The NDVI in northern china is vulnerable and is greatly affected by meteorological factors. In this study, the correlation between changes of NDVI and the major meteorological factors (temperature, precipitation) in northern China in the past 30 years with Trend analysis and partial correlation analysis methods. The results show that: (1) In the recent 30 years, the annual average NDVI in northern China shows an upward trend of volatility, with an annual growth rate of 0.0015, and the overall vegetation coverage increases. (2) In the context of global warming, the average annual temperature in the research area increased significantly, with an average annual growth rate of 0.0353, while the average annual growth rate of precipitation was not significant, with an average annual growth rate of 0.1591. (3) NDVI has a higher correlation with air temperature in high altitude alpine and plateau areas, and a higher correlation with precipitation in grassland and desert grassland areas.
Abstract:Steppe is an indispensable component for terrestrial ecosystems and it is of great significance to systematically analyze steppe sustainability and its driving forces. In this study, we propose a steppe dynamics ranking method based on Pauta criterion and a steppe sustainability assessment method with an effect matrix. The natural driving forces on steppe sustainability were systematically analyzed using the copula model, and the anthropogenic driving factors, including land use, were analyzed by using spatial overlay and statistical analysis methods. The results showed the following: (1) in general, steppe sustainability showed a trend of improvement from 2001 to 2010 in China. However, there were still some degraded areas scattered within the study area; (2) the consistent effect of steppe dynamics on steppe sustainability was significant on the whole, although there was a diverse effect on it; (3) among the natural factors, precipitation was the strongest positive driving force, followed by temperature average, while sunshine duration had strong negative driving force. The impact caused by land use factors was controlled during that decade, and the steppe land that evolved from urban and built-up land, cropland, and forest was vulnerable and resulted in steppe sustainability degradation.
Water inrush in mine is one of the most common hazards in the mining industry. To solve the problem of rescue route planning during a mine water inrush hazard, a dynamic rescue route planning method based on a 3 D network is proposed. First, the basic elements in the 3 D network model of the mine roadway are abstractly described, furthermore, the weights of edges, the topological connectivity of the elements, and the data structure of the network are defined. Then, the Dijkstra algorithm and the Breadth-first search algorithm are combined to implement the best rescue search route and return route planning based on the 3 D network model. Finally, the dynamic rescue route planning is simulated in 3 D virtual spatial scenario of a real mine. The factors such as topological connectivity of the elements, real-time water level, and slope of the mine roadways are considered in the process of rescue route planning, as the rescue route is adjusted dynamically according to the actual situations. This method proposed can provide powerful decision support for mine water inrush hazard rescue.
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