正交距离圆曲线拟合方法

在分析圆曲线拟合准则基础上,提出采用正交最小二乘法拟合圆曲线。该方法以圆曲线正交距离残差平方和极小为准则。基于间接平差原理详细推导了相关模型和算法,并以实际算例说明了该方法的效果。     

基于高光谱Hyperion数据的线性光谱混合模型与神经网络模型的比较

混合像元问题是定量遥感中的热点问题之一,为了改进从遥感数据中提取定量信息,人们建立了各种混合光谱分解技术,其中线性光谱混合模型和神经网络模型就是两种比较成熟的方法。以陕西省横山地区的高光谱Hyperion数据为研究基础,通过最小噪声变换(MNF)、像元纯度指数(PPI)转换和RMS误差分析的迭代方法相结合提取影像中的纯净像元作为终端端元。分别运用神经网络模型和线性光谱混合模型对影像进行光谱分解,得到各个组分的分解图像。以标准植被指数(NDVI)影像为衡量标准,选取训练样本点,分别对两种模型进行回归分析,结果显示NDVI影像与线性光谱混合模型植被分解图像的判定系数(R2=0.91)要大于其与神经网络模型的判定系数(R2=0.81)。进一步分析表明在一般情况下,线性光谱混合模型具有比神经网络模型略高的分离精度,但是神经网络模型对细部信息的提取的效果要好于线性光谱混合模型,最后提出了端元均方根误差(EAR)指数,一种新的混合像元分解的思路。     

On the multivariate total least-squares approach to empirical coordinate transformations. Three algorithms

The multivariate total least-squares (MTLS) approach aims at estimating a matrix of parameters, Ξ, from a linear model (Y−E _Y = (X−E _X ) · Ξ) that includes an observation matrix, Y, another observation matrix, X, and matrices of randomly distributed errors, E _Y and E _X . Two special cases of the MTLS approach include the standard multivariate least-squares approach where only the observation matrix, Y, is perturbed by random errors and, on the other hand, the data least-squares approach where only the coefficient matrix X is affected by random errors. In a previous contribution, the authors derived an iterative algorithm to solve the MTLS problem by using the nonlinear Euler–Lagrange conditions. In this contribution, new lemmas are developed to analyze the iterative algorithm, modify it, and compare it with a new ‘closed form’ solution that is based on the singular-value decomposition. For an application, the total least-squares approach is used to estimate the affine transformation parameters that convert cadastral data from the old to the new Israeli datum. Technical aspects of this approach, such as scaling the data and fixing the columns in the coefficient matrix are investigated. This case study illuminates the issue of “symmetry” in the treatment of two sets of coordinates for identical point fields, a topic that had already been emphasized by Teunissen (1989, Festschrift to Torben Krarup, Geodetic Institute Bull no. 58, Copenhagen, Denmark, pp 335–342). The differences between the standard least-squares and the TLS approach are analyzed in terms of the estimated variance component and a first-order approximation of the dispersion matrix of the estimated parameters.     

鲁北平原区井灌回归系数分析

利用井灌回归系数计算回归补给水量,是地下水资源评价计算井灌回归水量的基本方法。井灌回归系数确定的合理与否,直接影响到地下水资源评价成果的合理性。以试验站的观测资料为基础,结合引水灌溉调查成果,对影响井灌回归系数大小的因素和区域分布规律进行了系统分析,依地下水埋深和灌溉方式划分引黄灌区、井河结合灌区、井灌区三种类型,分析确定鲁北平原区适用的井灌回归系数。     

联合多种测高数据确定中国海及其邻域1．5′×1．5′重力异常

联合多种测高资料和Geosat/GM波形重构数据,基于EIGEN_CG01C重力场模型,采用沿轨迹加权最小二乘方法和逆Vening-Meinesz公式,确定了中国海及其邻域1.5′×1.5′重力异常。将计算结果与最新船测资料进行了比较,标准差为3.37×10-5m.s-2。     

成都城市发展对热岛强度影响的主成份回归分析

本文对成都市总人口、建成区面积等11个因子、作了主成份回归L-S估计和M-估计,讨论了成都城市发展对“热岛”强度的主要影响因子。结果表明,城区房屋建筑面积及总人口数是影响城市气候(气温)的主要因子,其次为城市人口总户数、建成面积等。 文中,对回归方程进行了拟合计算,回归效果比较满意(尤其是稳健回归)。     

