Comparison of GMF/GPT with VMF1/ECMWF and implications for atmospheric loading

This paper compares estimates of station coordinates from global GPS solutions obtained by applying different troposphere models: the Global Mapping Function (GMF) and the Vienna Mapping Function 1 (VMF1) as well as a priori hydrostatic zenith delays derived from the Global Pressure and Temperature (GPT) model and from the European Centre for Medium-Range Weather Forecasts (ECMWF) numerical weather model data. The station height differences between terrestrial reference frames computed with GMF/GPT and with VMF1/ECMWF are in general below 1 mm, and the horizontal differences are even smaller. The differences of annual amplitudes in the station height can also reach up to 1 mm. Modeling hydrostatic zenith delays with mean (or slowly varying empirical) pressure values instead of the true pressure values results in a partial compensation of atmospheric loading. Therefore, station height time series based on the simple GPT model have a better repeatability than those based on more realistic ECMWF troposphere a priori delays if atmospheric loading corrections are not included. On the other hand, a priori delays from numerical weather models are essential to reveal the full atmospheric loading signal.     

Assessment of troposphere mapping functions using three-dimensional ray-tracing

The troposphere delay is an important source of error for precise GNSS positioning due to its high correlation with the station height parameter. It has been demonstrated that errors in mapping functions can cause sub-annual biases as well as affect the repeatability of GNSS solutions, which is a particular concern for geophysical studies. Three-dimensional ray-tracing through numerical weather models (NWM) is an excellent approach for capturing the directional and daily variation of the tropospheric delay. Due to computational complexity, its use for positioning purposes is limited, but it is an excellent tool for evaluating current state-of-the-art mapping functions used for geodetic positioning. Many mapping functions have been recommended in the past such as the Niell Mapping Function (NMF), Vienna Mapping Function 1 (VMF1), and the Global Mapping Function (GMF), which have been adopted by most IGS analysis centers. A new Global Pressure Temperature model (GPT2) has also been developed, which has been shown to improve upon the original atmospheric model used for the GMF. Although the mapping functions mentioned above use the same functional formulation, they vary in terms of their atmospheric source and calibration approach. A homogeneous data set of three-dimensional ray-traced delays is used to evaluate all components of the mapping functions, including their underlying functional formulation, calibration, and compression method. Additionally, an alternative representation of the VMF1 is generated using the same atmospheric source as the truth data set to evaluate the differences in ray-tracing methods and their effect on the end mapping function. The results of this investigation continue to support the use of the VMF1 as the mapping function of choice when geodetic parameters are of interest. Further support for the GPT2 and GMF as reliable back-ups when the VMF1 is not available was found due to their high consistency with the NWM-derived mapping function. Additionally, a small latitude-dependent bias in station height was found in the current mapping functions. This bias was identified to be due to the assumption of a constant radius of the earth and was largest at the poles and at the equator. Finally, an alternative version of the VMF1 is introduced, namely the UNB-VMF1 which provides users with an independent NWM-derived mapping function to support geodetic positioning.     

GPT/GPT2/GPT3模型在广东省适应性对比分析

针对不同全球温度气压湿度模型(GPT/GPT2/GPT3)在不同地区精度不一致的问题,利用CMONOC观测数据验证GPT/GPT2/GPT3模型在广东省适应性,分别对气温、气压、水气压和大气可降水量进行定量分析,实验结果表明:GPT3模型在气温方向较GPT2和GPT模型相比,BIAS值分别提升26.7％、53.7％,R...     

Testing of global pressure/temperature (GPT) model and global mapping function (GMF) in GPS analyses

