Spatial and Temporal Patterns of NDVI Response to Precipitation
and Temperature in Mongolian Steppe
Tsedendamba PUREVSUREN*1), Buho HOSHINO2), Sumiya GANZORIG2) and Marie SAWAMUKAI1)
Abstract: Understanding of recent trends of the vegetation cover changes, and its relationship with the climate change will be
helpful in more accurate prediction of the vegetation cover changes. The accurate prediction of vegetation cover is helpful inreduction of loss and damages to the economy of the country. Rainfall is one of the limiting factors of animal productivity andsocio-economic development of Mongolia. In this study we analyzed temporal patterns of NDVI in relation to precipitation and/orair temperature in steppe zone of Mongolia. NDVI from the SPOT VEGETATION data, at a spatial resolution of 1 km and 10 day
intervals, were used to investigate the vegetation variations in Mongolia during the period from 2003 to 2009. Then, GIS and remotesensing techniques were used to examine the relationship between precipitation/temperature and the NDVI in Mongolia, and theseasonal change of NDVI is taken as a tool for drought monitoring. The results indicated that the NDVI values changed in relation todifferent amount of precipitation and maximally responds to the variation of precipitation with a lag of about 10 days and 20 days
during vegetation period.
Key Words: Mongolia, NDVI, Precipitation, Remote sensing, Steppe

1. Introduction
Nomadic livestock husbandry is a traditional sector ofMongolia and plays an important role in Mongolian economy.
Livestock husbandry is very sensitive and vulnerable to weatherand climate and therefore greatly depends on pasture condition.
Intensity and frequency of natural disasters, including
droughts and dzuds (a Mongolian term for an extreme weather
conditions in which large numbers of animals die due tostarvation) are increasing significantly during the last few years
because of climate change.
These phenomena cause significant economic damages
and losses. Recent studies shows that changes in climate ofMongolia manifest significantly in winter season (Natsagdorjet al., 2001).
According to climate change studies conducted in
Mongolia, during the period between 1940 and 2005, theannual average temperature in Mongolia has increased byabout 1.9°C and winter temperature changes were even greaterin the mountainous areas (2.0 - 3.7°C) (Batima et al., 2005).
The annual precipitation has been decreased from the1940’s to about the mid-1980’s, and is on increase in following
years. Only in Gobi desert area the precipitation is notincreasing. Annual mean precipitation has been decreasing incentral Mongolia, but has been increasing in both the eastern
and western regions of country (Batima et al., 2005).

Dynamic changes in the Mongolian pasture and its
correlation with weather and climate conditions were studied
using meteorological and agro-meteorological regularobservation data (Dagvadorj, 1996), various maps and digital
data of NOAA/AVHRR satellite (Erdenetuya, 2004).
However, spatial and temporal patterns of NDVI(Normalized Difference Vegetation Index) in response to
precipitation and air temperature in Mongolian Steppe stillaren’t well interpreted.
In this study we examined the spatiotemporal patterns ofNDVI distribution and its response to precipitation or airtemperature in Mongolian steppe using remote sensingtechnology.
Since pastures in the mountain steppe zone are mostpopulated and overgrazed, we have selected locations withdifferent conditions of usage and protection. Hustai National
Park and Chinggis Khaan International airport are area underprotection and have not been used by livestock, while theAltanbulag site is presents common pastures in Central Mongolia.
The main objective of this study is to find out the response ofNDVI values to different amount of precipitation dropped duringin summer time in conditions of mountain steppe of Mongolia.