Comparison of structural and least-squares lines for estimating geologic relations

Two different goals in fitting straight lines to data are to estimate a true linear relation (physical law) and to predict values of the dependent variable with the smallest possible error. Regarding the first goal, a Monte Carlo study indicated that the structural-analysis (SA) method of fitting straight lines to data is superior to the ordinary least-squares (OLS) method for estimating true straight-line relations. Number of data points, slope and intercept of the true relation, and variances of the errors associated with the independent (X) and dependent (Y) variables influence the degree of agreement. For example, differences between the two line-fitting methods decrease as error in X becomes small relative to error in Y. Regarding the second goal—predicting the dependent variable—OLS is better than SA. Again, the difference diminishes as X takes on less error relative to Y. With respect to estimation of slope and intercept and prediction of Y, agreement between Monte Carlo results and large-sample theory was very good for sample sizes of 100, and fair to good for sample sizes of 20. The procedures and error measures are illustrated with two geologic examples.     

Analysis on the sources of mercury in soils in the Chengdu Basin, China

Mercury is a pollutant of concern due to its toxic and bioaccumulative properties. Studies on the distribution and hazard of mercury in the environment are mainly focused on its forms, toxicity and the environment standard, and progresses and results have been achieved. But these studies in the past were concentrated on the scales of laboratory or smaller districts merely, such as a small unit of mineral area, vegetable base, paddy field, lake, etc. Multi-target regional geochemical survey carried out by China Geological Survey from the 1990s to now is a fundamental and commonweal geological survey, large-scale and systematical inquisition and research were conducted in 19 provinces （or municipalities directly under the Central Government） in the eastern overlay region of China, and the purpose is to provide the basic geochemical data for national economic construction, adjustment of industrial and agricultural structures and sustainable social development. Geochemical studies aim at investigating soils in these regions and 52 elements have been tested, producing a great amount of data at the same time. Methods： based on the data from 3061 samples of surface soil and 832 samples of deep soil from the project of multi-purpose geochemical survey in the Chengdu Basin, Sichuan, China, this paper describes the correlation relationship between Hg and other 48 elements and their spatial distribution in surface and deep soils of these areas by applying the method of linear regression and factor analysis.     

Water temperature behaviour in the River Loire since 1976 and 1881

Analysis of monthly mean river temperatures, recorded on an hourly basis in the middle reaches of the Loire since 1976, allows reconstruction by multiple linear regression of the annual, spring and summer water temperatures from equivalent information on air temperatures and river discharge. Since 1881, the average annual and summer temperatures of the Loire have risen by approximately 0.8?°C, this increase accelerating since the late 1980s due to the rise in air temperature and also to lower discharge rates. In addition, the thermal regime in the Orleans to Blois reach is considerably affected by the inflow of groundwater from the Calcaires de Beauce aquifer, as shown by the summer energy balance. To cite this article: F. Moatar, J. Gailhard, C. R. Geoscience 338 (2006).     

Multicollinearity and correlation among local regression coefficients in geographically weighted regression

Present methodological research on geographically weighted regression (GWR) focuses primarily on extensions of the basic GWR model, while ignoring well-established diagnostics tests commonly used in standard global regression analysis. This paper investigates multicollinearity issues surrounding the local GWR coefficients at a single location and the overall correlation between GWR coefficients associated with two different exogenous variables. Results indicate that the local regression coefficients are potentially collinear even if the underlying exogenous variables in the data generating process are uncorrelated. Based on these findings, applied GWR research should practice caution in substantively interpreting the spatial patterns of local GWR coefficients. An empirical disease-mapping example is used to motivate the GWR multicollinearity problem. Controlled experiments are performed to systematically explore coefficient dependency issues in GWR. These experiments specify global models that use eigenvectors from a spatial link matrix as exogenous variables.This study was supported by grant number 1 R1 CA95982-01, Geographic-Based Research in Cancer Control and Epidermiology, from the National Cancer Institute. The author thank the anonymous reviewers and the editor for their helpful comments.