半参数p-范极大似然回归

应用核权函数,在观测为误差单峰、对称的情况下,得到了一元p-范分布的半参数模型的计算公式.详细推导了p已知时一元p-范分布极大似然方程的解算公式,将半参数回归模型应用到极大似然平差的参数估计理论中,得到了一个比较好的算法.最后,构造了两个模拟平差问题,说明了此方法的优越性.     

2013 年3 月27 日台湾南投MW 6. 0 地震震源机制解与发震构造研究

采用基于近远震波形的CAPjoint 方法,对2013 年3 月27 日台湾南投MW6. 0 地震分别进行了单独反演和联合反演,获得了各自的震源机制解及震源深度。其中,联合反演所得的最优双力偶机制解参数为,节面Ⅰ:方位角0°,倾角30°,滑动角78°;节面Ⅱ:方位角193°,倾角60°,滑动角96°;震源深度18km。为了验证联合反演的有效性和可靠性,采用由重抽样理论发展而来的Bootstrap 方法,对近远震数据分别进行了重采样,并对其单独反演和联合反演所得的参数进行了统计,验证了联合反演的有效性及稳定性,并发现远震反演震源深度的结果一定程度上受台站分布的影响,若要获得精确的震源深度则需要方位角分布较好的远震台站记录。根据前人对集集地震及车笼埔断层的研究成果以及南投地震的发震断层性质接近车笼埔断层的认识,推测此次地震可能发生在车笼埔断层上。     

A Gridded Daily Min/Max Temperature Dataset With 0.1° Resolution for the Yangtze River Valley and its Error Estimation

The minimum/maximum (Min/Max) temperature in the Yangtze River valley is decomposed into the climatic mean and anomaly component. A spatial interpolation is developed which combines the 3D thin-plate spline scheme for climatological mean and the 2D Barnes scheme for the anomaly component to create a daily Min/Max temperature dataset. The climatic mean field is obtained by the 3D thin-plate spline scheme because the relationship between the decreases in Min/Max temperature with elevation is robust and reliable on a long time-scale. The characteristics of the anomaly field tend to be related to elevation variation weakly, and the anomaly component is adequately analyzed by the 2D Barnes procedure, which is computationally efficient and readily tunable. With this hybridized interpolation method, a daily Min/Max temperature dataset that covers the domain from 99°E to 123°E and from 24°N to 36°N with 0.1° longitudinal and latitudinal resolution is obtained by utilizing daily Min/Max temperature data from three kinds of station observations, which are national reference climatological stations, the basic meteorological observing stations and the ordinary meteorological observing stations in 15 provinces and municipalities in the Yangtze River valley from 1971 to 2005. The error estimation of the gridded dataset is assessed by examining cross-validation statistics. The results show that the statistics of daily Min/Max temperature interpolation not only have high correlation coefficient (0.99) and interpolation efficiency (0.98), but also the mean bias error is 0.00 °C. For the maximum temperature, the root mean square error is 1.1 °C and the mean absolute error is 0.85 °C. For the minimum temperature, the root mean square error is 0.89 °C and the mean absolute error is 0.67 °C. Thus, the new dataset provides the distribution of Min/Max temperature over the Yangtze River valley with realistic, successive gridded data with 0.1° × 0.1° spatial resolution and daily temporal scale. The primary factors influencing the dataset precision are elevation and terrain complexity. In general, the gridded dataset has a relatively high precision in plains and flatlands and a relatively low precision in mountainous areas.     

Flood season segmentation based on the probability change-point analysis technique

Abstract

The segmentation of flood seasons has both theoretical and practical importance in hydrological sciences and water resources management. The probability change-point analysis technique is applied to segmenting a defined flood season into a number of sub-seasons. Two alternative sampling methods, annual maximum and peaks-over-threshold, are used to construct the new flow series. The series is assumed to follow the binomial distribution and is analysed with the probability change-point analysis technique. A Monte Carlo experiment is designed to evaluate the performance of proposed flood season segmentation models. It is shown that the change-point based models for flood season segmentation can rationally partition a flood season into appropriate sub-seasons. China's new Three Gorges Reservoir, located on the upper Yangtze River, was selected as a case study since a hydrological station with observed flow data from 1882 to 2003 is located 40 km downstream of the dam. The flood season of the reservoir can be reasonably divided into three sub-seasons: the pre-flood season (1 June–2 July); the main flood season (3 July–10 September); and the post-flood season (11–30 September). The results of flood season segmentation and the characteristics of flood events are reasonable for this region.

