制图综合中道路与建筑物的移位研究

针对地图中道路与建筑物的具体冲突问题,分析了移位的约束条件,阐述移位算法的发展历史,并对其算法进行了分析与研究,最后设计了解决道路与建筑物具体冲突问题的移位方案。     

一种改进的点群移位算法及其应用

比例射线移位算法处理冲突目标群,能够较好地保持移位后目标群的空间分布模式,常被应用于点群移位。本文在对已有算法的研究基础上,对其进行改进：首先考虑了存在线状要素时点群移位的新情况;其次,提出了可变参数的衰减函数控制模型。最后本文通过实验,演示了算法的有效性。     

基于Snakes算法的道路要素移位软件模块

采用C#编程语言和ArcGIS Engine二次开发组件,设计并实现了一种基于Snakes算法的道路要素移位软件模块。介绍了Snakes移位算法的基本思想,从软件设计和开发的角度阐述了用于道路要素移位的Snakes算法的数据模型、逻辑结构和基本流程,最后给出了该软件模块的实现效果。     

比例射线移位算法的改进及其应用

点状要素群移位的比例射线算法能够较好地保持移位后点群的空间分布模式。文中从农村居民地群移位的实际要求出发,对比例射线移位算法进行了改进:首先考虑居民地面积的不同大小对移位的影响;其次,设计比例射线移位的迭代方法;最后对于非常邻近的居民地群的移位,采用"微小"移位方法。通过实验验所改进的算法是有效的。     

多层次移位原则的道路与建筑物空间冲突处理

本文在分析传统道路与建筑物空间冲突算法的基础上,借鉴其优点,从保持建筑物间的整体空间布局特征,以及模拟人工移位的处理方法角度出发,提出根据区域密集程度的不同,划分为稀疏区、密集区、高密集区三个等级区域,并制定相应的多层次移位处理原则,然后,根据道路与建筑物的邻近程度,将建筑物分为多等级的移位层,对移位层内的冲突进一步细分;据此,依据移位层的邻近程度,将多层次处理原则贯穿于要素冲突外力的计算、外力的聚合以及其移位算法的确定中,分别对道路与建筑物的冲突、建筑物之间的冲突分别进行处理。     

小比例尺地图居民地综合缩编更新

居民地是地形图的重要要素。本文首先对小比例尺居民地的数据更新方法进行了研究,总结了适用于不同分布模式居民地的合并、化简、移位等基本综合操作,重点分析各类操作算法的核心思想,并提出小比例尺居民地相关综合算法,给出了一套可行的居民地综合策略。研究成果可应川于小比例尺地形数掂的多尺度综合更新。     

面向等高线与河流冲突处理的多约束移位方法

本文针对等高线与河流的不一致性问题,以移位等高线匹配河流为出发点,提出一种对每个特征点动态确定仿射变换模型进行移位的方法。该方法综合考虑移位角度比例、地形特征点相对位置、局部形态的保持和变换等因素,对各特征点实时计算其位移的角度、位置和缩放变化等约束建立其移位模型。实验结果表明,本文提出的方法能够较好地实现等高线到河流的一致性改正,可有效解决等高线与河流数据的空间匹配问题。     

地图自动综合中Beams移位算法的实现与改进

地图自动综合中,基于Beams模型的全局最优化移位算法通过借鉴材料力学中杆件结构的移位和变形,模拟地图上空间目标(群)在移位操作中的传递性和衰减性,从而较好地保持地图目标(群)的形状、空间关系和分布模式。然而,目前对该算法实现细节的介绍仍然较少,也没有可操作的参数(弹性模量、横截面积和惯性力矩)设置方法。针对此种情况,对算法进行了实现与改进。首先,介绍了算法的基本数学模型与有限元求解方法;然后,从算法实现的角度,详细研究了Beams模型刚度矩阵和外力向量的计算和聚合等关键问题;最后,在降低参数复杂性的前提下,提出了一种自适应参数设置方法来改进算法。为了验证算法的可行性和适用性,在Delaunay三角网的支持下,分别对道路网和建筑物群进行移位,结果表明改进后的算法可较好地应用于地图上线状目标(群)和离散面状目标群的移位。     

线图形简化与移位算子的协同方法

在地图综合过程中,线的图形简化和移位算子通常是分别执行的,图形简化和移位有时都会产生新的空间冲突。本文试图把这两种算子进行协同,避免在地图综合过程中进行空间冲突的多次探测,提高地图综合数据处理的效率。本文通过把线图形简化转换为线上的点移位,并构建邻近地图目标之间的移位传播路径,在考虑空间上下文关系和地图感受规则的前提下,使移位过程能考虑到线图形简化,并尽量保持有关地图目标的空间特征。最后,以道路和其周边的建筑物群为例,验证了该算法的有效性和可行性。     

