Clustering Analysis of the Climate in Tobacco Planting Zone of Yunnan

[Objective] The research aimed to study clustering of the six climatic factors in Yunnan tobacco planting zone. [Method] 6 meteorological elements in 89 tobacco-growing counties and 12 sub-prefectures were conducted clustering analysis. According to indicator and climate characteristics of the each type, climate in tobacco planting area of Yunnan Province was divided. [Result] Climate in tobacco planting area of Yunnan Province could be divided into eight types: Jiangchuan (24 counties, belonged to northern and central subtropical climate belts), Songming (27 counties, belonged to northern subtropical and central, south, north temperate climate belts), Tengchong (3 counties, belonged to northern subtropical climate belt), Mile (12 counties, belonged to central and southern subtropical climate belts), Qiubei (11 counties, belonged to southern subtropical climate belt), Yanjin (4 counties, belonged to central subtropical humid climate belt), Yuanjiang (4 counties, belonged to southern subtropical and northern tropical climate belts), Zhenxiong (3 counties, belonged to warm temperate and northern subtropical climate belts) were eight representatives. Among 1-8 eco-zones, domestic and foreign cities where climate reached level-one similarity were respectively 3, 1, 1, 0, 1, 1, 0 and 1, up to level-two similarity, respectively 12, 15, 3, 13, 13, 1, 5 and 3. Among 8 major ecological zones, similar distance of the city reaching level-one similarity was in the range of 0.28 to 0.45, and similar degree was the highest. Variety introduction among these places would be successful. Similar distance of the city reaching level-two similarity was between 0.51 and 1.00, and similar degree was higher. Mutual variety introduction had high successful rate in these places. [Conclusion] The research provided theoretical basis for selecting new suitable tobacco variety and optimizing tobacco variety layout in different zones.

Digital regionalization of geomorphology in Xinjiang

This paper presents a method of geomorphologic regionalization for Xinjiang, with the use of Srtm-DEM (resolution 90 m) and TM images for 1990 (resolution 30 m). After interpretation and classification of geomorphologic types, the present research focuses on the qualitative and quantitative distribution of different geomorphologic types based on geographical grid analysis. Then, by using system clustering analysis method, geomorphologic types are grouped into divisions. The resulting geomorphologic regionalization hierarchy of Xinjiang includes three levels, i.e., macro-landform divisions, medium-landform divisions, and micro-landform divisions, containing 6, 23 and 200 types, respectively. This method makes it possible to digitally delimit geomorphologic regions. Comparison and verification show that the spatial precision of the boundaries of geomorphologic subareas in Xinjiang is very high.

Variation Characteristics of Focal Mechanisms of Small Earthquakes before Four Strong Earthquakes in Xinjiang

With the point source dislocation model and the velocity structure of a layered medium,focal mechanisms of small earthquakes are calculated using the maximum amplitude of the direct P- and S-waves in the vertical component. By system clustering,and using the vector synthesis method,the average focal mechanism solution is obtained. Using the above method,this paper analyzes the variation characteristics of the source ruptures and the P-axis azimuths of small earthquakes around the seismic zones before four strong earthquakes occurring since 2003 in the western part of north Tianshan and the middle part of Tianshan. The result shows that 2 ~ 3 years before the strong earthquakes,the focal mechanism types of small earthquakes are distributed randomly, and obvious dominant distributions are observed one year before the strong earthquakes. There are obvious changes in the P-axis azimuth.

The Establishment of Mathematical Models for the Composition Analysis and Identification of Ancient Glass Products

Glass is the precious material evidence of the trade of the early Silk Road. The ancient glass was easily affected by the environmental impact and weathering, and the change of composition ratios affected the correct judgment of its category. In this paper, mathematical models and methods such as Chi-square test, weighted average method, principal component analysis, cluster analysis, binary classification model and grey correlation analysis were used comprehensively to analyze the data of sample glass products combined with their categories. The results showed that the weathered high-potassium glass could be divided into 12, 9, 10 and 27, 7, 22 and so on.