国家社会经济统计地理信息系统的设计与实现

介绍了国家社会经济统计地理信息系统的设计与实现思路，提出了以空间数据为集线器统一集成社会经济统计数据的方法，并探讨了国家社会经济统计地理信息系统对GIS技术应用和统计信息产业化的影响。     

文昌市雷暴气候统计特征

通过对文昌46年来的雷暴资料进行整理统计分析,总结出文昌市雷暴出现的基本气候特征,雷暴日的年际变化和月份更变分布的规律及温度和地形特征。对雷电灾害防御有一定的指导意义。     

棒对星系核区恒星形成活动的影响

利用SDSS光谱,研究了IRAS卫星亮红外源星表中的盘状星系中的恒星形成性质,并着重探讨了棒对星系核区恒星形成活动的影响.利用星族合成的方法得到了每个样本星系核区的恒星组成性质、恒星形成活动的强度等信息,并比较了星系整体和核区恒星形成性质的差异.得到的结论:除去相互作用,样本中的棒星系显示出比非棒旋星系更强的核区恒星形成活动和更多的年轻星族成分.     

近年来中国统计气象学的新进展

近年来，统计气象学在中国取得了长足的进展。其中主要有：将熵原理用于气象学，从而建立了熵气象学；引进了忆及过去时次资料的记忆函数，导出了大气运动的自忆性方程；将模糊数学引入气象学；将非线性动力学用于气候学研究，提出了一系列相空间预报模式；将车贝雪夫多项式推广到不规则格点，提出了一种新的时间序列预报的迭代算法；应用子波分析方法进行气候学研究；将Ｌｏｇｉｓｔｉｃ判别分析用于气象预报，研究了二次判别及逐步判别等问题；将中国科学家提出的灰色系统理论和多层递阶方法引入气象预报。此外，还引进了复经验正交分解、奇异值分解、投影追踪、主振荡模态分析等较新的统计学方法。这些方法都已在气象业务预报中发挥了作用     

Using GIS and statistics to study influences of geology on probability features of surface soil geochemistry in Northern Ireland

The probability features of non-normality and non-lognormality are widely observed in geochemistry due to the influences of multiple factors that are difficult to quantify and model. In Northern Ireland, the pseudo-total concentrations of 14 elements (Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, P, Pb and Zn) from 6138 topsoils were measured, and GIS mapping showed that the spatial distribution of these data were in line with the spatial distribution of geology in the area. Investigations into the influences of geology on the concentration data and their probability features were carried out using GIS and statistics in this study. The whole raw data sets for each element were positively skewed and none of them followed either normal or lognormal distributions. Logarithmic transformation was found to have “over-transformed” most of the data sets, changing their skewness from positive to negative values. When soil samples were classified by rock type using a GIS overlay function, obvious differences were observed in the chemical concentrations of soils derived from different rock types. Soils in basalt areas displayed the highest concentrations for most elements under study (Ca, Co, Cr, Cu, Fe, Mg, Mn, Na, Ni, P and Zn) but the lowest concentrations for K, while the highest levels for Cd and Pb occurred in the shale areas. Classifying soils by rock type produced more normally distributed data sets, especially for the igneous rock areas. To restrain the influence of soil type and land cover, samples from both gleys and pastures were extracted via a GIS and it was found the data sets then showed generally greater tendencies towards normality. However, many of the data sets would still not pass a test for normality unless the sample size was small (e.g. of the order of a couple of hundreds). Geology, soil type, land cover and sample size all played important roles in determining soil chemical concentrations and their probability features. However, the influences from other factors were still evident. Attempts made in this study show that it remains a challenging task in geochemistry to separate all the factors and to model their influence at the regional scale.     

STATISTICAL CHARACTERISTICS ON TROPICAL CYCLONES LANDFALL IN CHINA

With the data from the Tropical Cyclone Yearbooks between 1970 and 2001, statistical analyses were performed to study the climatic features of landfall TCs (noted as TCs hereafter) in China with particular attention focused on landfall frequency, locations, sustaining, decaying, transition, intensification and dissipation etc. The results indicate that the sustaining periods of TC over land are quite different for different landfall spots, and increased from Guangxi to Zhejiang. The most obvious decreasing of TC intensity occurs mainly within 12 hours after landfall. The stronger a TC is，the more it decays. The areas over which TCs are dissipated can be in Heilongjiang, the northernmost, and Yunnan, the westernmost. Besides, Guangxi is an area with high dissipating rate and subject to TC dissipation as compared with the other coastal regions.     

Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA

Landslides in the hilly terrain along the Kansas and Missouri rivers in northeastern Kansas have caused millions of dollars in property damage during the last decade. To address this problem, a statistical method called multiple logistic regression has been used to create a landslide-hazard map for Atchison, Kansas, and surrounding areas. Data included digitized geology, slopes, and landslides, manipulated using ArcView GIS. Logistic regression relates predictor variables to the occurrence or nonoccurrence of landslides within geographic cells and uses the relationship to produce a map showing the probability of future landslides, given local slopes and geologic units. Results indicated that slope is the most important variable for estimating landslide hazard in the study area. Geologic units consisting mostly of shale, siltstone, and sandstone were most susceptible to landslides. Soil type and aspect ratio were considered but excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression. Soil types were highly correlated with the geologic units, and no significant relationships existed between landslides and slope aspect.     

L1-norm pre-analysis measures for geodetic networks

 Several pre-analysis measures which help to expose the behavior of L ₁ -norm minimization solutions are described. The pre-analysis measures are primarily based on familiar elements of the linear programming solution to L ₁-norm minimization, such as slack variables and the reduced-cost vector. By examining certain elements of the linear programming solution in a probabilistic light, it is possible to derive the cumulative distribution function (CDF) associated with univariate L ₁-norm residuals. Unlike traditional least squares (LS) residual CDFs, it is found that L ₁-norm residual CDFs fail to follow the normal distribution in general, and instead are characterized by both discrete and continuous (i.e. piecewise) segments. It is also found that an L ₁ equivalent to LS redundancy numbers exists and that these L ₁ equivalents are a byproduct of the univariate L ₁ univariate residual CDF. Probing deeper into the linear programming solution, it is found that certain combinations of observations which are capable of tolerating large-magnitude gross errors can be predicted by comprehensively tabulating the signs of slack variables associated with the L ₁ residuals. The developed techniques are illustrated on a two-dimensional trilateration network. Received: 6 July 2001 / Accepted: 21 February 2002     

地下水化学背景值研究中的异常值判定与处理

根据吉林省地下水化学背景值调查背景值确定出现的水化学异常问题,应用数理统计原理,并结合水文地球化学特征,讨论了判定和处理异常值方法的科学性与适用性。