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IMPACT OF ELEVATION AND ASPECT ON THE SPATIAL DISTRIBUTION OF
VEGETATION IN THE QILIAN MOUNTAIN AREA WITH REMOTE SENSING DATA
X.M. Jin a '°, Y.-K. Zhang b , M.E. Schaepman c , J.G.P.W. Clevers c , Z. Su d
a School of Water Resources and Environment, China University of Geosciences, Beijing, 100083, China
-jinxm@cugb.edu.cn
b Department of Geoscience, University of Iowa, Iowa City 52242, IA,USA
-you-kuan-zhang@uiowa.edu
c Wageningen University, Centre for Geo-Information, Wageningen, The Netherlands
- (Jan.Clevers ,Michael.Schaepman)@wur.nl
d International Institute for Geo-Information Science and Earth Observation (ITC), Enschede, The
Netherlands-B_Su@itc.nl
Commission VII, ICWG-VII-IV
ABSTRACT:
The spatial distribution of vegetation in the Qilian Mountain area was quantified with remote sensing data. The MODIS NDVI values
for June, July, August and September are the best indicators for the vegetation growth during a year in this area and thus were used in
this study. The results obtained by analyzing the NDVI data for seven years from 2000 to 2006 clearly indicated that elevation is the
dominating factor determining the vertical distribution of vegetation in the area: the vegetation growth is at its best between the
elevations of 3200 m and 3600 m with the NDVI values lager than 0.5 and a peak value of larger than 0.56 at 3400 m. The horizontal
distribution of vegetation within the zone of 3200 m and 3600 m is significantly impacted by the aspect of hillslopes: the largest
NDVI value or the best vegetation growth is found in the shady slope whose aspect is between NW340 0 to NE70° due to relatively
less evapotranspiration. The methodology developed in this study should be useful for similar ecological studies related to vegetation
distribution.
1. 1 INTRODUCTION
The vegetation cover in mountain areas is very important.
Vegetation cover affects local and regional climate and reduce
erosion. Economy of local communities and millions’ people in
mountain areas depends on forests and plants. They also
effectively protect people against natural hazards such as
rockfall, landslides, debris flows, and floods (Brang et al.,
2001). Settlements and transportation corridors in alpine
regions mainly depend on the protective effect of the vegetation
(Agliardi and Crosta, 2003). Therefore, understanding of
distribution and patterns of vegetation growth along with the
affecting factors in those areas are important and have been
studied by many researchers (Oliver and Webster 1986; Weiser
et al. 1986; Stephenson 1990; Turner etal. 1992; Henebry 1993;
Endress and Chinea 2001; Bai et al. 2004).
Topography is the principal controlling factor in vegetation
growth and that the type of soils and the amount of rainfalls
play secondary roles at the scale of hillslopes (O’Longhlin 1981;
Wood et al. 1988; Dawes and Short 1994). Elevation, aspect,
and slope are the three main topographic factors that control the
distribution and patterns of vegetation in mountain areas
(Titshall et al. 2000). Among these three factors, elevation is
most important (Day and Monk 1974; Busing et al. 1992).
Elevation along with aspect and slope in many respects
determines the microclimate and thus large-scale spatial
distribution and patterns of vegetation (Geiger 1966; Day and
Monk 1974; Johnson 1981; Marks and Harcombe 1981; Allen
and Peet 1990; Busing et al. 1992).
One of the powerful tools to study the spatial distribution of
vegetation is remote sensing. Remote sensing has traditionally
been used in large-scale global assessments of vegetation
distribution and land cover with the Normalized Difference
Vegetation Index (NDVI) data from Advanced Very High
Resolution Radiometer (AVHRR) and the Moderate Resolution
Imaging Spectroradiometer (MODIS) (Chen and Brutsaert 1997;
Defries and Townshend 1994; Defries et al. 1995; Friedl et al.
2002; Loveland et al. 2000, 1999). The NDVI is an index
derived from reflectance measurements in the red and infrared
portions of the electromagnetic spectrum to describe the
relative amount of green biomass from one area to the next
(Deering 1978). The NDVI is an indicator of photosynthetic
activity of plants and has been widely used for assessing
vegetation phenology and estimating landscape patterns of
primary productivity (Sellers, 1985; Tucker and Sellers, 1986).
It was designed to quantitatively evaluate vegetation growth:
higher NDVI values imply more vegetation coverage, lower
NDVI values imply less or non-vegetated coverage, and zero
NDVI indicates rock or bare land.
Most studies with remote sensing data were concentrated on
two-dimensional horizontal patterns and a few were focused on
the effect of elevation on the vertical distribution of vegetation
in mountain areas (Franklin 1995; Edwards 1996; Guisan and
Zimmermann 2000; Hansen 2000; Miller et al. 2004). The
objectives of this study are two-fold: 1) to quantitatively assess
both vertical and horizontal distribution of vegetation in the
Qilian Mountain area and its main controlling factors, i.e.,
elevation, aspect, and 2) to demonstrate the usefulness of the
methodology which may be used for other environmental and
ecological studies.