. (Figure 16). These drought maps are produced according to GIS standards and the
results are discussed in the time series below. As shown in Figure 15, the VCI and TCI indices are also in Figure 17, 18.
Figure 15. Drought dynamics, 2000-2011.

30. Figure 16. Drought frequency map, 2000-2011.
The Mongolia has the assessment of drought based on
summer condition evaluation which appraise for
summer condition within 1-5 values. /Natsagdorj L,
Dulamsuren J, 2005/

31. Figure 17. Average vegetation condition,
2000-2011.
Figure 18. Average land surface temperature condition,
2000-2011.
2912760.167 2814662.5
0
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
Average
number of grid
0-30
30-40
40-60
60-70
70-100
2000 2001 2002 2003 2004 2005 2006
0-30 3865938 3717486 3822768 339716 3124306 3833740 374004
30-40 1420823 1604541 1221136 638493 1447634 1291337 1111302
40-60 1964225 2195961 2261114 1705205 2232494 2017961 2897985
60-70 737678 725050 719867 1190048 926540 804740 1275391
70-100 1959377 1708076 1908253 6187419 2401974 2059093 4646347
Figure 18. Portion of drought dynamic In Mongolia,
VHI classification.
2007 2008 2009 2010 2011Average
5690010 2323466 2937645 3775021 1149022 2912760 28.9
1028688 1399710 1317792 1474965 1040202 1249719 12.4
1559510 2494911 2298440 2105420 2485874 2184925 21.7
507695 1129283 1004263 798599 1338802 929829.7 9.2
951967 2986501 2647619 1868717 4450607 2814663 27.9

32. Assimilation between Standardized Precipitation Index (SPI) and VHI
Figure 19. Assimilation
between SPI and VHI, 2000-
2010 (a. Dalanzadgad in Gobi,
b. Undurkhaan in steppe, c.
Hatgal in Forest regions).
VHI индекс нь SPI, Педийн
индекстэй муугүй хамааралтай
байна.
0
20
40
60
80
100
-4
-2
0
2
4
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Hatgal, Khuvsgul, 50.43 100.15, 1668m
SPI Ped's index VHIPed's index axis
0
10
20
30
40
50
60
70
80
90
-5
-4
-3
-2
-1
0
1
2
3
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Dalanzadgad, Umnugovi, 43.56 104.43, 1462m
SPI Ped's index VHI
Ped's index axis
opposited.
0
10
20
30
40
50
60
70
80
-6
-4
-2
0
2
4
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Undurkhaan, Khentii, 47.32 110.67, 1033m
SPI Ped's index VHIPed's index axis
opposited.
VHI correlation SPI Ped’s
Hatgal 0.79 0.58
Undurkhaan 0.69 0.77
Dalanzadgad 0.61 0.80
Хүснэгт 8: VHI болон SPI, Педийн индексийн хамаарлын коеффициент

33. Assimilation between Standardized Precipitation Index (SPI) and VHI
Figure 19. Assimilation
between SPI and VHI, 2000-
2010 (a. Dalanzadgad in Gobi,
b. Undurkhaan in steppe, c.
Hatgal in Forest regions).
VHI maps indicate a high visual
correlation with SPI, Ped’s index
but the quantitative correlations for
each year do not provide reliable
results.
Table4. SPI, SWI and VHI classifications schemes.
0
20
40
60
80
100
-4
-2
0
2
4
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Hatgal, Khuvsgul, 50.43 100.15, 1668m
SPI Ped's index VHIPed's index axis
0
10
20
30
40
50
60
70
80
90
-5
-4
-3
-2
-1
0
1
2
3
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Dalanzadgad, Umnugovi, 43.56 104.43, 1462m
SPI Ped's index VHI
Ped's index axis
opposited.
0
10
20
30
40
50
60
70
80
-6
-4
-2
0
2
4
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Undurkhaan, Khentii, 47.32 110.67, 1033m
SPI Ped's index VHIPed's index axis
opposited.

34. VHI average map of the July, drought situation with the altitude
A
B
C
D
Drought occurs might be influenced with altitude and
forest zone no more percentage. This relevance has been
calibrated with two transect which west side in Altai range
to east side in Khalkhiin gol its A-B, north side in Mongol
Shariin davaa to south side in Shargiin govi its C-D.

35. VHI and altitude values relevance by lines A-B, C-D

36. Also TCI
determined with
2788 grids.
VHI index of Shiluustei soum
(soum – administrative unit
in Mongolia) is good
indicated by ecosystem
reduction and its momentum
of geographical spreading
and has middle sized area
field in Mongolia and it
determined with 44608 grids.
Product discrimination
The several products, such as, the TCI, VCI, VHI,
Drought and Vegetation health differences, have own
resolutions depending on the source data:
•TCI 1000 meter
•VCI 250 meter
•VHI 250 meter
•Drought 250 meter
•Differences of VH 250 meter.
Figure 19. Resolution of the TCI.
Figure 20. Resolution of the VCI, VHI, Drought, et al.