Several sources of a priori meteorological data have been compared for their effects on geodetic results from GPS precise point positioning (PPP). The new global pressure and temperature model (GPT), available at the IERS Conventions web site, provides pressure values that have been used to compute a priori hydrostatic (dry) zenith path delay z _h estimates. Both the GPT-derived and a simple height-dependent a priori constant z _h performed well for low- and mid-latitude stations. However, due to the actual variations not accounted for by the seasonal GPT model pressure values or the a priori constant z _h, GPS height solution errors can sometimes exceed 10 mm, particularly in Polar Regions or with elevation cutoff angles less than 10 degrees. Such height errors are nearly perfectly correlated with local pressure variations so that for most stations they partly (and for solutions with 5-degree elevation angle cutoff almost fully) compensate for the atmospheric loading displacements. Consequently, unlike PPP solutions utilizing a numerical weather model (NWM) or locally measured pressure data for a priori z _h, the GPT-based PPP height repeatabilities are better for most stations before rather than after correcting for atmospheric loading. At 5 of the 11 studied stations, for which measured local meteorological data were available, the PPP height errors caused by a priori z _h interpolated from gridded Vienna Mapping Function-1 (VMF1) data (from a NWM) were less than 0.5 mm. Height errors due to the global mapping function (GMF) are even larger than those caused by the GPT a priori pressure errors. The GMF height errors are mainly due to the hydrostatic mapping and for the solutions with 10-degree elevation cutoff they are about 50% larger than the GPT a priori errors.     

Refined discrete and empirical horizontal gradients in VLBI analysis

Missing or incorrect consideration of azimuthal asymmetry of troposphere delays is a considerable error source in space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). So-called horizontal troposphere gradients are generally utilized for modeling such azimuthal variations and are particularly required for observations at low elevation angles. Apart from estimating the gradients within the data analysis, which has become common practice in space geodetic techniques, there is also the possibility to determine the gradients beforehand from different data sources than the actual observations. Using ray-tracing through Numerical Weather Models (NWMs), we determined discrete gradient values referred to as GRAD for VLBI observations, based on the standard gradient model by Chen and Herring (J Geophys Res 102(B9):20489–20502, 1997.  https://doi.org/10.1029/97JB01739) and also for new, higher-order gradient models. These gradients are produced on the same data basis as the Vienna Mapping Functions 3 (VMF3) (Landskron and Böhm in J Geod, 2017.  https://doi.org/10.1007/s00190-017-1066-2), so they can also be regarded as the VMF3 gradients as they are fully consistent with each other. From VLBI analyses of the Vienna VLBI and Satellite Software (VieVS), it becomes evident that baseline length repeatabilities (BLRs) are improved on average by 5% when using a priori gradients GRAD instead of estimating the gradients. The reason for this improvement is that the gradient estimation yields poor results for VLBI sessions with a small number of observations, while the GRAD a priori gradients are unaffected from this. We also developed a new empirical gradient model applicable for any time and location on Earth, which is included in the Global Pressure and Temperature 3 (GPT3) model. Although being able to describe only the systematic component of azimuthal asymmetry and no short-term variations at all, even these empirical a priori gradients slightly reduce (improve) the BLRs with respect to the estimation of gradients. In general, this paper addresses that a priori horizontal gradients are actually more important for VLBI analysis than previously assumed, as particularly the discrete model GRAD as well as the empirical model GPT3 are indeed able to refine and improve the results.     

Measuring the goodness-of-fit of decision-tree models of discrete and continuous activity-travel choice: methods and empirical illustration

The use of decision tree models for predicting activity-travel choice is receiving increasing attention, but raises two related problems that are considered in this study. First, commonly used deterministic action-assignment rules should be replaced by probabilistic action-assignment rules. We develop such probabilistic rules for both discrete and continuous choice problems. Second, common goodness-of-fit measures such as the hit-ratio need to be replaced by likelihood measures. In this paper, we develop and empirically illustrate the interrelated methods and measures. The findings suggest that the new measures add information to existing statistics for discrete as well as the continuous choice.     

RETRACTED ARTICLE: Likelihood-based GNSS positioning using LOS/NLOS predictions from 3D mapping and pseudoranges

