the vegetation cover dynamics (1982–2006) in different erosion regions of the yellow river basin,...
TRANSCRIPT
land degradation & development
Land Degrad. Develop. 23: 62–71 (2012)
Published online 27 October 2010 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/ldr.1050
THE VEGETATION COVER DYNAMICS (1982–2006) IN DIFFERENT EROSIONREGIONS OF THE YELLOW RIVER BASIN, CHINA
C. Y. MIAO1*, L. YANG2, X. H. CHEN3 AND Y. GAO4
1State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University,Beijing 100875, PR China
2State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, ChineseAcademy of Sciences, Beijing 100101, PR China
3School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68583, USA4School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China
Received 4 May 2009; Revised 23 July 2010; Accepted 27 August 2010
ABSTRACT
Vegetation significantly influences human health in the Yellow River basin and the plant cover is vulnerable to people. Typical types of erosionin the Yellow River basin include that caused by water, wind and freeze–thaw. In this paper, vegetation cover change from 1982 to 2006 wasstudied for a number of different erosion regions. The Global Inventory Monitoring and Modeling Studies Normalized Difference VegetationIndex (GIMMS NDVI) data were employed, while climatic data were also used for analysis of other influencing factors. It was shown that:(1) generally the vegetation cover in different erosion regions displayed similar increasing trends; (2) spatially the vegetation cover washighest in the water erosion region, the second highest was in the freeze–thaw region and the lowest in the wind erosion region; and(3) vegetation cover in the Yellow River basin is influenced by climate factors, especially by temperature. In water erosion regions, thetemporal change of vegetation cover seemed complicated by comprehensive climatic and human influences. In wind erosion regions,the vegetation cover had close relations to precipitation. In freeze–thaw erosion regions, the vegetation cover was primarily altered bytemperature. In all the three erosion regions, significant change of the vegetation cover occurred from 2000 just after the ‘Grain for Green’(GFG) programme was implemented throughout China. Copyright # 2010 John Wiley & Sons, Ltd.
key words: Yellow River basin; PR China; remote sensing; erosion; vegetation cover dynamics
INTRODUCTION
Eco-environmental systems are dynamic due to climatic
disturbances, such as drought, wind, flood and solar
radiation, or human interferences (Lozano et al., 2007).
Nowadays, various sorts of problems in the global eco-
environment are threatening the sustainable development of
societies, even though these challenges have received great
attention from governments and scientists (Chen et al.,
2008). In order to assess eco-environmental change, it is
possible to use vegetation cover dynamics as an indicator.
Long time-series data on vegetation cover are usually used to
detect discrete change and gradual change.
Nowadays, remote sensing (RS) technology is widely
used for monitoring the state of vegetation cover, due to its
high efficiency for acquiring updated information (Bannari
et al., 1995). The Normalized Difference Vegetation Index
* Correspondence to: C. Y. Miao, State Key Laboratory of Earth SurfaceProcesses and Resource Ecology, College of Global Change and EarthSystem Science, Beijing Normal University, 19 Xinjiekou Wai Street,Beijing 100875, PR China.E-mail: [email protected]
Copyright # 2010 John Wiley & Sons, Ltd.
(NDVI), can be defined as the difference between near
infrared and red waveband radiance or reflectance divided
by the sum of radiance or reflectance for these two
wavebands (Stow et al., 1998), and it remains the basic
vegetation index widely employed for vegetation cover
monitoring (Trishchenko et al., 2002). It was found that
change in NDVI time-series can indicate the variation in
vegetation conditions proportional to the absorption of
radiation used for photosynthesis (Sellers, 1985), and there
is a good correlation between the NDVI value and the
vegetation cover density, biomass and leaf area index (LAI)
(Xin et al., 2008). In addition, the NDVI also correlates with
climate variables such as precipitation, temperature,
evaporation, etc. (Chen et al., 2008). Therefore, the NDVI
index can be used not only to describe spatiotemporal
variation of vegetation, but also to reflect the vegetation
feedback and response to climate.
