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Satellite remote sensing from space offers a unique way to monitor surface soil moisture on a large geographical scale. In this work, the general approaches to monitoring surface soil moisture for Tibet area were developed using Moderate Resolution Imaging Spectroradiometer (MODIS) data and ground observations. The result shows that MODIS Vegetation Supply Water Index (VSWI) and band-7 reflectance are significantly correlated with ground measured soil moisture and MODIS band 7 is a simple and more effective method to monitor soil moisture in Tibet with higher spatial resolution at 500 m in comparison with VSWI at 1000 m resolution.

Snow cover is an important component of the cryosphere, and the study on spatial and temporal variations of snow cover is essential for understanding the consequences and impacts of climate change ...

Based on the result of the first land resources survey in Tibet Autonomous Region (TAR) carried out in the late 1980s, land-use map of Lhasa area in 1990 is produced using aerial photographs obtained in April, May, and October 1991 for the main agricultural area in the river valleys and Landsat TM images acquired in the late 1980s and 1991 for the rest of the area. Using these remotely sensed data, land-use status of Lhasa area in 1991, 1992, 1993, 1995, 1999, and 2000 is mapped through updating annual changes of cultivated land, artificial forest and grass planting, grassland restoration, built-up area expansion, and so on. Land-use map for the Lhasa area in 2007 is made using ALOS AVNIR-2 composite images acquired on October 24 and December 26, 2007, through updating changes of main land-use types. Of which, based on the land-use status in 1990, 1995, 2000, and 2007, the spatial and temporal land-use change and dynamics in the Lhasa area located at central Tibetan Plateau from 1990 to 2007 are analyzed using GIS spatial analysis techniques in this chapter.

A new land-use status classification system is developed based on the first land-use status survey of Tibet Autonomous Region (TAR) to be applicable for mapping land-use status in Tibet with different spatial scales of remote sensing data from aerial photograph to orbit satellite. It is a hierarchically based three-level classification system and contains 8 level I, 34 level II, and 12 level III. Land-use status map for the Lhasa area located at central Tibetan Plateau is made based on the color infrared aerial photographs and Landsat Thematic Mapper (TM) using proposed classification system. Results show that in the Lhasa area the grassland covers the largest area extent with 71.48% of total land area, followed by unused land (16.88%) and water body (5.25%). Other land-use types account for less than 4%. Among these, cultivated land is 70021.72 ha., covering 2.37% of total land area, and is distributed in all counties except Damshung County in the north.

Land-cover classification is an important application area of satellite remote sensing. However, deriving thematic map from satellite imagery through classification approaches is not a straightforward task, especially from high-resolution satellite imagery. In this study, Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) multispectral composite image is successfully used to land-cover classification for the Lhasa area located at central Tibetan Plateau (TP) using maximum likelihood classifier. Accuracy assessment for final results is also made using quantitative approaches. Study shows that there is a good agreement between classification results and reference data for defined land-cover classes in central TP. The overall classification accuracy is 87.68%. Reference and ancillary data are increasingly available and are very useful for refining accuracy of classification results during postclassification process. The integration of digital elevation model (DEM) into land-cover classification is particularly important in mountain region since land-cover distribution in mountain region is spatially topography-dependent. Study also suggests that with increase of spatial resolution, how to effectively use the spatial information inherent in satellite remote sensing images to extract thematic maps for various applications remains a challenge and is an important task to be fulfilled in the future.

Fractional vegetation cover (FVC) is an important parameter in the study of ecosystem balance, soil erosion, and climate change and is often used to evaluate and monitor vegetation degradation and desertification. Remote sensing provides the only feasible way to estimate FVC at regional and global scales. In the present study, an empirical model of FVC estimation is developed for central Tibetan Plateau (TP) based on the relationships between vegetation indices from Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) and corresponding field measurements derived from digital camera, which is followed by in-depth analysis on the spatial distribution of vegetation coverage using proposed method. Study shows that a linear relationship exists between vegetation coverage from the field observation and MODIS NDVI with coefficient of determination of R2 = 0.90, which is slightly better than MODIS SAVI performance with R2 = 0.89 and is an optimal regression model for FVC estimation. Vegetation coverage ranges 20–90% in the most part of central TP, presenting moderate to high as a whole, and generally decreases from east to west with strong regional differences due to discrepancies in land-cover types, plant species, topography and water resources availability, and so on.

Land use is one of the most important ways that humans use land resources to meet their material, social, and cultural needs, and its spatial distribution pattern largely features topographic dependence in mountain regions. Study on spatial distribution of different land-use types in the Lhasa area at central Tibetan Plateau shows that the altitude difference between the highest and the lowest points is 3612 m with an average elevation of 4616 meters above sea level (masl), and most of land ranges from 3550 to 5500 masl with 92.27% of total land area. As a mountainous region, in the study area the flat land without slope gradient is limited in area and covers 23.70% of total land area. Most of cultivated land is in elevation range from 3550 to 4000 masl with covering 74.32% of total cultivated land, while forest distribution is spatially much broader and natural shrub is dominant cover type. Over 50% of settlement and built-up land is in elevation range from 3650 to 3750 masl. Grassland is the largest land-use type with 93.78% lying in elevation range from 4000 to 6000 masl, while lake covers the largest area in water body and is composed of eastern part of Namtso Lake within Lhasa area.

