机载多光谱LiDAR的随机森林地物分类

机载多光谱LiDAR技术利用激光进行探测和测距,不仅可以快速获取地面物体的三维坐标,还可以获得多个波段的地物光谱信息,可广泛用于地形测绘、土地覆盖分类、环境建模、森林资源调查等。本文提出了多光谱LiDAR的随机森林地物分类方法。该方法通过对LiDAR强度数据和高程数据提取分类特征,完成多光谱LiDAR的随机森林地物分类;并分析随机森林的特征贡献度特性,采用后向特征选择方法实现分类特征选择。通过对加拿大Optech Titan多光谱LiDAR数据的试验表明：随机森林方法可以获得较好的地物分类精度,而且可以适当地去除部分冗余和相关的特征,从而有效提高分类精度。     

加权EIV模型的经典最小二乘算法

采用GHM方法将EIV模型在最优解处线性化,得到解的近似方差。然后,将EIV模型表达成与Gauss-Markov模型相似的形式,利用标准最小二乘理论推导EIV模型的解及近似方差矩阵,得到与已有算法等价的结论。最后,推导观测值估值和残差的统计性质,建立起一整套EIV模型参数估计和精度评定的体系。     

重力固体潮信号的独立成分分析与谱相关解调

针对提取重力固体潮潮汐谐波分量,分析各谐波分量间调制关系的问题,该文结合重力固体潮的产生机制建立了一种重力固体潮信号正交分解模型。利用独立分量分析算法和谱相关方法,分离出与模型相对应的独立分量信号,并从独立成分中解调出载波分量和被调制分量。从而完整地描述了地球自转产生的潮汐谐波与月球、太阳相对于地球轨道变化产生的潮汐谐波的正交分解关系。实验表明,此方法能有效地提取出重力固体潮信号中所包含的潮汐谐波信息,并揭示出该重力固体潮信号中存在3个线性叠加的独立分量,在月波分量和年波分量都以乘性调制的方式调制到半日波分量和日波分量上。     

利用椭球变换建立独立坐标系的方法

详细阐述了8种利用椭球变换建立独立坐标系的方法,推导了独立坐标系高程面与椭球面之间的相互关系,进而建立了椭球变换模型,减少了高程归化变形;并通过计算实例对其投影变形值进行分析,以探究不同方法间的特点与差异,得出了一些有益的结论。     

多变量分位数回归构建印度洋大眼金枪鱼栖息地指数

以0～300m水层加权平均水温、50～150m水层的温差和氧差及其交互变量为影响因子,运用分位数回归法,寻找出环境变量与大眼金枪鱼(Thunnus obesus)延绳钓钓获率的最佳上界分位数回归方程,计算出栖息地指数(HSI),并应用地理信息系统(GIS)软件绘制各月HSI空间分布图。研究表明:大眼金枪鱼延绳钓钓获率(HR)依加权平均水温(x)、温差(y)、氧差(z)与的最佳上界分位数回归方程为HR0.70=-15.596+2.124x-0.003x3+0.033xyz-0.036y2z+0.107yz2-0.337z3;HSI空间分布为:16°S—10°N印度洋海域HSI高于0.7,HSI>0.8的海域随季节发生显著变化,马达加斯加外海至100°E、16°S—26°S海域常年存在一片HSI<0.4的区域,26°S—40°S海域的HSI介于0.4～0.5,40°S以南海域HSI<0.4,东非外海季节性地出现一片HSI<0.6的海域。利用多个环境变量的栖息地指数模型来预测分析大洋金枪鱼资源分布效果较好。     

最短独立闭合环与附合路线的快速搜索方法

提出了一种间接平差误差方程转化为条件平差条件方程的快速且易实现自动化的方法,同时采用矩阵分析理论,通过对条件方程进行特殊的矩阵分块及变换,自动搜索出水准网或GPS网的最短独立闭合环与附合路线,并自动解算出闭合差。上述方法有别于传统的图论理论,不依赖于任何信息文件,算法简单,自动化程度高。     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models: An Empirical Validation of ISWRidge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p 〈0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to cheek the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height （X1 ） and potential energy （X2 ） significantly impact （p 〈 0. 0001 ） the amplitude-based refleeted rate; the P-values for the deviance and Pearson are all 〉 0.05 （0.2839, 0.3438, respectively）. That is, the goodness-of-fit between ridge height （ X1 ） and potential energy （X2） can further predict parameters under the scenario of the best parsimonious model. Investigation of 6 predictive powers （ R2, Max-rescaled R^2, Sorners＇ D, Gamma, Tau-a, and c, respectively） indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models： An Empirical Validation of ISW-Ridge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p<0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to check the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height (X1) and potential energy (X2) significantly impact (p<0.0001) the amplitude-based reflected rate; the P-values for the deviance and Pearson are all >0.05 (0.2839, 0.3438, respectively). That is, the goodness-of-fit between ridge height (X1) and potential energy (X2) can further predict parameters under the scenario of the best parsimonious model.Investigation of 6 predictive powers (R2, Max-rescaled R2, Somers'D, Gamma, Tau-a, and c, respectively) indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

基于独立坐标系相邻地形图的拼接处理

随着测绘技术的不断发展,各种工程用图也采用了独立坐标系,对于大范围或者高低起伏过大的测区,需要建立多个独立坐标系。为了满足设计或者规划的需求,需要对更多的分幅地形图进行拼接。介绍了基于独立坐标系地形图的拼接处理,分析了拼接处理的不同方法。认为地形图的拼接是测绘中的重要环节,必须认真对待,严格处理好。     

浅谈独立坐标系的建立

当测区远离中央子午线或平均高程较高时,基于满足工程测量中测量精度的要求,缩小长度投影变形的影响等因素,应建立地方独立坐标系。本文就建立地方独立坐标系谈一点认识。