1385 
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.