2. Materials and Methods
2.1. Site description
To study the NDVI response to precipitation andtemperature, three sites were selected.
The selection of that site was based on the level of land use.
To find out the changes in NDVI values, it is important toknow the influence of livestock and wild animals that graze on
steppe pastures. For this reason, the selected sites include asite with full protection from livestock and wild ungulates
grazing (control area), a site where only wild animals aregrazing (protected area) and a site where both domestic andwild animals utilizing the pastures. As the control area wechose the fenced part Chinggis Khaan (106°45’59” E,47°50’35’’N) International airport (Ulaanbaatar city). This
control area has an area of 2 × 4 km and has been fenced since1986 year to keep out livestock and human.
To exclude influence of the livestock grazing on vegetation
cover we selected protected area, named the Hustai National
Park, (105°55'23" E, 47°40'48" N） that was established in
1993. Third site was chosen in the area that of border
National Park, but used by herders for the livestock grazing.
The site is located in the south part of Altanbulag soum
(106°24'32"E, 47°41'46"N), Tuv province of Mongolia,Altanbulag soum has 566,866 hectares area, livestock
population is 104,500 heads. In this area the livestock grazes
during all seasons.
2.2. Data and methods
Meteorological variables (ten-days precipitation and airtemperature data sets) from June 2003 to August 2009 wereobtained from 3 meteorological stations (Table 1).
NDVI data came from 2 satellite image sources namely
SPOT VEGETATION (VGT) and NOAA/AVHRR. NDVI
data included a 10-day composite SPOT VEGETATION dataset (with 1 km resolution) from June of 2003 to August of 2009,
which were downloaded from the internet database (http://free.vgt.vito.be/home.php ).
NOAA/AVHRR NDVI data (with 8 km resolution and 15day intervals) were processed by in the GIMMS group atNASA(http://iridl.ldeo.columbia.edu/SOURCES/.UMD/.
GLCF/.GIMMS/.NDVIg/.global/.ndvi).
The mathematical combinations of the 0.55-0.68 μm and
0.725-1.10 μm wavelength data provide important information
on pasture vegetation condition (Tucker, 1979). Thisparameter is called “Normalized Difference Vegetation Index”(NDVI), which is derived from the visible red (RED) andnear-infrared (NIR) spectral bands (defined by Equation 1):
NDVI = (NIR– RED) / (NIR +RED)(1)
The NDVI was calculated from SPOT VGT data by using thecombinations of bands 2 (0.61-0.68 μm) and 3 (0.78-0.89 μm)
Then, a yearly NDVI anomaly during the warming season(June to August) was calculated as follows (defined byEquation 2):
NDVIσ= {((NDVIα)/(NDVIμ)-1)100}(2)
where NDVIσ(Anyamba and Turker, 2005) are the respective(June to August) percent anomalies, NDVIα are individual
seasonal (June to August) means, and NDVIμ is the long term
(June to August) mean. The individual seasonal NDVI is 3
month mean value for year. The long term NDVI is annual
mean index.
The Hovmöller diagram method is the 2D method toexamine the pattern in different meteorological data bylongitude and latitude over huge territories was used to study
the NOAA/AVHRR NDVI spatial patterns during 2003-2006(Hovmöller, 1949).

3. Results and Discussion
3.1. Trends in spatial variations of NDVI.
Spatial patterns of NDVI calculated from NOAA/AVHRR
during 2003-2006 are presented in Figure 1. We also haveanalyzed the NDVI change. The results show that highest
NDVI was registered in control area. The annual average ofNDVI in control area was 0.5. Those values in other twosites were 0.4-0.5 respectively. The NDVI spatial distribution
was irregular. NDVI higher values ranging 0.5-0.6 wereTable 1. Selected meteorological stations.
StationBuyant-uhaa

Hustai

Altanbulag

1 Longitude

106°45' 59" E105°55'23" E

106°24'32"E2 Latitude

47°50' 35"N

47°40'48" N

47°41'46"N

3 Altitude (m)1272

1100-1840

1260

4 Precipitation(mm)

248.8

270

131.1

5 Temperature (0C)

-1.6

0.2

-1.1

Fig.1. Spatial distributions of the trends in NDVI.