In China, the vegetation cover shows an increasing trend in
recent years according to the NDVI (Chen et al., 2002; Fang et
al., 2004); however, interannual variation rates of vegetation
indexes have apparent spatial differentiations (Piao and Fang,
2001, 2003). Moreover, Li et al. (2002), using Advanced Very
Figure 1. Distribution of erosion types in the Yellow River basin. Thisfigure is available in colour online at wileyonlinelibrary.com
VEGETATION COVER DYNAMICS (1982–2006) 63
High Resolution Radiometer (AVHRR) NDVI data for 1983–
1992 and climatic data from 160 monitoring stations, detected
a significant correlation between NDVI value and rainfall in
China; the results show that the correlation coefficient
increases in order from evergreen forest to deciduous forest,
to shrubs and desert vegetation, to steppe and savanna. Most
research has been focused on the regions with fragile and
sensitive ecology such as Qinghai–Tibet Plateau (Ding et al.,
2005; Liang et al., 2007; Li et al., 2008), northwestern China
(Ma et al., 2003; Li et al., 2005; Deng et al., 2006; Ma and
Veroustraete, 2006; Xu et al., 2007), agro-pastoral transition
regions (Xia et al., 2006; Fan et al., 2007), karst regions (Wang
and Yang, 2006; Meng and Wang, 2007; Xiao and Weng,
2007), etc.
Among these fragile and sensitive regions, the Yellow
River basin has received the most attention in China (Sun et
al., 2001; Yang et al., 2002; Li and Yang, 2004; Xin et al.,
2008), due to its vital domestic status and problematic eco-
environment. In the whole Yellow River basin, it was found
that the vegetation cover showed an increasing trend during
1982–1999 (Sun et al., 2001), with the increasing rate
reaching at 0�58 per cent in this period (Yang et al., 2002).
Although the monthly NDVI sometimes lags behind the
corresponding precipitation within a year, it still shows
positive correlations between annual NDVI series and
annual precipitation in the Yellow River basin (Li and Yang,
2004), and no significant correlation between NDVI value
and temperature (Liu and Xiao, 2006). The results from the
Yellow River basin indicate that vegetation showed an
increasing trend during the past 20 years, the interannual
variability of NDVI in the Yellow River basin has a close
relationship with climate and this relationship is enhanced in
the grassland, but weakened in the forest and irrigated
agricultural areas. Using the NDVI temporal series from
National Oceanic and Atmospheric Administration (NOAA)
AVHRR image, Yang et al. (2006) found that there is no
significant trend in alpine vegetation cover in the source
regions of the Yellow River during 1982–2001, and the
vegetation cover is sensitive to the temperature change.
However, the vegetation cover in the source regions presents
a common degradation tendency if the analysis focuses only
on the period of 1980–2000, and the decreasing precipitation
affects the plant cover greatly (Guo et al., 2008). Given the
time limitation of NOAA AVHRR, Xin et al. (2008)
extended the NDVI series by regressing with the SPOT VGT
(1999–2006) dataset. They discovered that the NDVI of
sandy land vegetation, grassland and cultivated areas show a
significant increasing trend in the Loess Plateau, but that the
NDVI for the forest shows a decreasing trend, and a
significant correlation exists between vegetation cover and
precipitation.
However, more efforts are still needed due to insuffi-
ciencies in the previous studies: (1) Lack of updated NDVI
Copyright # 2010 John Wiley & Sons, Ltd.
time-series for the whole basin: most of the pre-existing
research concentrated on the period between 1980 and 2000.
(2) Lack of spatial analysis for the climatic influences has
been a problem, most of the past studies mainly applied
to temporal correlation when analysing the climatic effects.
(3) Lack of systematic studies in terms of different erosion
regions; actually, the Yellow River basin can be divided into:
water erosion, wind erosion and freeze–thaw erosion
regions. This study investigates the dynamic change of
vegetation cover in water, wind and freeze–thaw erosion
regions in the Yellow River basin. A longer time-series
(1982–2006) was considered for interpretations of both
temporal and spatial variations of vegetation cover. This
study is of primary importance for understanding runoff
production, soil erosion and integrated river basin manage-
ment.
