Tibetan Plateau serves as the sources of several big rivers such as Yangtze River and Yellow River. Due to the high
elevation of the plateau, it has profound thermal and dynamical influence on both local and global climate and
atmospheric circulation. Land surface temperature (LST) plays a significant role in climate change and glacier melting.
In this paper we present our study on mapping land surface temperature variations for the years 2005-2006 in the plateau
using MODIS satellite data. Since the plateau has a very rough ground surface that is difficult to estimate the necessary
parameters for the mapping, we have developed a practical approach for LST retrieval from the MODIS thermal band
data. The approach was alternated from the split window algorithm proposed by Qin et al. (2001) for NOAA-AVHRR
data. Detailed methods for atmospheric transmittance and ground emissivity have been presented in the paper. Results
from our study indicate that ground temperature in the plateau is featured with obvious spatial and temporal variations.
Generally the temperature in winter and spring is less than 0°C and it is also not very high in summer, due to the high
altitude. Because of topological form, Chaidamu Basin of the plateau has the highest temperature in summer, usually
high up to above 40°C. Our study provides an alternative to understand the environmental changes in the plateau that
shape significant impacts on atmospheric dynamics of East Asia and South Asia.
As an important pasture region, Tibet has about 82 million hectares of natural grassland, accounting for 68.11% of its
total territory. Above 90% of Tibetan grassland belongs to the types of alpine meadow steppe and alpine steppe with
highly nutritious forage plant. Animal husbandry constitutes a major part of agricultural economy in Tibet. It is believed
that snow disaster become a significant threat to the development of animal husbandry in Tibet. The disaster often
happens in winter and spring as a result of complicated mountainous features and mutable climatic conditions. Statistics
indicates that, on average, there is a slight snow disaster for each 3-year, a medium disaster within 5 to 6 years, and a big
disaster in 8-10 years. Large numbers of animals died of hungry and cold during the disaster period. Huge economic loss
due to the disaster had brought giant difficulties to local herdsmen in Tibet. Accurate and timely monitoring of snow
cover for snow disaster evaluating is very important to provide the required information for decision-making in
anti-disaster campaigns. Remote sensing has many advantages in snow disaster monitoring hence been extensively
applied as the main approach for snow cover monitoring. In this paper we present our study of snow cover monitoring
and snow disaster evaluating in Tibet. An applicable approach has been developed in the study for the monitoring and
evaluating. The approach is based on the normalize difference of snow index (NDSI) and DEM retrieved from MODIS
and GIS data. Using the approach, we analyzed the snowstorm occurring in mid-March 2007 in southern Tibet. Results
from our analysis indicated that the new approach is able to provide an accurate estimate of snow cover area and snow
depth in southern Tibet. Thus we may conclude that the approach can be used as an efficient alternative for snow cover
monitoring and snow disaster evaluating in Tibet.
Grassland ecosystem degradation and desertification has been highly concerned in China for years because such
degradation is perceived to directly relate with the occurrence of sandstorms invading into north China. In this study we
intend to map the spatial-temporal variation of vegetation cover density from remote sensing data in Hulun Buir, a
typical grassland ecosystem with the highest biomass productivity in Inner Mongolia of China. Since NDVI is a good
indicator of vegetation, a practical approach had been developed in the study to map the spatial-temporal variation of the
vegetation cover. The MODIS satellite data were used for the mapping. Results from our study indicated that the
vegetation cover rate had been steadily decreasing in recent years, with relatively high spatial and temporal variation.
Our study reveals that the rate on average has a trend of steadily decreasing in recent years. In 2000 the rate was above
80.6% on average, while it decreased to below 76.5% in 2006. Generally the west part of the region had much lower
vegetation cover rate than the east part, probably due to the fact that the east part was dominated with forest ecosystem
while the west part with fragile grassland. The counties of Xinbaerhuyou Banner and Manzhouli in the west part had the
lowest vegetation cover rate among the 13 counties. As to the grassland types, lowland meadow had the highest
vegetation cover rate while the temperate meadow and steppe had the lowest, indicating that ecosystem degradation was
very serious in the temperate meadow and steppe, which were mainly distributed in the west part of the region. Though
many factors might contribute to the decrease of vegetation cover, annual precipitation vibration had very good
correspondence with the up-and-down change of vegetation cover in the region. In addition, overgrazing also played an
important role in accelerating the degradation under the drought year. Therefore, we were able to conclude that the
grassland ecosystem in Hulun Buir was under a very serious situation of degradation and desertification. Our study
suggested that the change of vegetation cover rate could be an applicable indicator for grassland ecosystem monitoring
required urgently to combat grassland degradation and desertification in arid and semiarid region.