The accuracy of conventional global navigation satellite systems (GNSS) positioning in dense urban areas is severely degraded due to blockage and reflection of the signals by the surrounding buildings. By using 3D mapping of the buildings to aid GNSS positioning, the accuracy can be substantially improved. However, positioning performance must be balanced against computational load. Here, a likelihood-based 3D-mapping-aided (3DMA) GNSS ranging algorithm is demonstrated that enables signals predicted to be non-line-of-sight (NLOS) to contribute to the position solution without explicitly computing the additional path delay due to NLOS reception, which is computationally expensive. Likelihoods for an array of candidate positions are computed based on the difference between the measured and predicted pseudoranges. However, a skewed distribution is assumed for those signals predicted to be NLOS on the basis that the ensuing ranging errors are always positive. An overall position solution is then extracted from the likelihood surface. GNSS measurement data have been collected at several locations in both traditional and modern dense urban environments. Horizontal root-mean-square single-epoch position accuracies of 4.7, 5.6 and 6.5 m are obtained using, respectively, a Leica Viva geodetic receiver, a u-blox EVK M8T consumer-grade receiver and a Nexus 9 tablet incorporating a smartphone GNSS antenna and a GNSS chipset that outputs pseudoranges. The corresponding accuracies using single-epoch conventional GNSS positioning are 20.5, 23.0 and 28.4 m, about a factor of four larger. The 3DMA GNSS algorithms have also been implemented in real time on a Raspberry Pi 3 at a 1-Hz update rate.

     

FORSAT: a 3D forest monitoring system for cover mapping and volumetric 3D change detection

ABSTRACT

A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing platform for forest assessment), was developed for the extraction of 3D geometric forest information from very high resolution (VHR) satellite imagery and the automatic 3D change detection. FORSAT is composed of two complementary tasks: (1) the geometric and radiometric processing of satellite optical imagery and digital surface model (DSM) reconstruction by using a precise and robust image matching approach specially designed for VHR satellite imagery, (2) 3D surface comparison for change detection. It allows the users to import DSMs, align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes (together with precision values) between epochs. FORSAT is a single source and flexible forest information solution, allowing expert and non-expert remote sensing users to monitor forests in three and four (time) dimensions. The geometric resolution and thematic content of VHR optical imagery are sufficient for many forest information needs such as deforestation, clear-cut and fire severity mapping. The capacity and benefits of FORSAT, as a forest information system contributing to the sustainable forest management, have been tested and validated in case studies located in Austria, Switzerland and Spain.     

Satellite sensor modeling and 3D geo-positioning using empirical models

The need for the use of general empirical mathematical models for satellite sensor modeling and 3D geo-positioning has increased recently, mainly because of the absence of the satellite sensor information of some of the high-resolution satellites. In addition, empirical mathematical models can be applied to different satellite sensors since they are time independent mathematical models and do not require specialized commercial software packages. This paper discusses the applicability of the empirical mathematical models presented by the 3D affine model and the 3D polynomial models for satellite sensor modeling and 3D geo-positioning. The objectives of the paper are to demonstrate that (a) the 3D affine model and its modifications of the 3D polynomial models are applicable to different satellite sensors and different types of terrain, and (b) under some conditions, the empirical models can produce accuracies close to those from rigorous mathematical models.     

巷道自动成图及三维建模

针对矿山计算机自动绘制巷道工程图存在工作繁重、精度不高的现象,本文建立了基于矿山测量数据的巷道生成算法,实现了巷道的自动绘制与标注。在此基础上,采用分而治之算法及巷道轮廓线作为约束线段的方式建立了巷道Delaunay三角网,并生成了巷道表面模型。通过巷道顶、底板表面模型的剖分连接实现了矿山巷道三维立体建模。对比目前采用较多的巷道中心线加载巷道断面的三维建模方式,本文所提供的方法避免了巷道中心线不易提取、巷道断面变形、巷道转弯处难以平滑及复杂的巷道节点拓扑运算等问题,具有自动化程度高、容易实现等特点。     

A clear link connecting the troposphere and ionosphere: ionospheric reponses to the 2015 Typhoon Dujuan

The global navigation satellite system (GNSS) total electron content (TEC) sequences were used to capture the arrival time and location of the ionosphere disturbances in response to the 2015 Typhoon Dujuan. After removing the de-trended TEC variation, the clear ionosphere disturbances on the typhoon landing day could be distinguished, and these disturbances disappeared from the TEC sequences before and after the typhoon landing day. The foF2 data observed by Xiamen ionosonde station also show ionosphere disturbances. Based on the advantages of GNSS multi-point observations, the disturbances horizontal velocity in the ionosphere were estimated according to the linear theory for a dispersion relation of acoustic gravity waves (AGWs) in an isothermal atmosphere. The average horizontal velocity (\(\sim \)240 m/s) and the radial velocity (\(\sim \)287 m/s) were used in the two-dimensional grid search for the origin point on the Earth’s surface. The origin area was determined to be on the eastern side of Taiwan. Lastly, a possible physical mechanism is discussed in this study. When typhoons land on Taiwan, the severe convective storms and the drag effect from the Central Mountains create an ideal location for development of AGWs. Topographic conditions, like the high lapse rate, contribute to the formation of AGWs, which then propagates into the ionosphere altitude.     

