Generating GPS satellite fractional cycle bias for ambiguity-fixed precise point positioning

With the development of precise point positioning (PPP), the School of Geodesy and Geomatics (SGG) at Wuhan University is now routinely producing GPS satellite fractional cycle bias (FCB) products with open access for worldwide PPP users to conduct ambiguity-fixed PPP solution. We provide a brief theoretical background of PPP and present the strategies and models to compute the FCB products. The practical realization of the two-step (wide-lane and narrow-lane) FCB estimation scheme is described in detail. With GPS measurements taken in various situations, i.e., static, dynamic, and on low earth orbit (LEO) satellites, the quality of FCB estimation and the effectiveness of PPP ambiguity resolution (AR) are evaluated. The comparison with CNES FCBs indicated that our FCBs had a good consistency with the CNES ones. For wide-lane FCB, almost all the differences of the two products were within ±0.05 cycles. For narrow-lane FCB, 87.8 % of the differences were located between ±0.05 cycles, and 97.4 % of them were located between ±0.075 cycles. The experimental results showed that, compared with conventional ambiguity-float PPP, the averaged position RMS of static PPP can be improved from (3.6, 1.4, 3.6) to (2.0, 1.0, 2.7) centimeters for ambiguity-fixed PPP. The average accuracy improvement in the east, north, and up components reached 44.4, 28.6, and 25.0 %, respectively. A kinematic, ambiguity-fixed PPP test with observation of 80 min achieved a position accuracy of better than 5 cm at the one-sigma level in all three coordinate components. Compared with the results of ambiguity-float, kinematic PPP, the positioning biases of ambiguity-fixed PPP were improved by about 78.2, 20.8, and 65.1 % in east, north, and up. The RMS of LEO PPP test was improved by about 23.0, 37.0, and 43.0 % for GRACE-A and GRACE-B in radial, tangential, and normal directions when AR was applied to the same data set. These results demonstrated that the SGG FCB products can be produced with high quality for users anywhere around the world to carry out ambiguity-fixed PPP solutions.     

Assessing Performance of Tomo-SAR and Backscattering Coefficient for Hemi-Boreal Forest Aboveground Biomass Estimation

Tomo-SAR technique has been used for hemi-boreal forest height and further forest biomass estimation through allometric equation. Backscattering coefficient especially in longer wavelength (L- or P-band) is thought as a useful parameter for hemi-boreal forest biomass retrieval. The aim of this paper is to assess the performance of vertical backscattering power and backscattering coefficient for hemi-boreal forest aboveground biomass (AGB) estimation with airborne P-band data. The test site locates in southern Sweden called Remningstorp test site, and the in-situ forest AGB ranges from 14 t/ha to 245 t/ha at stand level. Multi-baseline P-band Pol-InSAR data in repeat-path mode collected during March and May in 2007 at Remningstorp test site was used. We found that the correlation coefficient (R) between backscattering coefficient of P-band HH polarization and the in-situ forest biomass reached 0.87. The R for P-band VV backscattering power at 5 m is 0.71 and 10 m is 0.72. Backscattering coefficient in HH polarization and vertical backscattering power at 5 m and 10 m were applied to construct a model for hemi-boreal forest AGB estimation by backward step-wise regression and cross-validation approach. The results showed that the estimated forest AGB ranges from 19 to 240 t/ha, and the constructed model obtained a higher R and smaller RMSE, the value of R is 0.91, RMSE is 30.43 t/ha at Remningstorp test site.     

Identifying geospatial services across heterogeneous taxonomies

Geospatial services with different functions are assembled together to solve complex problems. Different taxonomies are developed to categorize these services into classes. As differences in granularity and semantics exist among these taxonomies, the identification of services across different taxonomies has become a challenge. In this paper, an approach to identify geospatial services across heterogeneous taxonomies is proposed. Using formal concept analysis, existing heterogeneous taxonomies are decomposed into semantic factors and their various combinations. With these semantic factors, a super taxonomy is established to integrate the original heterogeneous taxonomies. Finally, with the super taxonomy as a cross-referencing system, geospatial services with classes in original taxonomies are identifiable across taxonomies. Experiments in service registries and a social media-based spatial-temporal analysis project are presented to illustrate the effectiveness of this approach.     