STUDY AREA
The Yellow River (Huanghe) is the second largest river in
China, with a total length of 5464 km. It originates in the
northeast of the Tibetan Plateau, runs across the Loess
Plateau of North China and the Ordos Plateau and flows
eastwards to the Bohai Sea, via semi-arid and semi-humid
regions (Figure 1). The Yellow River basin (7�52� 105 km2)
is one of the most important basins in China, directly
supporting a population of 130 million, mostly farmers and
rural people. The Yellow River basin covers nine provinces,
i.e. Qinghai, Sichuang, Gansu, Ningxia, Inner Mongolia,
Shaanxi, Shanxi, Henan and Shandong. Due to the
overexploitation of natural resources and expanding human
economic production, the Yellow River basin has changed
markedly with serious soil and water loss and degradation of
the total eco-environment. Nowadays, the Yellow River is
LAND DEGRADATION & DEVELOPMENT, 23: 62–71 (2012)
64 C. Y. MIAO ET AL.
well known for its tremendous sediment load and is
frequently referred to as a mud river. The Yellow River
annually carries 1�6 billion metric tons of sediment to the
sea, and the average annual erosion rate of the entire Yellow
River Basin reaches 2480 t km�2, which is the highest of any
major river system worldwide (Shi and Shao, 2000), and
accounts for 1/15 of the sediment discharge of the world’s
rivers (Zhang et al., 2009).
According to the Second Soil Erosion Survey with Remote
Sensing Technology (1990s), the erosion types in the Yellow
River basin include: water erosion, wind erosion and freeze–
thaw erosion, and each erosion type accounts for 73�87,
16�57 and 9�56 per cent area of the whole Yellow River
basin, respectively (Figure 1).
MATERIALS AND METHODS
Data Source and Pre-treatment
The Global Inventory Monitoring and Modeling Studies
(GIMMS) NDVI dataset was derived from the NOAA/
AVHRR, and provides information about the monthly
changes in terrestrial vegetation during the period from
August 1981 to December 2006. The GIMMS data are based
on 15-day interval with 8 km spatial resolution (Tucker
et al., 2005). Due to incomplete data in 1981, the dataset
used for this research is from 1982 to 2006 and consists of
600 half-monthly GIMMS NDVI images. The GIMMS
NDVI dataset largely reduced the variation of NDVI caused
by solar zenith angle change through drift correction (Piao
et al., 2003). It has also been corrected for these aspects:
distortions caused by cloud cover (Vermote et al., 1997),
sensor inter-calibration differences (Vermote and Kaufman,
1995), solar zenith angle and viewing angle effects, volcanic
aerosols and interpolation of missing data in the Northern
Hemisphere during the winter (Jin et al., 2008).
The time-series of daily precipitation and temperature
records from 1982 to 2006 at 175 climatological stations
were collected for this study. The stations in and around the
Yellow River basin were shown in Figure 1. According to the
Chinese Bureau of Meteorology Standards, annual climatic
datasets were derived from daily data. The climatic data
were provided by the National Meteorological Information
Center, China Meteorological Administration.
Data Processing
To further eliminate the influence of clouds, atmosphere and
solar altitude angle, the international universal Maximum
Value Composites (MVCs) technique was used to get
monthly maximum NDVI (Stow et al., 2007), which selects
the highest NDVI at each pixel from GIMMS NDVI (15-day
interval) (Zhou et al., 2003). The annual average NDVI and
seasonally integrated NDVI (SINDVI) were calculated
Copyright # 2010 John Wiley & Sons, Ltd.
according to the monthly maximum NDVI. Annual average
NDVI is the mean value of 12 monthly maximum NDVI, and
SINDVI is the sum of NDVI values for each pixel and all
time intervals of MVCs for which the NDVI exceeds a
critical value (commonly NDVI> 0�1)(Stow et al., 2003).
The NDVI values in the three erosion regions were obtained
using the GIS software of ArcInfo 9�01.
Research Methods
The statistical indexes variation coefficient (Cv) and trend
coefficient (r) were adopted to analysed the characteristics of
NDVI series. The variation coefficient (Cv) is a normalized
measure of dispersion of a probability distribution calcu-
lated by eliminating the effects of unit and mean difference.
It is defined as the ratio of the standard deviation to the mean
(Bruland and Richardson, 2004) (Equation 1):
Cv ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1
n�1
Pni¼1
xi�xð Þ2
s
x(1)
where, n is the number of years for NDVI, xi is the NDVI in
the ith year and xis the multi-year average NDVI value.
