二维水质扩散模型的建立及应用

根据东湖实际，探讨了二维湖泊水质扩散模型及其定解。提出的二维交替算法，具有快速收敛及确保精度等特点；改进后的内插模型解决了流场和浓度场的初始值和边界条件问题，形成了全湖数字高程模型；在浓度等值线快速生成的基础上，通过接口自动形成信息系统空间和属性件，完成了专题自动分类。     

矿井巷道三维自动建模方法研究

基于地理信息系统和虚拟现实技术，提出了由二维巷道到三维巷道的自动建模方法，研究了二维巷道表达、数据提取与组织和三维巷道生成等问题，开发了一个原型系统，完成了二雏巷道数据导入、模型转换、渲染与驱动，并结合河南平煤集团大庄矿实际，实现了巷道模型的自动建立，取得了令人满意的效果。     

基于建筑物投影差纠正算法的电子地图生成与应用

针对2.5维电子地图中由于地形起伏导致的建筑物投影差的问题,本文设计并实现了一种建筑物投影差纠正算法,结合平行投影自动出图,能够将三维建筑物体块模型、三维建筑物精细模型、倾斜摄影实景建筑物三维模型、建筑物点云等快速生成2.5维电子地图。主要特点是支持多种建筑物数据源、坐标自动配准和建筑物投影差纠正,能够与正射影像或二维矢量数据进行无偏移叠加,有利于2.5维电子地图的广泛应用。     

DXF与OpenFlight API虚拟三维管网自动建模技术研究

通过分析DXF文件数据结构与三维管网模型,从DXF文件中提取二维管网数据,通过OpenFlight API构建三维图形并写入FLT文件,直接生成地下管网三维模型,实现了大场景地下管网的自动、快速建模。     

湖泊水质信息系统研究与应用

本文在建立湖泊运动模型，不量平衡模型的基础上，对污染物浓度的扩散进行了计算机模拟并快速形成了符合ＧＩＳ数据结构的空间数据和属性数据；实现了专题自动分类及查询子系统并对武汉市东湖富营养化物质氮，磷和江西赤湖重金属物质铜污染进行了计算机计算实验，达到了实用的要求。     

基于Skyline的城市三维管道自动生成技术

围绕城市地下三维管道的自动生成技术进行了分析与探讨,针对传统管道建模方法中所存在的不足之处,提出了一种基于Skyline的三维管道动态批量生成方法。其主要思想是：通过自动计算二维管线的三维管道建模参数,配合其属性参数的模板化机制,就能实现大规模三维场景中管道模型的快速创建。实践应用表明,该方法较传统建模方法更为快速和实用。     

七、P25 专业测绘与工程测量

CH20071028矿井巷道三维自动建模方法研究=On 3D Automatic Modeling Method of Mine Roadway/汪云甲,伏永明(中国矿业大学环境与测绘学院)∥武汉大学学报(信息科学版).-2006,31(12).-1097~1100基于地理信息系统和虚拟现实技术,提出了由二维巷道到三维巷道的自动建模方法,研究了二维巷道表达、数据提取与组织和三维巷道生成等问题,开发了一个原型系统,完成了二维巷道数据导入、模型转换、渲染与驱动,并结合河南平煤集团大庄矿实际,实现了巷道模型的自动建立,取得了令人满意的效果。图9参6CH20071029工业测量中一种二次曲面的拟合方法=A…     

利用归一化前景和二维联合熵的人群聚集检测方法

基于摄像机透视效应提出了一种场景归一化前景面积的计算方法;然后结合联合概率密度的概念设计出前景二值图的二维联合概率密度计算公式,并据此进一步计算出二维联合熵;最后,根据归一化前景面积和二维联合熵提出了一种人群聚集检测模型。实验表明,该模型可以实现对监控场景下人群聚集现象的快速有效检测。     

基于机载LiDAR的多面片建筑物3维重建方法研究

提出了顾及多面片建筑物模型拓扑关系的边界提取方法。针对多面片建筑物的特点并基于最小二乘法,设计了一套适合多面片建筑物的边界规则化方法,并生成了3维建筑物模型。实验证明,本文方法对于多面片建筑物模型的3维自动重建都是可行和有效的。     

一种基于三维模型的数据降维方法

在智慧城市建设推进过程中,各地利用三维建模软件如3ds Max获得大量的三维仿真模型,在城市管理和决策中发挥了重要作用。近年来,随着倾斜摄影技术、BIM技术等自动、半自动建模方法发展,极大地丰富了城市模型内涵,同时在生产、利用、管理上,给城市级的三维模型带来挑战。本文基于仿真模型,研究全自动、高效的降维技术,挖掘结构化的二维空间信息,在倾斜摄影模型单体化、2.5维地图中展开应用;并根据精确的几何位置信息,研究了一种地理编码,基于唯一的空间地理编码,关联城市二三维要素,可进行数据资源的快速定位、空间索引优化,为二三维一体化管理提供支撑。     

