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Land-surface water is an important factor influencing the regional environment and climate and is a key factor in the Tibetan Plateau, which is one of the most sensitive regions to global changes. Because of the high elevation, complex topography, and erratic weather of the Tibetan Plateau, direct measurement of the area of every lake is largely unfeasible. Moreover, complex natural geographic conditions increase the difficulty of image processing and information extraction with remote sensing because they enhance the uncertainty of quantitative data retrieved with satellites. Methods based on spectral features do not generate the expected results of lake area over the Tibetan Plateau due to a lack of distinction between water and other land objects, especially snow, vegetation, and low cloud cover. Therefore, a new method to extract lake area from satellite images in the Tibetan Plateau is needed. In this article, an automatic method was proposed to evaluate lake area during the wet season (from 1 September to 31 October) on the Tibetan Plateau with multi-day Advanced Very High Resolution Radiometer (AVHRR) remote-sensing images on board the Meteorological Operational satellite-A (MetOp-A) satellite. The method considers both spectral and textural features of lakes and does not need a cloud mask as an input. In addition, the Mixture Tuned Matched Filtering (MTMF) algorithm was applied to decompose the mixed pixels to better identify lakes and estimate the lake area. Based on daily lake identifications, the wet season’s lake data were composited with the maximum value composition (MVC) method to determine the lake area. A comparison of our work with the manually interpreted results from Landsat Thematic Mapper (TM) images and observational reports demonstrates the accuracy and reliability of our approach. However, certain factors, i.e. the sensor zenith angle of the polar-orbit satellite and the topography, can affect the lake area extracted from the remote-sensing images. [ABSTRACT FROM AUTHOR]

The Yangtze River is the China's longest river and the third-longest river in the world. The river's source region in the Qinghai-Tibet Plateau is especially sensitive to global environmental change because of its high elevation and cold environment. Under the influence of global warming, aeolian desertified land has expanded rapidly in this area. To assess the trends in aeolian desertification from 1975 to 2005, remote-sensing and GIS technology were used to monitor the extent of aeolian desertification in 1975, 1990, 2000, and 2005. The data sources included Landsat multi-spectral scanner images acquired in 1975, Enhanced Thematic Mapper (ETM+) images acquired in 2000, and Thematic Mapper (TM) images acquired in 1990 and 2005. Images recorded between June and October were selected, when vegetation grew well, because aeolian desertified land was more easily recognized during this period. Thematic maps, including land use and geomorphologic maps, were used as supplementary data. Aeolian desertification maps (1:100000) were produced for each year from the Landsat images through visual interpretation. The area of aeolian desertified land increased by 2,678.43 km from 1975 to 2005, accounting for 8.8% of the total area of aeolian desertified land in 1975, an increase of 89.28 km a. Increasing mean annual temperature and the combination of a dry, cold, and windy climate in winter and spring were mainly responsible for the expansion of desertified land. [ABSTRACT FROM AUTHOR]