Generally, Cv< 0�1 was regarded as weak variability,
0�1�Cv�1 as moderate variability and Cv> 1 as strong
variability (Hu et al., 2005). Trend coefficient (r) was used to
illuminate the long-term change direction and extent of
variant. In this study, it can be calculated by the process of
linear regression between the NDVI series and the time
series (Shin and Deng, 2000; Miehle et al., 2006)
(Equation 2):
r ¼
Pni¼1
xi�xð Þ i�tð ÞffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiPni¼1
xi�xð Þ2 Pni¼1
i�tð Þ2
s (2)
where t is the half of the time-series’ length. A positive value
of r indicated a linear increasing trend of the vegetation
cover during the interested period. On the contrary, a
negative value of r denoted a decreasing trend. The absolute
value of r reflected the increase or decrease speed (Gao et al.,
2009).
RESULTS
Spatial Distribution of Vegetation Cover
Based on the interannual average GIMMS NDVI (1982–
2006), the lowest vegetation cover appeared in the wind
erosion region (annual average NDVI range between 0 and
0�2), and followed by the freeze–thaw erosion (annual
average NDVI range between 0�1 and 0�4) (Figure 2). The
highest vegetation cover was primarily distributed in the
LAND DEGRADATION & DEVELOPMENT, 23: 62–71 (2012)
Figure 2. Spatial distribution of the annual average NDVI in the YellowRiver basin (1982–2006). This figure is available in colour online at
wileyonlinelibrary.com
VEGETATION COVER DYNAMICS (1982–2006) 65
water erosion region (annual average NDVI range between
0�2 and 0�8). Nevertheless, exceptions did exist for lower
vegetation cover in the water erosion regions nearby the
wind erosion region. Overall, higher vegetation cover often
appeared in the southern (especially in Xi’an and its
surrounding areas) and eastern areas than in the northern and
western areas in the whole Yellow River basin.
Interannual Vegetation Cover Variation
It was found that the annual NDVI in the three erosion
regions showed an increasing trend with a 95 per cent
confidence level during 1982–2006 (Figure 3). The Spear-
man correlation R are 0�67 (whole basin), 0�58 (water
erosion region), 0�55 (wind erosion region) and 0�70
(freeze–thaw erosion region). The increasing NDVI demon-
strated the improving ecosystems in the basin, and the
Figure 3. Temporal variation of average annual vegetation in the YellowRiver (1982–2006). This figure is available in colour online at
wileyonlinelibrary.com
Copyright # 2010 John Wiley & Sons, Ltd.
distinct fluctuation reflected different functions from
external factors in the three regions. In the Yellow River
basin, the vegetation cover improved rapidly after the low
value in 2000 (Figure 3). Annual NDVI value in the water,
wind and freeze–thaw erosion regions were: 0�28–0�32,
0�15–0�20 and 0�23–0�29, respectively; the order agreed well
with the spatial distribution of NDVI as shown in Figure 2.
Because of the large percentage, the interannual fluctuated
characteristic of NDVI in the water erosion region was
synchronous with the whole basin. The slope of regression
line, as shown in Figure 3, exhibits the increasing rate of
NDVI. It was found that the vegetation cover in the Yellow
River increased by the rate of 0�075 per cent per year.
Among these three major erosion regions, the highest
increasing rate appeared in the freeze–thaw erosion region,
followed by the water erosion region and then by the wind
erosion region. The mean increasing rates of NDVI were
0�124, 0�071 and 0�057 per cent per year, respectively. In
addition, a statistically significant trend of SINDVI was also
detected in the Yellow River (Figure 4). Compared with the
NDVI, the vibration of SINDVI series in the Yellow River
were more obvious. Interannual variation in SINDVI was
caused by variations in the magnitude of NDVI values in
some years and by different season lengths in other years (or
a combination of both factors).
Spatiotemporal Variation of Vegetation Cover
In the Yellow River basin, almost all the variation coefficient
Cv of vegetation cover concentrated in the range of 0–0�2during the period of 1982–2006, and exiguous pixels with
variation coefficient over 0�2 cannot be presented clearly in
the figure (Figure 5a). The weak variability (Cv< 0�1)
occupied the overwhelming majority of the area of the
Yellow River basin, and the moderate variability
(0�1�Cv�1) mostly distributed along the mainstream of
the Yellow River.
Figure 4. Temporal variation of SINDVI in the Yellow River basin (1982–2006).