移位安全区约束下的建筑物群移位免疫遗传算法

对于采用启发式或群智能搜索的组合最优化移位算法,地图要素空间关系与空间分布特征的保持是一个难题.本文基于免疫遗传算法提出一种移位安全区约束下的建筑物群最优化移位方法.该方法将建筑物群的移位问题定义为一个多目标最优化问题,然后采用免疫遗传算法搜索最优解.为了尽量保持建筑物群的空间关系和总体分布特征,避免出现拓扑错误,采用Voronoi图和缓冲区构建每个建筑物的移位安全区,以限定建筑物的移位范围;同时,采用建筑物群组整体移位策略,保持局部空间分布模式.最后,以北京市某部分街区建筑物群的移位为例验证改进算法的有效性,结果表明所实现算法能够在解决邻近冲突的同时,较好地保持地图目标间的空间关系和空间分布特征.     

数字海图线性特征的识别、量测与综合

图形特征的变化是无究的,只是依据与位移、夸大、化简等相似的综合方法,而不包含图形特征的识别与量测,数字海图的自动综合是无法实现的。只有识别、量测和综合方法的组合,才是数字海图综合概念的全部体现。因而,本文模拟人的综合方法的同时, 点模拟了人的图形特征的识别方式,同时,经过Ｄｏｕｇｌａｓ二叉树方法的引入,给出了图形特征的识别与量测函数,实现了数字海图红性特征的自动综合。     

基于改进Snake模型的道路网空间冲突处理

在对Snake模型研究分析的基础上,结合地图制图的需求,从3个方面对Snake模型进行改进：首先建立Snake模型中参数与道路曲线形态特征的关系,以更好地保持移位前后道路形态的相似性;其次控制Snake模型中外力的传播范围,以尽量保持要素位置的准确性;最后,通过道路交叉点的权重属性控制,保证移位后各交叉点的连通性以及道路的整体拓扑关系不发生变化。在此基础上,提出道路网移位整体思路,并采用改进的Snake模型对其进行移位,解决空间冲突。     

预处理共轭梯度法解病态问题及在GPS中的应用

介绍测量数据处理中病态问题的岭估计思想及确定岭参数的方法。引入预处理共轭梯度法求解病态法方程组,说明算法的基本原理和它能有效减弱病态性的原因。用一个GPS差分动态定位的实例,通过与不同岭估计方法的对比分析,验证该方法是一个有效的数值迭代算法。     

顾及格式塔原则的建筑物群移位实数编码遗传算法

在建筑物群的综合过程中,建筑物群的移位是一个非常重要的任务。在分析已有算法的基础上,探讨了建筑物群移位的一个新的自适应实数编码遗传算法,在该算法中,考虑了建筑物与街道之间的空间关系和建筑物群排列在图形表达上的格式塔原则,在适应度函数的设计上也考虑了多重因素的影响,使得移位结果更符合地图制图规范和地图感受规律。实验结果表明,该算法在移位空间充足时能精确收敛到最优解,移位效果良好。     

地图目标移位的空间关系维护

在分析有限元方法处理地图目标移位问题的基本思路和地图目标移位产生的空间关系冲突传播特征的基础上 ,提出了一个利用空间推理和有限元分析相结合的方法维护地图目标空间关系的算法     