Biomass is an important component of grassland ecosystems and plays a critical role in the sustainable use of grassland resources and the global carbon cycle. Satellite remote sensing provides an important approach for estimating aboveground biomass (AGB) at large spatial scales while biomass harvesting offers reliable and site-specific biomass magnitude and is only way to give indispensable ground truth for satellite remote sensing. In this study, estimate models for grassland AGB for the Lhasa area located at the central Tibetan Plateau (TP) are developed based on the relationships between the field measurements and Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices (NDVI, EVI), and the models are validated against independent field measurements. The result shows that exponential relationships exist between AGB and MODIS vegetation indices. MODIS NDVI is more effective to estimate grassland AGB in the study area with R2 = 0.63 than EVI with R2 = 0.50 and is an optimal regression model for AGB estimation. For green AGB estimation, the performance of NDVI (R2 = 0.69) is also better than EVI (R2 = 0.59). In the study area, AGB spatially presents decreases from east to west, with great regional differences due to inhomogeneous grassland types and impact of various environmental and climatic factors. AGB is above 100 g/m2 in some eastern regions whereas it is lower than 20 g/m2 in the west.

Some new features concerning the diurnal variation of precipitation over the Tibetan Plateau (TP) are revealed from rainfall data acquired by a network of rain gauge stations and estimated by the Climate Precipitation Center Morphing (CMORPH) technique collected during the summer of 2010 and 2011. Maxima in precipitation amount and frequency are associated with the afternoon-to-evening precipitation regime at approximately 60% of the stations in the network. CMORPH data also capture this pattern, but miss the late morning peak that occurs at some stations. The timing of maximum occurrence agrees well with the diurnal cycle of synoptic conditions favouring the development of precipitation over this area. There is no distinct west-to-east propagation of the diurnal cycle, implying that the diurnal cycle is more driven by local effects than by large-scale circulation. It turns out that the diurnal cycle in precipitation frequency depends largely on topography and landscape. The geographical transition in precipitation peak time is distinct from hilly regions (daytime peak) towards lakes and valleys (evening-to-nocturnal peaks). Stations located in mountainous regions (valleys) tend to experience more precipitation in either late morning or early afternoon (late afternoon or evening). Overall, precipitation amount shows a similar topographic dependence, as does the precipitation frequency, suggesting that local-scale effects, such as the mountain valley circulation effect, has a great impact on the diurnal variation in precipitation when large-scale dynamical processes are weak. A possible mechanism for the non-uniform diurnal cycle of precipitation over the TP is proposed. The major conclusion is that plateau-scale synoptic systems, as well as local circulation systems caused by the complex topography, should be taken into account when determining the diurnal variation in precipitation over the TP.

Measuring rainfall from space appears to be the only cost effective and viable means in estimating regional precipitation over the Tibet, and the satellite rainfall products are essential to hydrological and agricultural modeling. A long-standing problem in the meteorological and hydrological studies is that there is only a sparse raingauge network representing the spatial distribution of precipitation and its quantity on small scales over the Tibet. Therefore, satellite derived quantitative precipitation estimates are extremely useful for obtaining rainfall patterns that can be used by hydrological models to produce forecasts of river discharge and to delineate the flood hazard area. In this paper, validation of the US National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) RFE (rainfall estimate) 2.0 data was made by using daily rainfall observations at 11 weather stations over different climate zones from southeast to northwest of the Tibet during the rainy season from 1 June to 30 September 2005 and 2006. Analysis on the time series of daily rainfall of RFE-CPC and observed data in different climate zones reveals that the mean correlation coefficients between satellite estimated and observed rainfall is 0.74. Only at Pali and Nielamu stations located in the southern brink of the Tibet along the Himalayan Mountains, are the correlation coefficients less than 0.62. In addition, continuous validations show that the RFE performed well in different climate zones, with considerably low mean error (ME) and root mean square error (RMSE) scores except at Nielamu station along the Himalayan range. Likewise, for the dichotomous validation, at most stations over the Tibet, the probability of detection (POD) values is above 73% while the false alarm rate (FAR) is between 1% and 12%. Overall, NOAA CPC RFE 2.0 products performed well in the estimation and monitoring of rainfall over the Tibet and can be used to analyze the precipitation pattern, produce discharge forecast, and delineate the flood hazard area.