LAND DEGRADATION & DEVELOPMENT, 23: 62–71 (2012)
Figure 5. The variation coefficient (a) and trend coefficient (b) in theYellow River basin during 1982–2006. This figure is available in colour
online at wileyonlinelibrary.com
66 C. Y. MIAO ET AL.
The vegetation cover change in the Yellow River basin
showed a significant spatial difference (Figure 5b). In the
freeze–thaw erosion region, nearly all areas presented an
increasing trend with a high trend coefficient. The eco-
environment in the water and wind erosion regions was
ameliorated in general; however, the area with decreasing
vegetation cover was still enlarged when compared with the
freeze–thaw erosion region. In the wind erosion regions, the
vegetation cover around Yinchuan City (ellipse-shaped zone
in Figure 5b) showed a degrading trend. In the water erosion
region, the degrading trend occurred in the area between
Taiyuan and Xi’an (ellipse zone in Figure 5b), which
belongs to the Fen River basin. In these two kinds of erosion
regions, both of areas with a degrading trend were close to
the mainstream.
Figure 6. The climatic condition in the Yellow River basin (1982–2000).(a) precipitation; (b) temperature. This figure is available in colour online at
wileyonlinelibrary.com
DISCUSSIONS
Spatiotemporal Characteristics of Vegetation Cover
The spatial distribution of vegetation cover (Figure 2) is
accorded with the natural condition in the Yellow River
basin. In the wind erosion region, the annual average
precipitation and temperature is 276�71 mm and 7�328C,
Copyright # 2010 John Wiley & Sons, Ltd.
respectively (Figure 6). Most of this region is classified into
arid and semiarid areas in China. All of the Tenggeli Desert,
the Kubuqi Desert and the Wulanbuhe Desert are located in
this region. The low-precipitation and serious desertification
conditions make it difficult for plants to grow, and results in
the poorest vegetation cover.
In the freeze–thaw erosion region, the location on the
Southern Qinghai Plateau and the high altitude leads to low
air temperature. The annual average temperature is �0�878C(Figure 6). It greatly shortens plant’s growing season and
counteracts the vegetation’s photosynthesis. At the same
time, due to the atrocious weather and sparse population,
there has been little need for ecological reclamation in the
freeze–thaw erosion region in past decades.
In the water erosion region, the annual average
precipitation and temperature were 487�10 mm and
17�778C (Figure 6). The moderate climate and the
reasonable soil favour plant growth. As a result, the annual
vegetation cover in the water erosion region is the best.
Zones in the water erosion region, which border the wind
erosion region, have less vegetation cover with low NDVI.
The reason is mainly that the natural conditions in this area,
are similar to the wind erosion region (Maowusu Desert lies
in this area).
LAND DEGRADATION & DEVELOPMENT, 23: 62–71 (2012)
Figure 7. The annual precipitation and temperature variation in the YellowRiver basin.
VEGETATION COVER DYNAMICS (1982–2006) 67
The primary vegetation cover in the wind and freeze–thaw
erosion regions is really poor, so it is easy to register a higher
trend coefficient, as long as the growing conditions are
improved (Figure 5b). The synchronous trend coefficient in
this region leads to a NDVI with the highest increasing rate
(Figure 3d). In the water erosion region, the relative high
vegetation cover depresses the increasing trend. Moreover,
the vegetation cover in the hilly and gully region of the Loess
Plateau showed a descending trend during 1982–2006, and
the result is consistent with the Xin et al. (2008). In this area,
there is a large population and extensive croplands; in order
to meet the need for food, cultivation of steep areas and
intensive landuse cause serious soil erosion, destroy the eco-
environment further and consequently the vegetation cover
is decreasing.
Influencing Factor of Vegetation Variation
The vegetation cover dynamic is influenced by the climatic
conditions and anthropogenic factors.
Climatic factors
According to variation coefficient Cv and trend coefficient r,
the annual precipitation during 1982–2006 in the Yellow
River basin followed a decreasing trend (r¼�0�14) with a
moderate variability (Cv¼ 0�12), but a significant increasing
trend (r¼ 0�82) and weak variability (Cv¼ 0�04) were
detected for the annual average temperature (Figure 7).
Analysing the correlation between interannual NDVI and
the climatic factor indicated that the vegetation cover is
more sensitive to the temperature than precipitation, and the
correlation between annual NDVI and annual average
temperature in the whole Yellow River basin is significant at
the 95 per cent confidence level, using the Spearman
correlation R¼ 0�65. If the examination is focused-down to
the level of spatial pixel, it is found that the precipitation and
temperature influence the vegetation cover in a more
complicated manner (Figures 8,9 and 10). Generally, the
vegetation cover in the wind erosion region shows a positive
correlation with annual precipitation and negative corre-
lation with temperature (Figure 8). During the plant growth,
dryness is the great disadvantage in wind erosion region.
