The edge of the Qinghai-Tibet Plateau is characterized by high topographic relief, significant tectonic motion, extreme precipitation, and densely populated active debris flow gullies. It is essential to scientifically categorize the debris flow gullies to understand their mechanisms, prevent and mitigate debris flow disasters, and find out strategies to restore the ecology. The present study carried out topographical measurements and statistical analyses of seven regions on the edge of the Qinghai-Tibet Plateau, in which active debris flow gullies are concentrated. The debris flow gullies are classified into three types by means of nonmetric multidimensional scaling. Type I is formed by rainstorms in exposed bedrock areas, Type II is formed by glaciers in exposed bedrock areas, and Type III is formed by rainstorms in depositional basins. The variation in landforms of the three types is analyzed using Kruskal-Wallis tests. The sources of loose material and the characteristics of water flow and sediment transport in all the three types of debris flow gullies are discussed from the aspects of geology, topography, and climate. It is shown that the activity of Type II increases along with the warming of the Qinghai-Tibet Plateau, and the activities of types I and III increase along with the frequency of extreme rainfalls.

Relief degree of land surface (RDLS) is one of the key indicators in the fields of suitability assessment of human settlements (SAHS) as well as resources and environmental carrying capacity (RECC) evaluation at the regional scale. Currently, there is still a lack of in-depth research on the determination of the optimal window size for the RDLS calculation and evaluation and its correlation analysis with two topographical parameters, e.g., elevation and relative height difference. These issues further affect the effective representation of the RDLS in the delineation of local to regional topographic relief. Therefore, an objective understanding of the RDLS in the Qinghai-Tibet Plateau of China greatly contributes to promoting the construction of national ecological security barrier and regional green development. In this study, based on the 30 m Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM Version 2), the optimal window size for calculating and evaluating the RDLS in the Qinghai-Tibet Plateau was accurately determined using the average change-point method, and the first 30 m RDLS thematic map for the Qinghai-Tibet Plateau was generated accordingly. Next, the interrelation between the RDLS and elevation and relative height difference was quantitatively examined. Based on that, the effective representation or geographical meanings of the RDLS in the plateau were defined. The results/conclusions include: (1) The optimum window size for the RDLS calculation and evaluation in the study area based on the 30 m GDEM is a rectangular neighborhood of 41×41 pixels, equaling to an area of about 1.51 km². The average change-point analysis approach shows that the optimum window size for regional RDLS analysis is unique. (2) The average RDLS of the study area is approximately 5.06, along with over 60% of the plateau ranging between 4.5 and 5.7. On the whole, the topographic relief increases from the northeast to the southwest and west parts. Gentle to small-relief landforms are mostly seen in the Qaidam Basin, the Southern Tibet Valley, and the Hehuang Valley (Yellow and Huangshui river valleys). Also, the differences in the local surface relief in varied latitudinal sections (along the mountain range) are small, while those at longitudinal level are big, showing hierarchical and regular fluctuations (crossing the mountain trending). (3) Correlation analyses showed that different values of the RDLS in the plateau correspond to geomorphic units with different elevations and relative height differences. The profile characteristics of the mountains in the Qinghai-Tibet Plateau based on different terrain reliefs indicate that the height above sea level of low mountains steadily increases first, then experiences sudden rise and severe fluctuation in surface relief, and finally forms the orderly ups and downs of the extreme mountains, e.g., the Himalayas.

In the big data era, data of population migration on the Internet has exerted great influence on conducting researches on the patterns of inter-regional population inflows and outflows. This study, based on Tencent's daily migration data (2015-2018), analyzed and explored the patterns of population inflows and outflows in the Qinghai-Tibet Plateau by means of methods like time series analysis, social networks analysis and space-time statistical analysis, and discussed the seasonal law of the fluid population between the study area and other cities in China and the network features of population interaction. The results indicated that: (1) The population flow in the Qinghai-Tibet Plateau was featured by seasonal variability, which could be represented as four seasons "Low, Medium, Mid-High, High" during the year. From 2015 to 2018, the Qinghai-Tibet Plateau in the interaction network of national urban floating population witnessed an increasing status. The population flow rate improved by 8.2%, and the ranking on the population mobility network increased by 24.5%. Relative to the Low season, the average daily population movements in the Medium season, Mid-High season and High season increased by 14.2%, 26.7% and 57.8%, respectively. (2) The population flow direction lied in the 45° fan-shaped range from NEE-67.5° to SEE-112.5°, and the Qinghai-Tibet Plateau had strong and frequent interactions with the capitals of the surrounding provinces. (3) Most cities across the country attached importance to a continual increase of the intensity of population interaction with the Qinghai-Tibet Plateau, and tourism had played a dominant role in promoting the changing and development. The Hotan and Bayin prefectures in Xinjiang, Chongqing, Guang'an and Meishan in Sichuan, and Sanmenxia in Henan presented a pattern of seasonal rise in the Medium and Mid-High seasons and a pattern of seasonal fall in the High season, reflecting the seasonality of labor export to the Qinghai-Tibet Plateau. In addition, population flow in cities like Turpan, Dongguan and Yuncheng showed a declining trend in the stage of High season as a result of the goods and materials supply relations.