(Altanbulag soum 26.1 mm, Buyant-uhaa 35mm, Hustai 40.3mm) dropped during third ten days of July (2006). This isshowing that even in condition of dry, low precipitation
summer season, one moment high rain could sharply change
NDVI. So far, the NDVI values might be depending to thetime and amount of precipitation in conditions of mountainsteppe of Mongolia.

Fig.2. NDVI value between June-August, 2003-2009

distributed over the north-west and middle part of the protected
and unprotected sites. Lower values of 0.2 - 0.3 dominate innorth-east part and south. Spatially, only during 2003, theNDVI was homogenous over study area. During most years
the NDVI values were sporadic and might be depended on
surface roughness, exposition and the soil moisture.
3.2. Seasonal pattern of NDVI.
Figure 2 shows the seasonal dynamics of NDVI in thestudy area during 2003-2009. SPOT VGT satellite data forten days shows NDVI value increase from June to August.
The seasonal increase in NDVI was the same for all threesites, with highest values registered during three months in control
area. The NDVI values were lowest in the Altanbulag site.
3.3. Spatial distribution of NDVI
We have analyzed the distribution and long terms
vegetation dynamics. The seasonal mean NDVI (Spot VGT)
was highest during 2004, 2006, 2008, and lowest in 2005,
2007. The first decrease in mean NDVI registered in 2004
and lowest was in 2005. As it was mentioned above, despite
very low precipitation uncharacteristically high NDVI values
registered in 2006 (Fig. 3).
3.4. Relationship between NDVI and precipitation
The 10 and 20 days time lag of NDVI response toprecipitation was observed in conditions of Hustai National
Park. Also, the time lag was different in 2003 and 2007, 10days and 20 days, respectively in protected area.
3.5. Changes in mean NDVI and precipitation in study
area during 2003-2009
In general, NDVI pattern follows that of precipitation, with10 to 20 days time lag, although that trend was not seen in2006 (Fig. 4a), when despite low amount of monthly
precipitation (60.5 mm) high NDVI (0.44) was registered.
In that year (2006), we found that the increase of NDVI
was response to a relative high amount of precipitation

Fig. 3. Spatial and temporal distribution of NDVI in study area
during August.

(2004) used NOAA/AVHRR; Iwasaki (2006) used SPOT
VGT, Wang et al. (2003) used NOAA/AVHRR, Anyamba etal. (2005）used Landsat, SPOT, MODIS, and Davenport et al.
(1993) used NOAA/AVHRR, respectively. Iwasaki (2006)
found, 10 to 30 days time lag in NDVI after rain in steppe zoneof Mongolia. Anyamba and Turker (2005) and Wang et al.
(2001) observed strong relationship between precipitation andNDVI in Africa.
In our study, we found the same pattern in conditions ofmountain steppe zone of Mongolia. The results of our study
shows that NDVI depends on the time and amount ofprecipitation.
Acknowledgment
This work was supported by Grant-in-Aid for Scientific
Research (S) (No.) 21221011 (Project leader: Prof. Y.
Shimada) from JSPS of Ministry of Education, Culture, Sports,
Science and Technology.

References

Fig. 4. Changes in mean NDVI and precipitation in study area
during 2003-2009.
Table 2. Correlation matrix (Principal component analysis, Xlstat).
Variables

Temp (°C)

Prec(mm)mean NDVI

Temp (°C)

1-0.8

0.15

Precipitation(mm)

-0.8

10.46

mean NDVI

0.15

0.46

13.6. Relationship between NDVI, temperature andprecipitation in study area during 2003-2009
Table 2 shows distribution of the maximum correlation
between precipitation and NDVI. Negative correlations arerecognized with respect to the summer air temperature in study area.
3.7. NDVI anomaly index
Examination of this time series (2003-2009) reveals that2005 and 2007 were marked by low values below average
NDVI and characterized by a significant large-scale drought.
On the other hand, 2006 and 2008, were marked by a very wet
trend with regional high values above average NDVI. The
drought occurred every two years in protected area andunprotected area. At control area had been changed to wetand drought.
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