Effect of different tropospheric mapping functions on the TRF, CRF and position time-series estimated from VLBI

This paper compares estimated terrestrial reference frames (TRF) and celestial reference frames (CRF) as well as position time-series in terms of systematic differences, scale, annual signals and station position repeatabilities using four different tropospheric mapping functions (MF): The NMF (Niell Mapping Function) and the recently developed GMF (Global Mapping Function) consist of easy-to-handle stand-alone formulae, whereas the IMF (Isobaric Mapping Function) and the VMF1 (Vienna Mapping Function 1) are determined from numerical weather models. All computations were performed at the Deutsches Geodätisches Forschungsinstitut (DGFI) using the OCCAM 6.1 and DOGS-CS software packages for Very Long Baseline Interferometry (VLBI) data from 1984 until 2005. While it turned out that CRF estimates only slightly depend on the MF used, showing small systematic effects up to 0.025 mas, some station heights of the computed TRF change by up to 13 mm. The best agreement was achieved for the VMF1 and GMF results concerning the TRFs, and for the VMF1 and IMF results concerning scale variations and position time-series. The amplitudes of the annual periodical signals in the time-series of estimated heights differ by up to 5 mm. The best precision in terms of station height repeatability is found for the VMF1, which is 5–7% better than for the other MFs.     

一种结合纹理择优算法的影像三维重建方法

针对多视影像重叠度高、影像来源丰富等特点,提出了一种基于多视角影像的纹理择优映射算法,该方法对模型三角形进行逐个相机场景可见性分析,对模型在场景中不可见三角形和部分可见三角形进行选择性剔除,只对完全可见三角形及符合阈值计算的部分可见三角形提供候选纹理三角形,能有效解决模型不可见三角形和部分可见三角形被误贴纹理的问题,再通过对候选纹理三角形的视角分析,为几何模型表面三角形选择一个理论最优纹理,计算映射关系自动映射到模型表面。同时,本文将该纹理择优映射算法应用到基于近景影像的三维重建中,使用从运动中恢复结构SFM的方法进行相机标定及影像相对定向,通过CMVS/PMVS密集匹配方法从影像中获取点云模型,采用Possion算法重构模型三角网,最终利用提出的纹理择优算法确定最佳纹理并实现自动映射。通过与Smart3d、PhotoScan、lensphoto软件的对比证明了本文三维重建及纹理择优算法在近景影像三维重建中的有效性。     

Automatic near-photorealistic 3-D modelling and texture mapping for rectilinear buildings

Three-dimensional (3-D) representations of urban regions have gained much attention because of recent developments in remote sensing and computer graphics technologies. In particular, textured 3-D building reconstruction for a variety of applications has been a popular research topic in recent years. In this study, we present the reconstruction of 3-D building models along with texture selection and mapping. Extracted two-dimensional building patches and normalized digital surface model (nDSM) data are used to generate the 3-D models. To build near-photorealistic 3-D models, the acquired geo-referenced facade textures are associated with the corresponding building facades using an automated GPS-assisted approach. On the other hand, the modelling and texture mapping of the roof structures were carried out manually. The study area is composed of eight housing estates (blocks), where a total of 110 buildings were analysed. The whole study area was modelled, with facade textures, in less than 1 min of processor running time with an acceptable level of accuracy. The texture mapping was carried out using MATLAB’s Virtual Reality Toolbox?.     

