“工程测量”实践教学体系的研究与构建

工程测量是港口航道与海岸工程专业技术人员必须掌握的基本技能之一。为解决应用型本科院校工程测量课程的实践教学体系与应用型人才培养目标要求不相适应的问题,从剖析实践教学过程中存在的现实问题出发,结合学校及专业实际情况,以大连海洋大学港口航道与海岸工程专业为例,提出了一套完整的、操作性强、专业特色鲜明的实践教学体系,并取得了一定的教学成果,对于普通高等学校应用型人才的培养具有重要的借鉴意义。     

Small target extraction based on independent component analysis for hyperspectral imagery

A small target detection approach based on independent component analysis for hyperspectral data is put forward. In this algorithm, firstly the fast independent component analysis(FICA) is used to collect target information hided in high-dimensional data and projects them into low-dimensional space. Secondly, the feature images are selected with kurtosis. At last, small targets are extracted with histogram image segmentation which has been labeled by skewness.     

Towards an integral strategy for modelling uncertain geospatial data

This paper endeavours to put the discussion on errors and uncertainties in geographical information systems (GISs) in a more systematic way by examining the strength and weakness of discrete objects and continous fields, the two distinct schools of spatial data modelling. In doing so, it argues that neither discrete objects nor continous fields alone provide objective and complete representations of highly complex geographical phenomena, though there are good reasons for asserting that continuous fields are better suited to modelling spatial dependence, heterogeneity and fuzzines significant in geographical reality than discrete objects. Thus, there seems to be merit in adopting an integrated model incorporating analytical capabilities of fields and generalization functions of objects, for which extended TIN (triangulated irregular network) models along with their duals (Voronoi diagrams) provide a pragmatical solution.     

地图误差对地图匹配质量的影响

高精度的数字地图是正确匹配车辆位置的基础。详细分析了地图数据的地理误差和拓扑误差的误差形式,路网数据模型的常见误差因素和改进策略,最后介绍了不同地图匹配算法对地图质量的敏感性和可行性。根据可能出现的误差对现有数字地图和匹配算法加以改进,弥补了原有数字地图带来的不精确缺陷。跑车实验证明,考虑了数字地图误差影响的匹配算法可以明显提高定位精度,减小车辆定位误差。     

Signal acquisition of Luojia-1A low earth orbit navigation augmentation system with software defined receiver

Low Earth Orbit (LEO) satellite navigation signal can be used as an opportunity signal in the case of a Global Navigation Satellite System (GNSS) outage, or as ...     

工程测量研究现状与发展探讨

总结现代工程测量的主要研究成果,分析该研究领域存在的主要问题,探讨该领域的主要方向和技术增长点.     

基于UML的GIS空间数据管理系统的设计

GIS应用系统设计,是GIS软件开发的一个重要环节,介绍了基于UML的GIS空间数据管理系统的设计,用Rational Rose工具完成了系统的总体设计与详细设计,为该系统的进一步开发与实现提供了技术依据。     

Constructing a Near Real‐time Space‐time Cube to Depict Urban Ambient Air Pollution Scenario

This study adopts a near real‐time space‐time cube approach to portray a dynamic urban air pollution scenario across space and time. Originating from time geography, space‐time cubes provide an approach to integrate spatial and temporal air pollution information into a 3D space. The base of the cube represents the variation of air pollution in a 2D geographical space while the height represents time. This way, the changes of pollution over time can be described by the different component layers of the cube from the base up. The diurnal ambient ozone (O₃) pollution in Houston, Texas is modeled in this study using the space‐time air pollution cube. Two methods, land use regression (LUR) modeling and spatial interpolation, were applied to build the hourly component layers for the air pollution cube. It was found that the LUR modeling performed better than the spatial interpolation in predicting air pollution level. With the availability of real‐time air pollution data, this approach can be extended to produce real‐time air pollution cube is for more accurate air pollution measurement across space and time, which can provide important support to studies in epidemiology, health geography, and environmental regulation.     

基于地下水位变化的城市地面沉降确定性模型研究

依据有限元基本原理和土的渗流理论,推导出基于地下水位变化的确定性模型,并利用实测数据对所研究的模型的效果进行试验分析,结果表明该模型与实际情况吻合良好,模型精度高,且具有较好的预测效果。     

Evaluating Local Non-Stationarity when Considering the Spatial Variation of Large-scale Autocorrelation

Multi‐scale effects of spatial autocorrelation may be present in datasets. Given the importance of detecting local non‐stationarity in many theoretical as well as applied studies, it is necessary to “remove” the impact of large‐scale autocorrelation before common techniques for local pattern analysis are applied. It is proposed in this paper to employ the regionalized range to define spatially varying sub‐regions within which the impact of large‐scale autocorrelation is minimized and the local patterns can be investigated. A case study is conducted on crime data to detect crime hot spots and cold spots in San Antonio, Texas. The results confirm the necessity of treating the non‐stationarity of large‐scale spatial autocorrelation prior to any action aiming at detecting local autocorrelation.