Improving prediction performance of GPS satellite clock bias based on wavelet neural network

As one of the IGS ultra-rapid predicted (IGU-P) products, the orbit precision has been remarkably improved since late 2007. However, because satellite atomic clocks in space show complicated time–frequency characteristics and are easily influenced by many external factors such as temperature and environment, the IGU-P clock products have not shown sufficient high-quality prediction performance. An improved prediction model is proposed in order to enhance the prediction performance of satellite clock bias (SCB) by employing a wavelet neural network (WNN) model based on the data characteristic of SCB. Specifically, two SCB values of adjacent epoch subtract each other to get the corresponding single difference sequence of SCB, and then, the sequence is preprocessed through using the preprocessing method designed for the single difference sequence. The subsequent step is to model the WNN based on the preprocessed sequence. After the WNN model is determined, the next single difference values at the back of the modeling sequence are predicted. Lastly, the predicted single difference values are restored to the corresponding predicted SCB values. The simulation results have shown that the proposed prediction principle based on the single difference sequence of SCB can make the WNN model simple in architecture and the predicting precision higher than that of the general SCB prediction modeling. The designed preprocessing method specific to the single difference of SCB is able to further improve the prediction performance of the WNN model by reducing the effect from outliers. The proposed SCB prediction model outperforms the IGU-P solutions at least on a daily basis. Specifically, the average prediction precisions for 6, 12 and 24 h based on the proposed model have improved by about 13.53, 31.56 and 49.46 % compared with the IGU-P clock products, and the corresponding average prediction stabilities for 12 and 24 h have increased by about 13.89 and 27.22 %, while the average prediction stability of 6 h is nearly equal.     

Lunar gravity field determination using SELENE same-beam differential VLBI tracking data

A lunar gravity field model up to degree and order 100 in spherical harmonics, named SGM100i, has been determined from SELENE and historical tracking data, with an emphasis on using same-beam S-band differential VLBI data obtained in the SELENE mission between January 2008 and February 2009. Orbit consistency throughout the entire mission period of SELENE as determined from orbit overlaps for the two sub-satellites of SELENE involved in the VLBI tracking improved consistently from several hundreds of metres to several tens of metres by including differential VLBI data. Through orbits that are better determined, the gravity field model is also improved by including these data. Orbit determination performance for the new model shows improvements over earlier 100th degree and order models, especially for edge-on orbits over the deep far side. Lunar Prospector orbit determination shows an improvement of orbit consistency from 1-day predictions for 2-day arcs of 6 m in a total sense, with most improvement in the along and cross-track directions. Data fit for the types and satellites involved is also improved. Formal errors for the lower degrees are smaller, and the new model also shows increased correlations with topography over the far side. The estimated value for the lunar GM for this model equals 4902.80080±0.0009 km³/s² (10 sigma). The lunar degree 2 potential Love number k ₂ was also estimated, and has a value of 0.0255 ± 0.0016 (10 sigma as well).     

BDS伪距偏差改正对UPD估计的影响分析

针对BDS伪距偏差严重影响UPD估计的问题,提出基于单站伪距偏差改正的UPD估计方法,并利用香港地区18个连续运行参考站2016-01-04至2016-01-13的数据进行UPD估计,详细分析BDS卫星伪距偏差改正前后的宽巷和窄巷UPD特性。结果表明:BDS卫星伪距偏差会对宽巷UPD的结果引入将近0.5个整周的偏差,降低宽巷和窄巷UPD的数据利用率,改正伪距偏差后,宽巷UPD的一致性、数据利用率以及残差分布均得到显著提高,窄巷UPD的估计结果尤其是数据利用率也得到提高。     

分布式虚拟地理环境中时间同步问题研究

分布式虚拟地理环境中的时间同步问题是达成系统时空一致,确保仿真正确,是用户对虚拟地理环境形成正确认识的前提条件。文中针对分布式虚拟地理环境中3个时间概念,重点对机器时间和仿真时间同步问题进行研究,基于网络延时、各仿真节点时间偏移和PC机及操作系统本身时间分辨率不高的因素对时间不同步造成的影响,提出时间同步自适应模型和算法。     

An improved SVM model for relevance feedback in remote sensing image retrieval

With the rapid development of satellite remote sensing technology and an ever-increasing number of Earth observation satellites being launched, the global volume of remotely sensed imagery has been growing exponentially. Processing the variety of remotely sensed data has increasingly been complex and difficult. It is also hard to efficiently and intelligently retrieve what users need from a massive database of images. This paper introduces an improved support vector machine (SVM) model, which optimizes the model parameters and selects the feature subset based on the particle swarm optimization (PSO) method and genetic algorithm (GA) for remote sensing image retrieval. The results from an image retrieval experiment show that our method outperforms traditional methods such as GRID, PSO, and GA in terms of consistency and stability.     