Warmer conditions might accelerated evapotranspiration,
especially in Spring and Summer, the higher temperature
aggravates the water deficiency, and as a result, suppresses
the growth of vegetation (Figure 9). Plentiful precipitation
will alleviate desertification, and afford water for growth. It
is found that the precipitation in Summer supports
vegetation and helps reduce wind erosion (Figure 10).
Compared with the wind erosion region, the reverse
phenomenon occurred in most of the freeze–thaw erosion
region. Along with the increasing temperature, the time
needed for thawing the frozen soil layer is shortened, and the
growing season is prolonged, which is beneficial to plant
Copyright # 2010 John Wiley & Sons, Ltd.
growth, so the vegetation cover gave a positive correlation
with the annual temperature (Figures 8b and 9). However, a
negative correlation between the vegetation cover and
annual precipitation is abnormal (Figures 8a and 10). The
anomaly can be explained by the facts that (1) water
availability is not a critical limiting factor for vegetation
growth in the freeze–thaw erosion region. Water is relatively
plentiful in this region and the area of freeze–thaw is less
than 15 per cent of the whole Yellow River basin, but
contributes about 35 per cent of total water resources in the
basin (Zheng et al., 2009). (2)The types of land use in this
region are more sensitive to temperature and solar radiation
than precipitation. Alpine and subalpine grasslands occupy
the overwhelming majority of the land in the freeze–thaw
erosion region according to the IGBP DISCover dataset with
1 km resolution (Loveland et al., 2000). When compared
with the precipitation, it is reported that the temperature
and solar radiation play more significant effects during the
grassland growth (Yang et al., 2003). Consequently,
the increasing temperature and solar radiation facilitate
the vegetation cover in this region although the precipitation
is decreasing. (3) Part of precipitation in the freeze–thaw
LAND DEGRADATION & DEVELOPMENT, 23: 62–71 (2012)
Figure 8. Correlation between annual average NDVI and climate factors (1982–2000); (a) with annual precipitation, (b) with annual temperature. This figure isavailable in colour online at wileyonlinelibrary.com
Figure 9. The correlation between monthly NDVI and monthly average temperature. This figure is available in colour online at wileyonlinelibrary.com
Copyright # 2010 John Wiley & Sons, Ltd. LAND DEGRADATION & DEVELOPMENT, 23: 62–71 (2012)
68 C. Y. MIAO ET AL.
Figure 10. The correlation between monthly NDVI and monthly precipitation. This figure is available in colour online at wileyonlinelibrary.com
VEGETATION COVER DYNAMICS (1982–2006) 69
erosion region falls in the form of snow. Generally, the
NDVI is expressed on a scale between �1 and + 1. GIMMS
NDVI ranges between �0�2 and 0�1 for snow, inland water
bodies, deserts and exposed soils, and increases from about
0�1 to 0�7 for increasing amounts of vegetation (Zhou et al.,
2001). In the freeze–thaw erosion region, part of precipi-
tation falls in the form of snow (Figure 6b), which influences
the calculation of NDVI to a certain extent. In particular the
affects the water erosion region. The four ellipse zones in
Figure 8 shows a reversed trend with the rest of water erosion
region. The ellipse zone belongs to the Fen-Wei basin, where
the relatively flat terrain was developed into irrigated
farming land. The irrigation area is more than 231�6 ha
(Yang et al., 2004), and according to the land use map of the
Yellow River basin, the crops planted there mainly include
paddy rice and winter wheat. Increasing temperature is
beneficial to crop growth (especially for winter wheat), so
there is positive correlation between yearly vegetation cover
and annual temperature (Figures 8b and 9). A leading
irrigation area in the Yellow River basin, the Fen-Wei River
basin is seldom dependant on precipitation, it is mainly
supplied from the upper reaches by watercourse. It was
estimated more than 50 per cent water of irrigation in the
Fen-Wei River basin comes from a diversion project
(YRCC, 2000), which channels the streamflow into crop-
lands. At the same time, the precipitation in the Fen-wei
River basin shows a declining trend over the past 20 years
Copyright # 2010 John Wiley & Sons, Ltd.