Citation Liu, P., Guo, S., Xiong, L. & Chen, L. (2010) Flood season segmentation based on the probability change-point analysis technique. Hydrol. Sci. J. 55(4), 540–554.     

径向基函数算法中插值参数对DEM精度的影响

以多重对数径向基函数插值算法中的插值参数为研究对象,选取了5种不同地貌类型的离散点数据,使用中误差度量指标,研究光滑因子、搜索点数、搜索方向对DEM插值精度的影响,给出插值参数的"最优"取值区间,消除插值参数选择的随意性,更好地指导DEM建模的运用。     

青藏高原东北部岩石圈有效弹性厚度及其各向异性

青藏高原东北部是中国大陆构造环境特殊的主要构造域,毗邻青藏高原羌塘地块、塔里木盆地、四川盆地和华北克拉通,属于不同构造类型块体俯冲、碰撞及陆内汇聚的结合部,在中国大陆形成与演化的历史中扮演着重要角色.岩石圈有效弹性厚度(T_e)及其各向异性与岩石圈流变性、力学结构紧密相连,研究青藏高原东北部的岩石圈T_e及其各向异性将为我们认识大陆岩石圈的流变性及动力学过程提供重要信息.本文基于Fan小波相关性分析法,运用布格重力和地形资料获得了青藏高原东北部岩石圈T_e及其各向异性二维分布的详细信息.研究结果表明研究区域内T_e的分布范围在5～100 km之间;松潘-甘孜地块、祁连山造山带和龙门山地区的T_e较薄(5 kme<40 km)、各向异性较强;而周缘的断裂带、缝合带的T_e值都较低,其中龙门山断裂带T_e只有5～20 km,且南、北两段各向异性存在明显差异.内部的若尔盖盆地T_e值略显高值,说明其是仍保留有刚性的块体;北缘的柴达木盆地下伏为古生代的地壳,被认为是古老的克拉通碎片,T_e较大(50 kme<90 km),显示为轮廓分明的刚性块体.并且我们发现研究区域内T_e的各向异性轴垂直于大的块体边界.通过比较T_e各向异性与SKS波的快波偏振方向、Rayleigh面波方位角各向异性的相互关系我们推测阿拉善地块各向异性源自地幔橄榄岩晶格的优势取向,岩石圈变形趋于垂直连贯变形模式;柴达木盆地各向异性源于历史构造事件残留在岩石圈中的"化石"各向异性;松潘-甘孜地块各向异性源自物质的侧向流动.     

利用ArcGIS Engine建立暴雨水调蓄模型的三维分析系统

首先基于ArcGIS Engine建立小区水容积-水位关系;进而对暴雨过程线公式进行推导,并建立暴雨水调蓄模型;最后利用暴雨水调蓄模型建立径流流量、排水流量随时间变化关系图,并基于ArcGIS Engine实现暴雨水调蓄模型的三维分析系统.     

The integrated spatial databases of GeoStar

GeoStar is the registered trademark of GIS software made by WTUSM in China. By means of the GeoStar, multi-scale images, DEMs, graphics and attributes integrated in very large seamless databases can be created, and the multi-dimensional dynamic visualization and information extraction are also available. This paper describes the fundamental characteristics of such huge integrated databases, for instance, the data models, database structures and the spatial index strategies. At last, the typical applications of GeoStar for a few pilot projects like the Shanghai CyberCity and the Guangdong provincial spatial data infrastructure (SDI) are illustrated and several concluding remarks are stressed.     

Verification of net primary production estimation method in the Mongolian Plateau using landsat ETM+data

We plan to estimate global net primary production (NPP) of vegetation using the Advanced Earth Observing Satellite-II (ADEOS-II) Global Imager (GLI) multi-spectral data. We derive an NPP estimation algorithm from ground measurement data on temperate plants in Japan. By the algorithm, we estimate NPP using a vegetation index based on pattern decomposition (VIPD) for the Mongolian Plateau. The VIPD is derived from Landsat ETM+multi-spectral data, and the resulting NPP estimation is compared with ground data measured in a semi-arid area of Mongolia. The NPP estimation derived from satellite remote sensing data agrees with the ground measurement data within the error range of 15% when all above-ground vegetation NPP is calculated for different vegetation classifications.     

一元非对称P范分布的极大似然平差

从测量误差的实际情况出发,提出一元非对称P范分布极大似然平差方法,建立该方法的数学模型,得到一元非对称P范分布的密度函数,利用极大似然估计方法推导参数估计值的基础方程.研究表明,结合实际测量数据,通过选择合适的参数估计值,可以增加误差分布模型选取的灵活性,便于P范分布理论在测绘数据处理中的推广应用.