中国大陆及邻区地震活动背景、环境触发与地震预测研究

This dissertation that includes most of the P. PH.D research work during 2001~2002 covers the large-scale distribution of continental earthquakes in mainland China, the mechanism and statistic features of grouped strong earthquakes related to the tidal triggering, some results in earthquake prediction with correlativity analysis methods, and the flushes from the two strong continental earthquakes in South Asia in 2001. Mainland China is the only continental sub-plate that is compressed by collision boundaries at its two sides, within which earthquakes are dispersive and distributed as seismic belts with different widths. The control capability of the continental block boundaries on the strong earthquakes and seismic hazards is calculated and analyzed in this dissertation. By mapping the distribution of the 31282 ML:3s2,0 earthquakes, I found that the depth of continental earthquakes depend on the tectonic zonings. The events on the boundaries of relatively integrated blocks are deep and those on the new-developed ruptures are shallow. The average depth of earthquakes in the West of China is about 5km deeper than that in the east. The western and southwestern brim of Tarim Basin generated the deepest earthquakes in mainland China. The statistic results from correlation between the grouped M7 earthquakes and the tidal stress show that the strong events were modulated by tidal stress in active periods. Taking Taiwan area as an example, the dependence of moderate events on the moon phase angles (￡>) is analyzed, which shows that the number of the earthquakes in Taiwan when D is 50° ,50° +90° and 50° +180° is more than 2 times of standard deviation over the average frequency at each degree, corresponding to the 4th, 12th and 19th solar day after the new moon. The probability of earthquake attack to the densely populated Taiwan island on the 4th solar day is about 4 times of that on other solar days. On the practice of earthquake prediction, I calculated and analyzed the temporal correlation of the earthquakes in Xinjinag area, Qinghai-Tibet area, west Yunnan area, North China area and those in their adjacent areas, and predicted at the end of 2000 that it would be a special time interval from 2001 to 2003, within which moderate to strong earthquakes would be more active in the west of China. What happened in 2001 partly validated the prediction. Within 10 months, there were 2 great continental earthquakes in south Asia, i.e., the M7.8 event in India on Jan 26 and M8.1 event in China on Nov. 14, 2001, which are the largest earthquake in the past 50 years both for India and China. No records for two great earthquakes in Asia within so short time interval. We should speculate the following aspects from the two incidences: The influence of the fallacious deployment of seismic stations on the fine location and focal mechanism determination of strong earthquakes must be affronted. It is very important to introduce comparative seismology research to seismic hazard analysis and earthquake prediction research. The improvement or changes in real-time prediction of strong earthquakes with precursors is urged. Methods need to be refreshed to protect environment and historical relics in earthquake-prone areas.

大城市内部商业环境满意度评价与消费区位决策研究-以北京市西城区和海淀区为例

Since 1990s, commercial conditions in China including commercial environment, retail types, scale of retail enterprises, spatial structure of retail and shopping decision making factors have changed. In order to keep up with these changes, commercial geography should set up new perspectives, theories and methods to analyze its internal mechanism and changing rules, and thus provide reasonable and practical scientific basis to commercial planning, location decision of retail enterprises and commercial environment construction. Taking Xicheng and Haidian District of Beijing as research case, which is a sector region from city center to rural region, this paper selects 12 commercial centers as most important study objects of this sector. This paper mainly makes use of the methods of Modeling, Pearson Bivaiiate Correlations Analysis, Factor Analysis and Logit model. Based on 1300 questionnaires and fieldwork, this paper focuses on modeling of Consumer Satisfaction of Commercial Environment (CSCE), evaluation of commercial environment and driving factors of consumers' shopping location decision. Firstly, this paper discusses the development of commercial geography and commercial environment evaluation, the new characteristics and trends of commercial development in Beijing and physical commercial environment of Xicheng and Haidian District of Beijing from chapter 1 to chapter 4. Secondly, this paper summarizes characteristics of residents' shopping behavior in chapter 5. Thirdly, this paper sets up an evaluative model of CSCE, and analyzes consumer satisfaction indexes of commercial environment and their spatial features in chapter 6. Fourthly, this paper infers how residents' attributes and shopping behaviors affect their preferences of shopping location and what are residents' shopping location decisions and their influencing factors in chapter 7. Fifthly, this paper constructs a significant index model and a pyramidal framework of CSCE, and further analyzes the diversity and competitive advantage of commercial environment in chapter 8. Finally, some conclusions are drawn as follows: 1. Characteristics of residents' shopping behavior mostly embody residents' time distance preference, commodity consumption preference, shopping time distribution and shopping activity characteristics. The important factors that influence shopping location choice of residents are distance, transportation, commodity price, commodity types and commodity quality. However, the important factors, which influence shopping location re-choice of residents, are commodity price, commodity quality, commodity types and transportation. 2. CSCE indexes of 12 commercial centers show us significant spatial characteristics, such as spatial differences of "Center-fringe region", spatial characteristics of axes, spatial diversity of ring roads and so on. 3. Influencing factors including factor endowments, relative establishment factor and location and transportation factor of commercial environment are of importance for CSCE. 4. Logit model 1 indicates that shopping behavior of residents is significantly and positively related to working in high-tech companies, high income and by car and positively related to high school diploma, by bus and subway. 5. Logit model 2 indicates that residents' shopping location decision is significantly and positively related to leisure establishment and relative restaurant and entertainment establishment and negatively related to commercial location, commodity price, service quality, parking site. 6. The significant index model and the pyramidal framework of CSCE indicate competitive advantages are crucial to attractive capability of commercial center, and competitive weakness limits development of commercial centers, in particular the weakness of service quality and parking site now is the chief factors restricting development of commercial centers