Quality of reprocessed GPS satellite orbits

High-precision Global Positioning System (GPS) satellite orbits are one of the core products of the International GNSS Service (IGS). Since the establishment of the IGS in 1994, the quality and consistency of the IGS orbits has steadily been improved by advances in the modeling of GPS observations. However, due to these model improvements and reference frame changes, the time series of operational orbits are inhomogeneous and inconsistent. This problem can only be overcome by a complete reprocessing starting with the raw observation data. The quality of reprocessed GPS satellite orbits for the time period 1994–2005 will be assessed in this paper. Orbit fits show that the internal consistency of the orbits could be improved by a factor of about two in the early years. Comparisons with the operational IGS orbits show clear discontinuities whenever the reference frame was changed by the IGS. The independent validation with Satellite Laser Ranging (SLR) residuals shows an improvement of up to 30% whereas a systematic bias of 5 cm still persists.     

利用水位修正模型精化潮位数值模拟

利用海洋动力模式FVCOM（finite volume coast and ocean model）模式建立了高分辨率的海州湾及其外海域潮汐数值模型,提取了整个场内各个网格点上天文潮位值的时间序列。利用该区域内分布的5个验潮站资料提取水位修正模型,对场内的网格点进行水位修正,得到高精度的格点水位时间序列,然后对修正前后的水位值进行比较。结果表明,基于水位修正后的潮位数值模拟结果水位精度提高了10 cm左右。     

Improvement of the empirical thermospheric model DTM: DTM94 – a comparative review of various temporal variations and prospects in space geodesy applications

The Drag Temperature Model (1978) has been improved to respond better to the actual requirements of space geodesy, especially under extreme solar and geomagnetic conditions. Extended data and an improved algorithm have been considered, leading to valuable improvements. Temporal variations of temperature of the thermopause, total density and major chemical constituent density are reviewed and compared to the DTM94, DTM78 and MSIS86 models. A comparison with data is performed, giving the mean ratios between observed and model values with their root mean squares for different physical and geometric conditions. This comparison is made for the three models and includes data used in the modelling as well as external data. The limits of the thermosphere modelling are discussed. Received: 3 December 1996 / Accepted: 4 August 1997     

幂函数变换的GM(1,1)模型在BDS卫星钟差预报中的应用研究

由于卫星钟存在频率高、敏感性强、极易受到外界影响从而导致观测数据波动大,预测结果精度低的问题,利用幂函数变换法对初始观测数据进行变换预处理,从而提高观测数据的平顺度.由此提出一种基于幂函数变换的GM(1,1)模型,选用北斗卫星导航系统(BDS)卫星钟差进行插值和预报,并且进行了精度验证.实验结果表明:Lagrange插值方法可以满足高精度BDS的钟差的插值需要;利用幂函数变换的GM(1,1)模型相比传统模型精度有效提高了,而且当改进模型和传统模型预报值越接近实际值,则幂函数改进的GM(1,1)模型精度更高,适用性更强,对BDS卫星钟差预报具有实际参考价值.     

Orbit determination of the SELENE satellites using multi-satellite data types and evaluation of SELENE gravity field models

The SELENE mission, consisting of three separate satellites that use different terrestrial-based tracking systems, presents a unique opportunity to evaluate the contribution of these tracking systems to orbit determination precision. The tracking data consist of four-way Doppler between the main orbiter and one of the two sub-satellites while the former is over the far side, and of same-beam differential VLBI tracking between the two sub-satellites. Laser altimeter data are also used for orbit determination. The contribution to orbit precision of these different data types is investigated through orbit overlap analysis. It is shown that using four-way and VLBI data improves orbit consistency for all satellites involved by reducing peak values in orbit overlap differences that exist when only standard two-way Doppler and range data are used. Including laser altimeter data improves the orbit precision of the SELENE main satellite further, resulting in very smooth total orbit errors at an average level of 18 m. The multi-satellite data have also resulted in improved lunar gravity field models, which are assessed through orbit overlap analysis using Lunar Prospector tracking data. Improvements over a pre-SELENE model are shown to be mostly in the along-track and cross-track directions. Orbit overlap differences are at a level between 13 and 21 m with the SELENE models, depending on whether 1-day data overlaps or 1-day predictions are used.