An enhanced approach for surface flow routing over drainage‐constrained triangulated irregular networks

The accuracy and efficiency of the simulations in distributed hydrological models must depend on the proper estimation of flow directions and paths. Numerous studies have been carried out to delineate the drainage patterns based on gridded digital elevation models (DEMs). The triangulated irregular network (TIN) has been increasingly applied in hydrological applications due to the advantages of high storage efficiency and multi‐scale adaptive performance. Much of the previous literature focuses mainly on filling the depressions on gridded DEMs rather than treating the special cases in TIN structures, which has hampered its applications to hydrological models. This study proposes a triangulation‐based solution for the removal of flat areas and pits to enhance the simulation of flow routing on triangulated facet networks. Based on the drainage‐constrained TIN generated from only a gridded DEM by the compound point extraction (CPE) method, the inconsistent situations including flat triangles, V‐shape flat edges and sink nodes are respectively identified and rectified. The optimization algorithm is an iterative process of TIN reconstruction, in which the flat areas are generalized into their center points and the pits are rectified by embedding break lines. To verify the proposed algorithm and investigate the potential for flow routing, flow paths of steepest descent are derived by the vector‐based tracking algorithm based on the optimized TIN. A case study of TIN optimization and flow path tracking was performed on a real‐world DEM. The outcomes indicate that the proposed approach can effectively solve the problem of inconsistencies without a significant loss in accuracy of the terrain model.     

Sea-Level Change Over the China Sea and Its Vicinity Derived from 25-Year T/P Series Altimeter Data

The characteristics of sea-level change in the China Sea and its vicinity are studied by combining TOPEX/Poseidon (T/P), Jason-1, Jason-2, and Jason-3 altimeter data. First, the sea-surface height is computed by using monthly data via collinear adjustment, regional selection, and crossover adjustment. The sea-level anomaly (SLA) from October 1992 to July 2017 is calculated based on the difference that is obtained by the value derived from the inverse distance weighting method to interpolate the CNES_CLS15 model value at a normal point. By analyzing the satellite data at the same time in orbit, three mean bias groups over the China Sea and its vicinity are obtained: the difference between T/P and Jason-1 is ??11.76 cm, the difference between Jason-1 and Jason-2 is 9.6 cm, and the difference between Jason-2 and Jason-3 is 2.42 cm. To establish an SLA series for 25 years in the study area, the SLAs are corrected. Mean rate of sea-level rise of the Bohai Sea, Yellow Sea, East China Sea, and South China Sea of 4.87 mm/a, 2.68 mm/a, 2.88 mm/a, and 4.67 mm/a, respectively, is found by analyzing the series of SLAs.     

恶劣环境下GPS/BDS混合双差模糊度固定性能分析

针对在恶劣观测环境下每个GNSS系统只观测到较少的几颗卫星,采用标准双差模型很难实现整周模糊度固定的问题,该文对GPS/BDS系统间混合双差模型进行研究,利用该模型计算出GPS/BDS系统偏差。在此基础上,利用实验分别对模拟和真实恶劣观测环境下的模糊度固定性能进行分析,实验结果表明,恶劣环境下GPS/BDS系统间混合双差模型表现良好,相较于经典的双差模型可将模糊度固定平均所需时间分别缩短43%和33%,模糊度固定成功率分别提高107%和31%。     

基于三维激光扫描技术的盾构隧道变形分析

为保证地铁隧道建设过程中的安全,对其进行变形监测是必不可少的工作.传统测量方法采用特征点位进行隧道断面监测,存在数据量较少、点位不够全面等缺点,且工作量较大,工作效率低.针对这一问题,本文将三维激光扫描技术应用于盾构隧道监测,利用获取的三维激光点云对盾构隧道进行监测.为验证其可靠性,将其与全站仪数据进行联合分析.实验表...     