Land use change is the result of the interplay between socioeconomic, institutional and environmental factors, and has important impacts on the functioning of socioeconomic and environmental systems with important tradeoffs for sustainability, food security, biodiversity and the vulnerability of people and ecosystems to global change impacts. Based on the results of the First Land Use Survey in Tibet Autonomous Region carried out in the late 1980s, land use map of Lhasa area in 1990 was compiled for the main agricultural area in Lhasa valley using aerial photos obtained in April, May and October 1991 and Landsat imagery in the late 1980s and 1991 as remotely sensed data sources. Using these remotely sensed data, the land use status of Lhasa area in 1991, 1992, 1993, 1995, 1999 and 2000 were mapped through updating annual changes of cultivated land, artificial forest, grass planting, grassland restoration, and residential area and so on. Land use map for Lhasa area in 2007 was made using ALOS AVNIR-2 composite images acquired on October 24 and December 26, 2007 through updating changes of main land use types. According to land use status of Lhasa area in 1990, 1995, 2000 and 2007, the spatial and temporal land use dynamics in Lhasa area from 1990 to 2007 are further analyzed using GIS spatial models in this paper.

The Normalized Difference Vegetation Index (NDVI) derived from NOAA AVHRR Global Vegetation Index (GVI) for Lhasa area in the central Tibetan Plateau from 1985 to 1999 and its relationship with climate conditions (precipitation and temperature) are established in this study. Climate data from the Lhasa meteorological station provided by the Tibet Climate Data Center are used for this analysis. The NDVI-derived vegetation growth patterns show very strong seasonal cycles and interannual variations. The growing season length varies between years. The correlation between NDVI and precipitation (r = 0.75, P < 0.01) in Lhasa area is higher than the correlation between NDVI and temperature (r = 0.63, P < 0.01), suggesting that NDVI is more sensitive to precipitation than temperature in this semiarid climate zone. Furthermore, the time series of NDVI demonstrate a positive trend from 1985 to 1999, which means that the vegetation biomass present on land surface is increasing. This trend is strongly correl...

Plant specimens are collected from the areas between latitude 27 ° 42′N and 40 ° 57′N, and longitude 88 ° 93′E and 103 ° 24′E, with an altitudinal range from 2210 to 5050 m above the sea level in Qinghai-Tibetan Plateau. The stable carbon isotope analysis indicates that two of Chenopodiaceae and six of Poaceae in the samples are C4 plants. Four of the C4 plants are found in 11 spots with altitudes above 3800 m, and Pennisetum centrasiaticum, Arundinella yunnanensis and Orinus thoroldii are present in six spots above 4000 m, even up to 4520 m. At low CO2 partial pressure, that sufficient energy of high light improving C4 plant’s tolerance of low temperature and precipitations concentrating in growing season probably are favorable for C4 plants growing at high altitude in Qinghai-Tibetan Plateau.

Using the brightness temperature data measured by an Advanced Microwave Scanning Radiometer (AMSR-E) and the in-situ measurement, this paper compared the accuracy and applicability of five snow-depth retrieval algorithms (Chang algorithm, GSFC 96 algorithm, AMSR-E SWE algorithm, the improved algorithm for Qinghai-Tibet Plateau and atmosphere-correction algorithm) in the regions of Xinjiang, Qinghai-Tibet Plateau, Inner Mongolia, Northeast China, Northwest China and the North China Plain. Generally, over the whole China area, the results of the study show that, the improved algorithm for Qinghai-Tibet Plateau shows a relatively higher accuracy, with a root-mean-square error (RMSE) of 9.16, 9.96 and 9.63cm and a mean relative error (MRE) of 59.77%, 52.79% and 48.47%. According to regional verification respectively, the accuracy algorithm for Xinjiang region is the GSFC 96 algorithm, the RMSE of which is 6.85cm~7.48cm; For Inner Mongolia, it is the QTP algorithm, the RMSE of which is 5.9, 6.11 and 5.46cm; and For Northeast China, it is also the Qinghai-Tibet Plateau algorithm, the RMSE of which is from 6.21cm to 7.83cm. None of the five algorithms is in a good quality for Northwest China and the North China plain regions. For the Qinghai-Tibetan plateau region, the author is not able to obtain the results of statistical verification due to a lack of actually measured data.

The middle reaches of Yarlung Zangbo River (YR) and its two tributaries is a region in central Tibet Autonomous Region where the industrial and agricultural economy is most concentrative and developed. Remote sensing of land surface parameters has significant meaning for crop growth monitoring, crop yield assessment and disaster monitoring. It also has great theoretical importance for understanding energy and water cycle in local area and even for surrounding regions. In this paper, four scenes data in 2003 under nearly clear weather conditions are selected as the spring, summer, autumn and winter cases. Different algorithms for AVHRR and MODIS data will be applied to retrieve land surface temperature (LST), albedo, Normalized Difference Vegetation Index (NDVI), vegetation coverage, emissivity, and water vapour content, respectively. The derived LST, albedo are validated with field measurements and MODIS products. The estimations are in good agreement with in-situ measurements, with MODIS retrievals being slightly better than those of AVHRR. This means that the adopted remote sensing retrieval algorithms are not only applicable but also simple for the study area. As called the "water vapour inflow corridor", the valleys of YR and its two tributaries are proved to have higher LST and larger atmospheric water vapour content. Spatiotemporal variations of land surface parameters in the middle reaches of YR and its two tributaries can also be clearly identified.