Land use/cover change (LUCC) has significant impacts on regional environment. Land surface temperature (LST) is an
important indicator for assessment of regional environment especially in big cities where urban heat island is very
obvious. In this study, remote sensing and geographic information systems (GIS) were used to detect LUCC for
assessment of its impacts on spatial variation of LST in Urumqi, a big city in northwestern China. Two Landsat
TM/ETM+ images respectively in 1987 and 2002 were examined for LUCC detection. LST and NDVI were computed
from the images for different land use/cover types. Impacts of LUCC on regional environment can be assessment
through LST difference during the period. Our results showed that land use/cover changes were very obvious in Urumqi
between 1987 and 2002 due to rapid expansion of the city. Urban/built-up land increased by almost twice in the period,
while the barren land, the forestland and water area declined. The increase of urban/built-up land was mainly from the
barren land. Spatial distribution of LST in the city has been highly altered as a result of urban expansion. The
urban/built-up area had LST increase by 4.48% during the period. The LST difference between built-up land and other
land use/cover types also significantly increased between 1978 and 2002, with high LST increase area corresponding to
the urban expansion regions. Moreover, changes of vegetation also had shaped many impacts on spatial variation of LST
in the city. We found that NDVI has a negative correlation with LST among the land use/cover types. This probably is
due to the ecological function of vegetation in cooling down the surface from high evapotranspiration. The study
demonstrated that combination of remote sensing and GIS provided an efficient way to examine LUCC for assessment of
its impacts on regional environment in big cities.
Drought is very severe in North China Plain, where winter wheat is one of the most important cropping systems. In this paper, we present an approach to map drought status of winter wheat in the plain for better farming management. The approach is based on the temperature-vegetation dryness index (TVDI) computed from the wet and dry edges of Ts-NDVI space. Using the MODIS data, we applied the approach to map drought status in North China Plain for the winter wheat growing period from March to May in 2006. Our results show that spatial variation of agricultural drought is very obvious in the region. Severe drought was observed in eastern Hebei, western Shandong, and northwestern Henan province respectively. The weather reports from China Meteorological Administration were used to validate our mapping results of the drought status. The highly accordance of our drought mapping results with the reported drought distribution from CMA confirms the applicability of TVDI approach in drought mapping in North China Plain.
Grassland degradation in grassland ecosystems of China has been highly concerned in recent decades. Grassland growing is an important element for identification of grassland degradation. In this paper we intend to develop an applicable method for grassland growing monitoring in China using the EOS/MODIS data. Firstly the normalized difference of vegetation index (NDVI) can be calculated from April to October within grassland growing period in 2005 and 2006. In order to evaluate the grassland growing, vegetation index R was proposed, which was calculated from the NDVI value difference of the two years 2006 and 2005. According to the R value, five grades (from grade1 to grade5) were obtained: worse, slightly worse, balance, slightly better and better. Grassland region in China can be divided into a number of small sub-regions for determination of different regions and grassland types. Our results indicate that grassland growing was better in 2006 than in 2005. The grassland with balance, slight better and better growing accounted for 71.43% of the total grassland area, the area is 251.42 thousand KM2. The overall growing of 2006 is: Grade3>Grade4>Grade2>Grade5>Grade1.Valuation of the grassland growing is thus urgently required for better administration of the grassland ecosystem for sustainable development.
Hulun Buir represents the best grassland in Inner Mongolia. Due to intensive anthropogenic activities especially unreasonable grazing, desertification has been an important environmental problem in the grassland. In the paper we intend to develop an applicable approach for desertification monitoring in the grassland. Since vegetation is the most essential factor of grassland and desertification actually implies the declination of vegetation in the grassland, an index indication desertification severity has been constructed from vegetation cover fraction. Using MODIS satellite data, we firstly computed NDVI and then computed vegetation cover rate in the grassland. The rate is consequently used to construct the desertification index (DI) for evaluation of desertification severity. Using precipitation and temperature data from 45 points, we validate the capability of DI in representing the severity of actual desertification in the grassland. The general accordance of precipitation and temperature with DI demonstrates the applicability of the proposed approach for desertification in the grassland. Using the approach, we analyzed the changes of desertification in the grassland in recent years. Results showed that desertification process in the grassland are accelerating in recent years, with rate of 1% annually. The acceleration of desertification implies that grassland ecosystem is under evolution of degradation in spite of rapid economic development in the region. Our study suggests that necessary measures should be urgently employed to protect the grassland from further desertification.
Rangeland in Inner Mongolia is an arid ecosystem with vulnerability. Anthropogenic activities especially over-grazing
have been believed to be a leading factor shifting the vulnerability into actual degradation in the ecosystem. Net primary
productivity (NPP) is an important indicator for vulnerability monitoring in arid ecosystem. In this study we use the
vegetation photosynthesis model to estimate NPP of rangeland ecosystem in Inner Mongolia. The objective is to examine
the spatial variation of NPP in Inner Mongolia and to highlight vulnerable areas for sustainable development. Several
improvements have been done to the model especially in its parameterization. Land surface temperature required by the
model was estimated from split window algorithm proposed for MODIS thermal band data. Using the MODIS image
data and the ground climate datasets, we applied the improved model to estimate the NPP in 2003 in Inner Mongolia.
Our results showed that mean NPP was 192.03gC m-2 Gr-1 in Inner Mongolia in 2003. Spatial variation of the NPP was
very obvious. Very low NPP was observed in the western parts while relatively high NPP could be seen in the eastern
and northeastern parts. For various type rangelands, temperate alpine meadow is the highest. Although the mean NPP of
temperate steppe is not high, its area is the largest in Inner Mongolia, so it has the highest ratio to total NPP. Comparison
of our NPP with similar studies from conventional methods confirms the accuracy of our estimation.
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