哈依煤气工程管线GPS测量及数据处理

介绍哈依煤气工程管线ＧＰＳ控制网的布设、施测及观测数据处理,总结了长距离导线型ＧＰＳ控制网布设的可能性与经验。     

专用方位控制网形变检测方案的设计

为检测专用方位控制网是否发生了明显变形 ,本文作者提出了方位边夹角灵敏度的概念 ,并推导了相应的公式。     

Non-destructive estimation of foliar chlorophyll and carotenoid contents: Focus on informative spectral bands

Leaf pigment content provides valuable insight into the productivity, physiological and phenological status of vegetation. Measurement of spectral reflectance offers a fast, nondestructive method for pigment estimation. A number of methods were used previously for estimation of leaf pigment content, however, spectral bands employed varied widely among the models and data used. Our objective was to find informative spectral bands in three types of models, vegetation indices (VI), neural network (NN) and partial least squares (PLS) regression, for estimating leaf chlorophyll (Chl) and carotenoids (Car) contents of three unrelated tree species and to assess the accuracy of the models using a minimal number of bands. The bands selected by PLS, NN and VIs were in close agreement and did not depend on the data used. The results of the uninformative variable elimination PLS approach, where the reliability parameter was used as an indicator of the information contained in the spectral bands, confirmed the bands selected by the VIs, NN, and PLS models. All three types of models were able to accurately estimate Chl content with coefficient of variation below 12% for all three species with VI showing the best performance. NN and PLS using reflectance in four spectral bands were able to estimate accurately Car content with coefficient of variation below 14%. The quantitative framework presented here offers a new way of estimating foliar pigment content not requiring model re-parameterization for different species. The approach was tested using the spectral bands of the future Sentinel-2 satellite and the results of these simulations showed that accurate pigment estimation from satellite would be possible.     

边角后方交会在高铁板式无碴轨道放样中的应用

智能型全站仪结合边角后方交会原理在高速铁路测量工作中得到广泛应用,其在CPⅢ高精度铺轨控制网的基础上进行自由重叠设站的精度能满足高铁测量的精度要求。在板式无碴轨道底板放样和轨道板安装时,可以根据仪器误差参数计算得出每个测站进行放样时误差不超限的最远放样距离,供测量人员参考。     

采用弱基准和抗差估计的重力网平差

以沿海某测区绝对重力和相对重力网数据处理为例,详细描述了弱基准重力网平差的方法,绝对重力和相对重力先验权的确定,用抗差等价权来调整相对重力的权、重力仪参数的取舍。结果表明,弱基准能有效地提高整网的精度;抗差估计能有效地探测并降低异常数据的权。重力点平均中误差为13.6×10-8 ms-2,偶然误差检验符合正态分布。     

基于小波分析的灰色-神经网络组合模型在大坝变形预测中的应用

监测序列经小波分解后可以得到各层分量。对低频分量采用灰色GM(1,1)模型进行建模预测,对高频分量采用BP神经网络进行建模预测,最后将各分量进行小波重构,得到监测序列的预测值。将预测值分别与没有进行小波分解直接用GM(1,1)模型预测的值和经小波分解的低、高频系数都采用GM(1,1)模型预测的值进行对比,发现经小波分解的灰色-神经网络组合模型预测精度更高。     

大尺寸高精度三维控制网技术探讨

空间大尺寸机构的位置和姿态测量是诸多领域中不可或缺的必要环节。而传统的一维测量技术在精度、范围和速度上已经无法满足越来越高的需求,因此必须探索新的测量技术和方法。激光跟踪仪的单站坐标测量精度在局部范围内能够达到几十个微米量级,如果要在大尺度空间内同样实现该坐标测量精度,则需要建立全局的精密三维控制网。为了解算控制点全局坐标以及测站的位置和姿态参数,文中基于边角观测值和坐标转换模型建立了激光跟踪仪三维边角网整体平差模型。平差过程中,为了削弱激光跟踪仪测角误差的影响,建立了合理的角度和距离观测值权矩阵,为高精度距离观测值赋予较大的权值,从而对其进行约束。将该方法应用于宝钢不锈钢冷轧厂生产线的安装检测和轧辊轴线平行度测量,基于激光跟踪仪自由设站理论实现大尺寸精密三维控制网的建立,取得了良好效果。     

HBCORS高精度参考框架获取策略分析

通过对HBCORS坐标联测方法、基线处理策略以及网平差策略进行研究,分析了HBCORS高精度参考框架建立的方法,为高精度区域参考框架的获取以及高精度GPS网数据处理提供了思路。     

BP神经网络用于水下地形适配区划分的方法研究

为确保背景场中最优适配航线设计的正确性以及水下地形匹配导航的可靠性,提出了一种基于BP神经网络的背景场适配/误配区自动识别和划分方法,该方法通过分析地形背景场特征参量显著性和主成分、构建BP神经网络、建立输入地形特征参量与匹配性能的映射关系,最终实现了地形背景场误配/适配区的自动识别和划分。试验验证了本方法的有效性。     

“数字重庆”地理空间信息定位基准体系的建设

介绍了"数字重庆"地理空间信息定位基准建设的基本情况,着重阐述了CQGNSS、高精度GPS控制网、精密水准网和区域似大地水准面精化等方面的数据处理情况,展示了山城地区的基准体系建设特点。