Scale-oriented temporal analysis of movement data: A series-based approach

The ubiquity of movement data has led to new research interest in aspects of temporal scale. Few of the approaches analyzing movement data have been developed specifically for scale-oriented temporal analysis. To overcome this limitation, this article proposes a series-based approach to perform scale-oriented temporal analysis of movement data. Key to the proposed approach is the construction of four types of series (one type of identical-scale series and three types of cross-scale series) based on the continuous triangular model (CTM). Two distinct research goals are derived from this: to investigate the changes in motion attributes of moving individuals across different temporal scales, and to detect the time intervals during which active events might have occurred. The results based on real football movement data show that finer changes in motion attributes can be found and more accurate time intervals can be detected through the proposed approach.     

顾及用户体验的三维城市模型自适应组织方法

传统基于“图层付象”的组织方法,没有考虑三维城市模型的不同内容以及不同细节层次的粒度差异,导致在网络环境下的传输效率低,难以满足多用户并发访问的流畅可视化。深入分析了大范围漫游与小范围聚焦的用户体验特点,通过元数据统筹管理和对象离散化,即时响应用户请求,减少无效数据传输,保证了多用户并发环境下的高效调度和浏览。针对模型LoI)和分解的对象,设计了结构统一的对象ID,隐式存储关联关系并支持分布式模型存储管理。以分布式数据库MongoDB为平台进行实验,验证了本文方法的可行性和有效性。     

基于SMVF的高频雷达自适应多目标检测

针对高频雷达强海杂波和干扰环境下的多目标检测问题,结合S-method时频分布和Vitcrbi算法提出了一种多分量线性调频信号瞬时频率估计方法—SMVF法(S-method viterbi fitting),然后根据所提取的瞬时频率的直线拟合性能,提出了一种自适应多目标检测算法。实测数据的处理结果,表明了该算法在低信噪比时,与WDM法(wigncr distribution maxima) , WDV法( wigncr distribution vitcrbi)相比,估计精度提高约2000,验证了该算法的可行性和有效性。     

The determination of potential difference by the joint application of measured and synthetical gravity data: a case study in Hungary

In an elementary approach every geometrical height difference between the staff points of a levelling line should have a corresponding average g value for the determination of potential difference in the Earth’s gravity field. In practice this condition requires as many gravity data as the number of staff points if linear variation of g is assumed between them. Because of the expensive fieldwork, the necessary data should be supplied from different sources. This study proposes an alternative solution, which is proved at a test bed located in the Mecsek Mountains, Southwest Hungary, where a detailed gravity survey, as dense as the staff point density (~1 point/34 m), is available along a 4.3-km-long levelling line. In the first part of the paper the effect of point density of gravity data on the accuracy of potential difference is investigated. The average g value is simply derived from two neighbouring g measurements along the levelling line, which are incrementally decimated in the consecutive turns of processing. The results show that the error of the potential difference between the endpoints of the line exceeds 0.1 mm in terms of length unit if the sampling distance is greater than 2 km. Thereafter, a suitable method for the densification of the decimated g measurements is provided. It is based on forward gravity modelling utilising a high-resolution digital terrain model, the normal gravity and the complete Bouguer anomalies. The test shows that the error is only in the order of 10⁻³mm even if the sampling distance of g measurements is 4 km. As a component of the error sources of levelling, the ambiguity of the levelled height difference which is the Euclidean distance between the inclined equipotential surfaces is also investigated. Although its effect accumulated along the test line is almost zero, it reaches 0.15 mm in a 1-km-long intermediate section of the line.     

半参数模型统计诊断与粗差检验

This paper systematically studies the statistical diagnosis and hypothesis testing for the semiparametric linear regression model according to the theories and methods of the statistical diagnosis and hypothesis testing for parametric regression model.Several diagnostic measures and the methods for gross error testing are derived.Especially,the global and local influence analysis of the gross error on the parameter X and the nonparameter s are discussed in detail;at the same time,the paper proves that the d...     

Using gravity and topography-implied anomalies to assess data requirements for precise geoid computation

Many regions around the world require improved gravimetric data bases to support very accurate geoid modeling for the modernization of height systems using GPS. We present a simple yet effective method to assess gravity data requirements, particularly the necessary resolution, for a desired precision in geoid computation. The approach is based on simulating high-resolution gravimetry using a topography-correlated model that is adjusted to be consistent with an existing network of gravity data. Analysis of these adjusted, simulated data through Stokes’s integral indicates where existing gravity data must be supplemented by new surveys in order to achieve an acceptable level of omission error in the geoid undulation. The simulated model can equally be used to analyze commission error, as well as model error and data inconsistencies to a limited extent. The proposed method is applied to South Korea and shows clearly where existing gravity data are too scarce for precise geoid computation.     

A hierarchical model for estimating methane emission from wetlands using MODIS data and ARIMA modeling

A three-step hierarchical Semi Automated Empirical Methane Emission Model (SEMEM) has been used to estimate methane emission from wetlands and waterlogged areas in India using Moderate Resolution Imagine Spectroradiometer (MODIS) sensor data onboard Terra satellite. Wetland Surface Temperature (WST), methane emission fluxes and wetland extent have been incorporated as parameters in order to model the methane emission. Analysis of monthly MODIS data covering the whole of India from November 2004 to April 2006 was carried out and monthly methane emissions have been estimated. Interpolation techniques were adopted to fill the data gaps due to cloudy conditions during the monsoon period. AutoRegressive Integrated Moving Average (ARIMA) model has been fitted to estimate the emitted methane for the months of May 2006 to August 2006 using SPSS software.     

Climate applications of a global, 2-hourly atmospheric precipitable water dataset derived from IGS tropospheric products

A global, 2-hourly atmospheric precipitable water (PW) dataset is produced from ground-based GPS measurements of zenith tropospheric delay (ZTD) using the International Global Navigation Satellite Systems (GNSS) Service (IGS) tropospheric products (~80–370 stations, 1997–2006) and US SuomiNet product (169 stations, 2003–2006). The climate applications of the GPS PW dataset are highlighted in this study. Firstly, the GPS PW dataset is used as a reference to validate radiosonde and atmospheric reanalysis data. Three types of systematic errors in global radiosonde PW data are quantified based on comparisons with the GPS PW data, including measurement biases for each of the fourteen radiosonde types along with their characteristics, long-term temporal inhomogeneity and diurnal sampling errors of once and twice daily radiosonde data. The comparisons between the GPS PW data and three reanalysis products, namely the NCEP-NCAR (NNR), ECMWF 40-year (ERA-40) and Japanese reanalyses (JRA), show that the elevation difference between the reanalysis grid box and the GPS station is the primary cause of the PW difference. Secondly, the PW diurnal variations are documented using the 2-hourly GPS PW dataset. The PW diurnal cycle has an annual-mean, peak-to-peak amplitude of 0.66, 0.53 and 1.11 mm for the globe, Northern Hemisphere, and Southern Hemisphere, respectively, with the time of the peak ranging from noon to late evening depending on the season and region. Preliminary analyses suggest that the PW diurnal cycle in Europe is poorly represented in the NNR and JRA products. Several recommendations are made for future improvements of IGS products for climate applications.     

Skyline精细地形场景生成探讨

提出了Skyline精细地形场景生成的解决方案,并针对业务思路、业务流程进行了详细介绍,同时,通过实例说明方案的可行性,为工作开展提供了便利。