(Zuo, 2006; Su et al., 2007). As a result, the seemingly
abnormal positive correlation appeared in the ellipse zone.
The rest of the region is mainly hilly and gully Loess
Plateau. It is influenced by desert wind erosion.
Anthropogenic factors
Cimate change is one of the most important factors
influencing Yellow River basin spatiotemporal variation
of vegetation. However, the impacts from human activities
should not be neglected. Social and economic factors, such
as national policy, people’s consciousness, agricultural
modernization, economic level and life style change, might
profoundly affect the vegetation (Vicente-Serrano et al.,
2004). According to the data from the State Forestry Bureau,
since the 1980s, the new area of forest planting has been
500� 104 hm2 per year in China. In the Yellow River basin,
new afforestation is estimated to have been 52�59� 104 hm2
during 1991–1999 (Yang et al., 2002).
It was found that the vegetation cover has increased
quickly since 2000; the rate far exceeds that in the period
1982–2000 (Figure 3). The temperature after 2000 in the
Yellow River basin has shown a decreasing trend (Figure 7).
So, the vegetation cover increased sharply since 2000 mainly
due to human factors. Indeed, the most effective impacts
from human activities has been the ‘Grain for Green’ (GFG)
programme, which was launched by the Chinese Govern-
LAND DEGRADATION & DEVELOPMENT, 23: 62–71 (2012)
70 C. Y. MIAO ET AL.
ment at the end of 1999. The objective of this programme is
to increase the vegetation coverage on steep slopes by
planting trees or sowing grass on former cropland. Farmers
are encouraged to take land units on steep slopes out of
production and to plant trees. At the same time, farmers
participating in the GFG programme will be compensated
with free grain and cash payments. The tree seedlings are
provided for free by the Government. The GFG was
practiced experimentally in three provinces (Sichuan,
Shannxi, Gansu) in 1999, and has then popularized
Countrywide until 2002, which explains why the vegetation
cover increased quickly after it the minimum in 2000. The
total area of the GFG programme in the Yellow River basin
reached 8�27 million hectares during 1999–2006 (YRCC,
2008), which resulted in a significant increase of the
vegetation cover on farmland (Zhou et al., 2009).
CONCLUSIONS
The results of this study suggest that, under the dual effects
of natural conditions and human activities, the vegetation
cover in the wind erosion region is lowest, followed by the
freeze–thaw region and then by the water erosion region. So
the wind erosion region is the critical area for eco-
environment reconstruction. The interannual vegetation
cover dynamic shows a continued increase from 1982 to
2006 in the whole Yellow River basin, but it has a significant
spatial variation. The vegetation cover in the Fen River basin
shows a descending trend during 1982–2006, which reflects
the negative effects of human action. This area should be
singled-out for further eco-environment reconstruction
because the vegetation cover variation in the Yellow River
basin is greatly influenced by the water erosion region. In the
Yellow River basin, all the variation is weak or moderate,
and shows little variability (Cv< 0�1) can be recognized for
most of the area of the Yellow River basin.
Vegetation cover in the Yellow River basin is influenced
by climate factors, especially by temperature. In the wind
erosion region, warmer conditions might accelerate the
evapotranspiration and suppress growth, but plentiful
precipitation should alleviate any desertification. If there
is thawing in the frozen erosion region, increasing
temperature will prolong the plant growing season. In the
water erosion region, the vegetation cover in the Fen-wei
basin showed a negative correlation with annual precipi-
tation. The latter needs further study in the future. In the rest
of the area of the water erosion region high precipitation and
low temperatures will be helpful to plant growth. Besides the
effects of climatic factors, human activities contribute to the
vegetation cover variation. Especially after the implementa-
tion of the GFG, the role of human management in
increasing the vegetation cover is obvious.
Copyright # 2010 John Wiley & Sons, Ltd.
ACKNOWLEDGEMENTS
Funding for this research was provided by the National
Natural Science Foundation of China (grant no. 41001153)
and State Key Laboratory of Earth Surface Processes and
Resource Ecology (grant no. 2009-KF-03). We are grateful
to the Yellow River Water Conservancy Commission
(YRCC) (China), the National Meteorological Information
Center (China), and the Flemish Institution (Belgium), for
permitting us access to data on soil erosion division map,
meteorological information, and vegetation cover related to
the Yellow River basin.
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