Evaluating urban public facilities of Shenzhen by application of open source data

Abstract

This article applies open source data of public facilities through data mining, not only to evaluate the public facilities from an objective dimension, but also to reflect the sensory opinions of the group factually, eventually realizing the evaluation measurement of urban public facilities. The research takes Shenzhen city as an empirical case and chooses typical public facilities to mine data, resolve address and weight to explore the application of public facilities evaluation under dimension reduction of open source data. The empirical study consists of three parts. First, as the objective evaluation, we estimate the density distribution and per capita of public facility through data mining and address resolution. Second, as the subjective evaluation, we carry on the location analysis to high-score public facility through attention and satisfaction data of Internet evaluation. Finally, as mentioned above, we calculate the weight of objective and subjective evaluation of public facility, eventually formatting the comprehensive evaluation of public facilities.     

测量机器人的关键技术

本文提出了测量机器人概念,重点分析了测量机器人的组成框架及关键技术,聚焦定位与建图、场景感知、路径规划及多机协同等测量机器人前沿研究领域,综述了最新研究进展,并剖析了当前面临的技术难题,简述了测量机器人的发展机遇.     

市县级智慧城市时空信息云平台建设方案研究与应用——以智慧大丰时空信息云平台建设为例

分析了智慧城市时空信息云平台在智慧城市建设中的定位,针对目前国内时空信息云平台建设中普遍存在的一些问题,提出了平台架构云端化、市县运维一体化、数据内容泛在化、更新方式多样化的市县级智慧城市时空信息云平台的建设模式,并在智慧大丰时空云平台建设项目中进行了实践。     

城区重度污染水体遥感识别研究

城市污染水体整治对城市良好水环境具有重大意义。本文基于污染水体形成机理,构建污染水体遥感识别模型,实现了城市污染水体快速、高效、大范围的提取。本文以银川市为研究区,开展银川市污染水体遥感识别,并进行实地验证。验证结果表明污染水体遥感识别精度可达62.96%,共确定银川市污染水体12条,为银川市污染水体整治工作提供参考。此外,本文还分析了影响识别精度的原因,以提高后续污染水体遥感识别精度。由于遥感识别污染水体尚属首次,因此识别精度一般。在今后研究工作中,将会加入其他指标继续研究,以提高精度。     

基于多源遥感数据的森林火灾监测研究

以2019年5月13日黑龙江省佳木斯市同江市洪河国家级自然保护区为研究对象,基于静止气象卫星Himawari-8(H8)和极轨气象卫星MODIS数据对火灾发生经过进行还原,基于高分一号(GF-1)和高分六号(GF-6)数据进行火烧迹地识别.试验结果表明,Himawari-8及MODIS数据都可较好地反演出火灾发生地点,...     

油气管道纵断数据自动提取技术研究

作为管道工程勘测设计中的一项重要工作,纵断面测量内业数据处理具有工作量大、自动化水平低的特点,极大地影响了工作效率.针对此问题,本文设计了油气管道纵断数据提取程序,实现油气管道中线高程点加密、基于机载LiDAR点云数据的纵断数据提取、里程和角度计算等功能,并应用在实际工作当中.该系统具有易操作、高精度、高效率等优势,大...     

多媒体地理信息系统的网络结构分析

数据模型是GIS的灵魂和关键,为了使开发出的GIS尽可能准确地反映地理空间,能够较好地满足GIS用户各方面的需要,而网络拓扑对网络的构成也至关重要,本文分析和总结了早期和近期GIS几种数据模型的优缺点,并在此基础上提出了整体GIS数据模型及网络设计的几种常见模式.