推车SLAM室内实景三维测图及应用

以推车SLAM移动测图系统NavVis为数据采集手段,简要介绍了其工作原理,并详细介绍了室内实景三维测图的技术流程,实现了室内三维实景地图的网络发布。同时,对该地图定制了兴趣点(POI)添加查询和室内导航路径规划两种应用功能。NavVis推车SLAM系统提供的从数据采集、数据处理、网络发布到地图应用的一整套解决方案,为室内推车SLAM的发展和高精度三维实景地图的制作提供了有益的参考。     

The refined spatiotemporal representation of soil organic matter based on remote images fusion of Sentinel-2 and Sentinel-3

Remote sensing technology is important for soil organic matter (SOM) estimation, but existing studies have mainly relied on a single data source. This limitation makes it difficult to simultaneously ensure high spatial resolution, high spectral accuracy and refined temporal granularity simultaneously, which cannot meet the requirements of the spatiotemporal dynamics representation. This study aimed to introduce a new remote sensing image source into SOM modeling and spatiotemporal estimation generated by fusing together Sentinel-2 and Sentinel-3 remote sensing images that have a 5-day revisit cycle; 10 m spatial resolution; and 21 different bands in blue, green, red and NIR spectral ranges. According to the image fusion process, a total of 52 available images were acquired between November 2016 and December 2018 in Donghai County, China. The fused images were used for SOM estimation model associated with 107 field samples. The results indicated that, first, the optimal model consisted of the band reflectivity (B20) and RVI (B18/B9), which were derived from the fused images, and the R² approached 0.7 in the two phases of the synchronized data. Second, the modeling accuracy was influenced to some extent by the actual SOM content. The R² values exceeded 0.75 when the SOM content was higher than 24 g/kg, while the R² was even lower than 0.35 when the SOM content was lower. Third, the averaged SOM contents remained stable in general, while the seasonal variances can also be found during the two-year interval. The SOM contents maintained a low level during autumn and winter, while higher SOM levels were found in the spring and summer. Finally, the spatial variations could be described as ‘low in the west and high in the east’. In summary, the spatiotemporal dynamics of SOM highlighted the necessity of modeling with fused remote sensing images, and more effective modeling could be expected with the continued increase in SOM in future.     

北斗三号卫星经验型太阳光压模型分析与精化

太阳光压摄动作为在轨导航卫星受到的最大的非保守力,是卫星精密定轨的重要误差源。ECOM模型、ECOM2模型,这两种经验型光压模型被广泛应用于导航卫星定轨。然而,ECOM模型和ECOM2模型分别是针对GPS和GLONASS卫星设计的,并不完全适用于我国北斗三号(BDS-3)卫星。针对五参数ECOM模型在BDS-3卫星低太阳高度角时期轨道不连续性增大的问题,本文提出在 D方向引入一阶周期项来吸收未被模型化光压加速度。结果表明,引入一阶余弦周期项 D_c,能将低太阳高度角时期CAST卫星的切向、法向、径向重叠轨道误差分别减小约60%、52%、29%。针对ECOM2模型中 D_2c和 D₀、D_2s和 B_s之间存在的强相关性,本文提出了不估计 D_2c参数的八参数ECOM2模型和不估计 D_2c与 D_2s的七参数ECOM2模型。结果表明,相较九参数ECOM2模型,不估计 D_2c参数的八参数ECOM2模型能够将CAST卫星和SECM卫星径向重叠轨道误差分别减少约18%和27%。在此基础上,继续移除 D_2s后(七参数ECOM2),径向重叠轨道误差可进一步减小5.2%~8.5%。综合考察重叠轨道精度和SLR检核精度,不顾及 D_2c和 D_2s的七参数ECOM2模型表现最佳。CAST卫星和SECM卫星重叠轨道切向、法向、径向精度分别为5.0、3.4、1.4 cm和5.4、3.5、1.5 cm;SLR检核残差标准差分别为3.1~3.2 cm、4.4~4.7 cm。     

面向智能化测绘的城市地物三维提取

精准有效的三维时空信息是新型基础设施建设、实景三维中国、自然资源管理与监测等国家重大需求不可或缺的重要支撑。测绘装备的快速发展提升了点云和影像获取的便捷性,为智能化测绘提供了一种全新技术手段。然而,如何从点云、影像中智能地提取三维时空信息仍然面临诸多困境。本文围绕城市场景中地物目标智能化提取的需求,重点阐述点云位置精度改善、点云与全景影像融合、部件级典型地物要素精细提取、软件研发与工程实践4个方面的关键技术与研究进展,为实景三维中国建设等提供关键支持。