37. Where study area ecosystem as a self-organizing under the gradient of temperature. Energy from the sun to
land where energy changed to heat energy. On land heat energy becoming temperature gradient which ruled the
ecosystem process. Land cover has higher potential of energy dissipative (radiation perception, evaporation by
body of plant), land surface temperature decreased then plant growth higher, backward plant cutes where LST
increase.
Geometric mean adequate for dissipative parameters of environmental which case of assessment with TCI
and VCI.
Realizing drought occur increased north grassland such as Selenge river basin, Huvsgul, Zavkhan, Bulgan
aimags from the released drought frequency map.
Most extremely, wide drought event in 2007, most favorable chilly year was 2003.
This study indicated that the utility of the new products using source of information about climate impacts on
pasture vegetation can be generated. These results can be used for early warning advice to farmers and herders
when they looking for better grazing places. Therefore these results are useful for assessment of the biomass
production, drought, vegetation health, temperature conditions and their changes. Also VCI and TCI values
were higher where expected the fire risky area. These assessments are high beneficial in the areas where
meteorological data not available, it cause not scattered meteorological stations.
The products indicate very high accuracy with 250 m resolution and severity, duration of products from local
(bag, soum) to national scales.
The products differences are very useful for comparison with anytime conditions these hot or cool, poor or
better of vegetation condition and drought changes.
Geometric mean adequate for dissipative parameters of environmental which case of assessment with TCI
and VCI.
TCI and VCI parameters are strongly linked then they will influence each other substantially.
Conclusions

38. References
James J. Kay, Ecosystems are Self-organizing Holarchic open systems: Narratives and the Second law of Thermodynamics. “CRC Press -
Lewis Publishers. pp 135-160, 2000”
Diamandi A, Oancea S, Alecu C, Analysis of the land surface temperature estimated from different satellite sensors over romania.
“Romanian reports in physics, vol. 62, no. 1, p. 185–192, 2010”
Chuluun T, Altanbagan M, Dennis Ojima. Vulnerability assessment of the Mongolian rangeland ecosystem.
Kogan F, Stark R, Gitelson A, Jargalsaikhan L, Dugrajav C and Tsooj S, Derivation of pasture biomass in Mongolia from AVHRR-
based vegetation health indices. “Int. Remote sensing, 2004”
Mijiddorj R. Self-Organizing structures and its surrounding. Мижигддорж Р. Аяндаа цэгцрэх тогтолцоо, түүний эргэн тойронд, 2009.
230х.
Bayarjargal Y, Karnieli A, Bayasgalan M, Khudulmur S, Gandush C, Tucker C.J. A comparative study of NOAA/AVHRR derived
drought indices using change vector analysis. “ Elsevier Inc. 10.1016/j.rse. 2006.06.003”
Drought Event Definition, Technical Report No. 6
Tukcer C, Bayasgalan M.Assesment and monitoring of desertification processes in Mongolia using GIS.
Bhuiyan C. Desert vegetation during droughts response and sensitivity.
Natsagdorj L. Drought and Dzud. Ulaanbaatar. 2009. p55
Jiergen V.Vogt, Alain.A.Viau, Isabelle Beaudin, Stefan Niemeyer, Francesca Somma.Drought monitoring from space using empirical
indices and physical indicators.
Anup.K, Prasad.A, Lim Chai, Ramesh P. Singh, Menas Kafatos.Crop yield estimation model for Iowa using remote sensing and surface
parameters.
Karnieli A Comments on the use of the Vegetation Health Index over Mongolia.
Kogan F Contribution of Remote Sensing to Drought Early Warning.
Ramesh P Singh, Sudipa Roy, Kogan F.Vegetation and temperature condition indices from NOAA/AVHRR data for drought monitoring
over India.
Kogan F Operational Space Technology for Global Vegetation Assessment.
Kogan F Monitoring Drought and its Impacts on Vegetation from Space.
The National Atlas of the Mongolian People’s Republic, 1990
The Atlas of Climate and Ground Water Resources in the Mongolian People’s Republic, 1985
Calculating the human development indices—graphical presentation, Technical notes, HDR-2010
Tsakiris G, Loukas A, Pangalou D, Vangelis H, Tigkas D, Rossi G, and Cancelliere A. Drought characterization, Chapter 7.

39. Thank you for pleasure attention
criticism is growth origin
Шүүмжлэл бол хөгжлийн
хөшүүрэг мөн.

40. Second law of thermodynamics: The
entropy of any isolated system not in
thermal equilibrium almost always
increases. Isolated systems
spontaneously evolve towards thermal
equilibrium -- the state of maximum
entropy of the system -- in a process
known as "thermalization". Equivalently,
perpetual motion machines of the second
kind are impossible.

41. Хүлээгдэж буй үр дүн
1. TCI /температурын
хөхцөлийн зураг/
2. VCI /ургамлын
хөхцөлийн зураг/
3. VHI /ургамлын эрүүл
мэндийн зураг/
4. Гангийн мониторингийн зураг
5. Бэлчээрийн ургамлын
ургацын зураг
Цаашдаа жил бүр
“Чийг, дулаан, гангийн”
мэдээллийн баазыг
зузаатгах /энэ ажлын
хүрээнд татан,
боловсруулан, тооцоо
хийсэн суурь мэдээ/.
10-дугаар сарын
эхний 10 хоногт TCI,
VCI-ийн max, min утгыг
шинэчлэн бодуулж
байх.
Шинэ
бааз
Зарим тохиолдолд түймрийн эрсдэлтэй нутгийг харуулдаг