Application of Robust Estimation Method in Study of Relationship Between Lake’s Water Area and Water Level

Better understanding of the relationship between lake’s water area and water level plays an important role for the monitoring of floods and droughts. At present, there are many analysis and research on the relationship between water area and level, but the estimation criteria are mostly based on ordinary least square, which has no ability to resist the gross error. In this paper, the equivalent weight estimation method with robustness ability is introduced. We use the proposed method in study of the Poyang Lake which is the largest freshwater lake in China. The area extraction data and water level records spans the period from 2009 to 2013. Four models (linear, exponential, logarithmic and quadratic polynomial) of water area and water level are constructed by regression analysis. Meanwhile, two kinds of common weight function factors are applied to analyze the quadratic curve model. The experimental results show that the quadratic polynomial fitting performs best, and the solution of the equivalent weight function method is closer to the realism than least square. We note that the proposed robust estimation method can dynamically monitor the water area and water level, which provides a theoretical basis for similar research.     

面向对象的测量平差软件设计与网络化应用

对测量平差软件用面向对象的方法进行了重新设计,并用纯面向对象的Java语言实现了其抽象类和继承类,各种平差方法都以对象的形式出现,为程序代码的共享和多用户并发运行时字节码的共享打下了基础。     

一种改进的Goldstein InSAR干涉图滤波算法

提出了一种抑制InSAR干涉图噪声并保持干涉图条纹细节的算法,该算法改进了Goldstein滤波的参数α,将干涉图的相位标准偏差函数模型作为参数。相位标准偏差是相位噪声的体现,以干涉图的相位噪声强弱来决定滤波的强弱,噪声强的局部区域强滤波,噪声弱的局部区域弱滤波。实验结果表明,此方法改善了滤波效果,增强了滤波的局部自适应性和条纹细节的保真性。     

Geographically weighted regression‐based determinants of malaria incidences in northern China

Geographically weighted regression (GWR) is an important local method to explore spatial non‐stationarity in data relationships. It has been repeatedly used to examine spatially varying relationships between epidemic diseases and predictors. Malaria, a serious parasitic disease around the world, shows spatial clustering in areas at risk. In this article, we used GWR to explore the local determinants of malaria incidences over a 7‐year period in northern China, a typical mid‐latitude, high‐risk malaria area. Normalized difference vegetation index (NDVI), land surface temperature (LST), temperature difference, elevation, water density index (WDI) and gross domestic product (GDP) were selected as predictors. Results showed that both positively and negatively local effects on malaria incidences appeared for all predictors except for WDI and GDP. The GWR model calibrations successfully depicted spatial variations in the effect sizes and levels of parameters, and also showed substantially improvements in terms of goodness of fits in contrast to the corresponding non‐spatial ordinary least squares (OLS) model fits. For example, the diagnostic information of the OLS fit for the 7‐year average case is R² = 0.243 and AICc = 837.99, while significant improvement has been made by the GWR calibration with R² = 0.800 and AICc = 618.54.     

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和极大似然估计及其性质

将小误差和粗差看成同一正态分布时 ,最小二乘估计不抗差 ,而其和极大似然估计是抗差的 ,其统计性质受尺度因子 (方差因子 ) k影响。k =1 .41 6时 ,有最小最大偏差 ,即最强的抗差能力 ,效率为 83.85 ;k=2 .73时 ,其最大偏差不超过无粗差时 (以 2倍中误差为阈值 )最小二乘估计的最大偏差 ,具有很好的抗差性 ,效率为 97.91 ,是最合适的取值 ;k =∞时 ,与最小二乘估计等价     

不等式约束M估计的均方误差矩阵和解的改善条件

缺少精确先验时,不等式约束可改善参数估计。针对不等式约束M估计,利用巴哈杜尔线性化原理和凝聚函数方法导出参数估计、残差向量以及观测量平差量线性表达式,进一步导出相应的方差协方差矩阵和均方误差矩阵。线性表达式说明不等式约束M估计通常情况下是有偏的;均方误差矩阵公式表明不等式约束M估计解有可能改善,条件是最大不等式绝对值小于所导出的阈值,阈值由M估计的第一、第二多余参数和与不等式约束有关的多余参数确定。针对正态分布和p范分布确定了Lp估计改善解的具体条件。所导出的公式和结论可用于统计分析和不等式设计。     

基于对数-主成分变换的EM算法用于遥感影像分类

提出对多光谱数据进行对数变换来凸显类型特征,然后进行主成分变换并根据主成分贡献率确定EM算法分类所需主成分数,消除方差协方差矩阵的奇异性,同时削弱噪声;对数变换后的第一主成分直方图充分反映类型信息,由此确定的初始类别标签作为多个主成分EM分类算法所需初始值,避开随机选初值的敏感问题.实验证明,所提出的计算方案分类精度优于普通EM方法和传统的K-means方法.     

A method for GB-InSAR temporal analysis considering the atmospheric correlation in time series

Natural Hazards - GB-InSAR, with high time-spatial resolution and high accuracy, shows great potential in landslide monitoring. However, the accuracy of GB-InSAR is usually reduced by the...     

随机游动模型下系统误差补偿算法研究

采用地球同步静止卫星的观测数据,通过批处理方法及EM算法分别加以处理。利用偏度、峰度正态性检验方法对批处理方法所得的残差进行正态性检验,鑫诺卫星观测数据中不仅含有偶然误差,还存在系统误差等,批处理方法在处理含有系统误差的观测数据时所得的结果不可靠。相对于批处理方法,利用随机游动模型描述系统误差,基于数字滤波方法的EM算法在处理含有系统误差数据时具有可行性,在一定程度上达到了提高数据处理精度的目的。