Scientifically assessing the interaction between urbanization and eco-environment in the Tibetan Plateau is critical for optimization of urbanization speed and quality, and for the restoration and improvement of the eco-environment. Based on previous studies about the interaction between urbanization and eco-environment in the Tibetan Plateau, we established complete analysis models to examine the overall process, including comprehensive evaluation index analysis, coupling coordination degree measurement, coupling type identification, decoupling path exploration, and future trend prediction. We used a multi-scale comparison analysis method to clarify the differences between scales (across the Tibetan Plateau and its provinces and prefecture-level cities), identify the problem regions, and propose customized improvement measures. Here we show that the comprehensive evaluation index of urbanization has experienced a staged upward trend in different scales, and the overall urbanization index of Qinghai is higher than that of Tibet. However, the changing trends of the eco-environment index are different. The changes in eco-environment index of Qinghai show a decreasing trend, whereas Tibet's changes tend to be stable. The eco-environment index of prefecture-level cities is stratified. We also found that the changing trends of coupling coordination degree of urbanization and eco-environment in different scales were overall rising. The coupling type has changed from imbalanced recession type to nearly imbalanced recession type, and finally to grudgingly coordinated development type. However, most of these types are lagged urbanization types. The alternate change trend between strong decoupling and weak decoupling indicates a negative interaction between urbanization and the eco-environment at different scales. Thus, it can be inferred that the lagged urbanization is a prominent phenomenon. The result of predication shows that in the next 10 years the coupling coordination degree of urbanization and eco-environment will increase steadily in all geographic units, but there will be a gap in the growth rate.

The activities of local people and tourists have great effects on the ecological environment on the Qinghai-Tibet Plateau. Different kinds of activities may cause different impacts on ecology and environment. To effectively protect the ecological environment, it is necessary to study the spatiotemporal patterns of different kinds of human activities. In this paper, two Tencent positioning datasets which record one-week location requests in January and July of 2018, respectively, are used to explore the human activities in off-season and peak season of tourism on the plateau. A Tucker tensor decomposition method is employed to reduce the dimension of massive data and obtain the principle modes of human activities. The data in off-season are decomposed into 3 daily patterns, 3 hourly patterns and 8 spatial patterns, and the data in peak season are decomposed into 2 daily patterns, 4 hourly patterns and 8 spatial patterns. By analyzing the core tensor, different kinds of activities are inferred through the relations among different dimensions of data, and the human activities in off-season and peak season of tourism are analyzed. The human activities on the Qinghai-Tibet Plateau are found to be different from those in other places. Different from ordinary weekday and weekend patterns, there is a mid-week pattern (Tuesday through Friday) and an inter-week pattern (Saturday, Sunday and Monday) on the Qinghai-Tibet Plateau, and there is a special holiday pattern in off-season of tourism. It is also found that the human activities in off-season and peak season of tourism are different, which indicates different activities of the local residents and the tourists. In off-season of tourism, the positioning activities are very active in the morning, however, the activities are less active during the daytime of mid-week days than during the daytime of inter-week days, and the activities are mostly found in the cities in the mid-week days but mostly in the outskirts of the cities or on the way to scenic spots in the inter-week days. In off-season, there exist the activities of local residents. In peak season, there are less activities in the morning, but the activities during the day are more broadly distributed both in the mid-week days and in the inter-week days. It is indicated that the activities of tourists are significant in the peak season. After clustering spatial grids with similar patterns, we find that there are mixed spatial patterns in most parts of the study area, which discloses that there are usually multiple kinds of human activities in a region.