On the theoretical link between LLL-reduction and Lambda-decorrelation

The LLL algorithm, introduced by Lenstra et al. (Math Ann 261:515–534, 1982), plays a key role in many fields of applied mathematics. In particular, it is used as an effective numerical tool for preconditioning the integer least-squares problems arising in high-precision geodetic positioning and Global Navigation Satellite Systems (GNSS). In 1992, Teunissen developed a method for solving these nearest-lattice point (NLP) problems. This method is referred to as Lambda (for Least-squares AMBiguity Decorrelation Adjustment). The preconditioning stage of Lambda corresponds to its decorrelation algorithm. From an epistemological point of view, the latter was devised through an innovative statistical approach completely independent of the LLL algorithm. Recent papers pointed out some similarities between the LLL algorithm and the Lambda-decorrelation algorithm. We try to clarify this point in the paper. We first introduce a parameter measuring the orthogonality defect of the integer basis in which the NLP problem is solved, the LLL-reduced basis of the LLL algorithm, or the $\Lambda $ -basis of the Lambda method. With regard to this problem, the potential qualities of these bases can then be compared. The $\Lambda $ -basis is built by working at the level of the variance-covariance matrix of the float solution, while the LLL-reduced basis is built by working at the level of its inverse. As a general rule, the orthogonality defect of the $\Lambda $ -basis is greater than that of the corresponding LLL-reduced basis; these bases are however very close to one another. To specify this tight relationship, we present a method that provides the dual LLL-reduced basis of a given $\Lambda $ -basis. As a consequence of this basic link, all the recent developments made on the LLL algorithm can be applied to the Lambda-decorrelation algorithm. This point is illustrated in a concrete manner: we present a parallel $\Lambda $ -type decorrelation algorithm derived from the parallel LLL algorithm of Luo and Qiao (Proceedings of the fourth international C $^*$ conference on computer science and software engineering. ACM Int Conf P Series. ACM Press, pp 93–101, 2012).     

MELISSA,a new class of ground based InSAR system. An example of application in support to the Costa Concordia emergency

Ground Based Interferometric Synthetic Aperture Radars (GB-InSAR) have proved to be fully operational tools for the monitoring of ground displacement and structural deformation. The main limiting factor of the existing systems is the time to acquire a single image, typically ranging from few seconds to few minutes. This paper presents the validation and the operational use of a new system – Mimo Enhanced LInear Short SAr (MELISSA), belonging to a new class of GB-InSAR devices. MELISSA is based on a Multiple Input Multiple Output Synthetic Aperture Radar (MIMO SAR) and is capable of acquiring and processing image data at an unprecedented high speed. A configuration of the system acquiring a 0.96 m synthetic aperture and 260 m swath image in 2.6 ms was tested in a controlled environment. The results prove its ability to reach an image refreshing time smaller than 4 ms and Line-Of-Sight (LOS) displacement accuracies better than 10 μm. Thus, MELISSA was able to help with the monitoring of the Costa Concordia ship movements in the immediate aftermath of grounding during both the rescue operations and subsequent wreckage removal. The accurate displacement measurements of specific points of the structure are presented in a global interferogram sequence (2-D displacement maps of the whole structure). The collected data contributed to a precise wreck deformation reconstruction. MELISSA’s ability to update the information almost every second has proven to be extremely reassuring as early warning on potentially catastrophic movements.     

A spatial contextual immune genetic algorithm to building cartographic displacement

In map generalization, displacement is the most frequently used operator to reduce the proximity conflicts caused by reducing scales or other generalization operations. Building displacement can be formalized as a combinatorial optimization problem, and a heuristic or intelligent search algorithm can be borrowed to obtain the solution. In this way, we can explicitly resolve minimum distance conflicts and control positional accuracy during the displacement. However, maintaining spatial relations and patterns of buildings can be challenging. To address spatial conflicts as well as preserve the significant spatial relations and patterns of buildings, we propose a new spatial contextual displacement algorithm based on an immune genetic algorithm. To preserve important spatial relations and global patterns of map objects and avoid topology errors, displacement safety zones are constructed by overlapping the Voronoi tessellation and buffer areas of the buildings. Additionally, a strategy to shift the buildings in a building group synchronously is used to maintain local building patterns. To demonstrate the effectiveness of our algorithm, two data sets with different building densities were tested. The results indicate that the new algorithm has obvious advantages in preventing topology errors and preserving spatial relations and patterns.     

Building Displacement Based on the Topological Structure

Map data at smaller scales than their source can result in spatial conflict, whereby map symbols become too close, or overlaid. Server map generalisation operators may be applied to solve this problem, including displacement. In this paper, we show how an optimisation algorithm, the snake algorithm, was used to displace multiple objects in order to resolve spatial conflicts and maintain important spatial relationships between objects during displacement. Two principles based on the snake algorithm are proposed in this paper. First, the truss structure mirroring spatial proximity relationships between buildings and between building and road is formed based on the weighted proximity graph derived from constrained Delaunay triangulations (CDT) in each map partition. In the weighted proximity graph, each connecting line is determined as a snake and as an element unit to assemble the global stiffness matrix in snake algorithm. Second, a buffer method that calculates force between a building and a road (or other linear features) or between pair of buildings is adopted in the snake algorithm. This avoids the imbalance phenomenon caused by different force calculation methods during the displacement. The feasibility of the approach is demonstrated in obtaining real geographic data. Finally, the results are cartographically usable and in particular, the spatial relationships between objects are preserved.