结合邻域信息和结构特征的遥感影像变化检测

为提高像元级变化检测方法的精度,提出一种结合邻域信息和结构特征的遥感影像变化检测方法.该方法涵盖邻域相关影像(neighborhood correlation image,NCI)、匹配误差和结构特征3种属性特征.首先,通过邻域相关分析技术获得表示上下文信息的邻域相关影像,利用邻域间像素的互相关性进行模板匹配获得匹配误差.然后,基于方向梯度信息提取能抵抗影像间光谱差异的结构特征.随后将邻域相关影像、匹配误差、结构特征作为决策树的分类属性,获取初始变化检测结果.最后,利用马尔可夫随机场(Markov random field,MRF)对其进行优化,获得最终的二值变化图.本文通过采用两组不同传感器的双时相遥感影像进行试验.结果表明,相较于采用变化向量分析法(change vector analysis,CVA)、单一邻域信息法及邻域信息和纹理特征相结合的方法,本文方法有效提高了变化检测的精度.     

众源矢量数据分块纠正研究

众源矢量数据能够提供丰富的地理信息,但存在几何误差分布不均匀问题.针对众源矢量数据几何误差问题,本文提出一种众源矢量数据分块纠正方法.以遥感影像作为标准数据,通过模板匹配得到遥感影像与众源矢量数据的同名点,根据同名点的几何误差分布对众源矢量数据切分及分块纠正,最后拼接纠正结果实现众源矢量数据的纠正.本文以上海市OpenStreetMap矢量道路网作为实验数据进行分块纠正实验,实验结果表明分块纠正后众源矢量数据几何误差显著降低.     

集成学习和条件随机场的影像招弧角识别

无人机巡检是目前电力部门主推的一种巡检方式,招弧角是一种重要的电网设备、但其呈现细长的几何形状特征,其测量需要优于1 cm空间分辨率的影像.为了从无人机获取的高分辨率影像上提取招弧角,该文提出了基于随机森林、集成学习、全连接条件随机场的无人机影像分类和招弧角提取方法.首先,提取了影像的12个光谱和纹理特征.接着,建立训练样本库,训练了多个独立的随机森林分类器、并形成随机森林集成模型进行影像分类.最后,利用全连接条件随机场优化分类结果.该文采用5000张无人机影像进行了实验.实验表明,该文提出方法的整体分类精度达到85.5％,招弧角识别的正确率为98.3％、完整率为74.3％,表明该方法具有潜在的工程应用价值.     

三维激光扫描技术在船体外形测量中的试验性研究

介绍了三维激光扫描技术的测量原理,进行了21 m长船体外形测量的试验性研究,证明了其在快速、高效获取船体三维数据、提取船体型线方面有着较大的优越性。     

测绘情报工作发展战略思考

本文通过对“十五”期间测绘情报工作的回顾，分析了目前测绘情报研究存在的主要问题，讨论了今后测绘情报工作的发展对策。     

Mining Association Rules in Spatio-Temporal Data: An Analysis of Urban Socioeconomic and Land Cover Change

This research demonstrates the application of association rule mining to spatio‐temporal data. Association rule mining seeks to discover associations among transactions encoded in a database. An association rule takes the form A→B where A (the antecedent) and B (the consequent) are sets of predicates. A spatio‐temporal association rule occurs when there is a spatio‐temporal relationship in the antecedent or consequent of the rule. As a case study, association rule mining is used to explore the spatial and temporal relationships among a set of variables that characterize socioeconomic and land cover change in the Denver, Colorado, USA region from 1970–1990. Geographic Information Systems (GIS)‐based data pre‐processing is used to integrate diverse data sets, extract spatio‐temporal relationships, classify numeric data into ordinal categories, and encode spatio‐temporal relationship data in tabular format for use by conventional (non‐spatio‐temporal) association rule mining software. Multiple level association rule mining is supported by the development of a hierarchical classification scheme (concept hierarchy) for each variable. Further research in spatio‐temporal association rule mining should address issues of data integration, data classification, the representation and calculation of spatial relationships, and strategies for finding ‘interesting’ rules.