利用 LiDAR 点云提取有地形约束的光滑海岸线

针对传统海岸线提取算法误差大、在地形突变区域形变大的缺点,提出了一种基于离散 LiDAR 点云提取有地形约束海岸线的方法.首先,通过离散点云构建约束三角网,减少内插规则格网的误差并且保证海岸线不穿越地形结构;其次,进行顾及地形结构的点云高程修正,在数据源上缓解海岸线的平滑问题;最后采取二次多项式法消除毛刺,利用动态阈值张力样条函数内插生成光滑海岸线.     

基于等高线构建TIN模型的平三角形修正算法

设计了一种平三角形修正算法来修正TIN模型中可能出现的平三角形区域.该算法通过对由平三角形组成的区域进行分类,并针对不同的平区域采用交换边、增加点甚至不处理的修正方法,同时对由于等高线数据错误产生的一些特殊情况进行了分析处理.实验结果表明,该算法能够去除约束型狄洛尼三角网中所有应修正的平三角形,并生成对地形描述更为精确的三角网.     

利用自动匹配与三角剖分进行遥感图像几何精校正

在研究传统几何精校正方法的基础上,提出了一种高精度的基于自动同名点匹配和三角剖分技术的几何精校正方法,该方法是通过基准底图对待校正图像进行几何精校正的。首先利用FAST (Features from Accelerated Segment Test)算子在基准底图上快速提取均匀分布的候选特征点,通过图像自身携带的地理定位信息确定初始同名点对;经平移误差消除、互相关双向匹配、RANSAC(Random Sample Consensus)粗差剔除、二元三点插值等步骤获取稳定可靠的亚像元级同名点对;最后根据亚像元级同名点对构建Delaunay三角网进行图像变换和重采样处理。以Landsat卫星ETM为基准底图对环境卫星CCD数据进行几何精校正试验,本算法几何精校正精度较传统的方法得到了很大提高。     

Delaunay三角剖分算法在地震烈度速报中的应用——以天津市强震台网为例

利用计算图形学中的Delaunay三角剖分算法及其对偶结构的Voronoi图算法,构建天津市强震台网的Delaunay三角网及Voronoi图.结果表明,Voronoi图可以较直观地显示台网的布局疏密,并为等震曲线绘制的合理性提供判断依据.     

基于Delaunay三角关系的面状要素合并方法

详细介绍了一种基于Delaunay三角关系的面状要素合并的新方法，并举例阐述了该方法在居民地、植被和土质等面状要素的制图综合中的应用。     

Sensitivity of a stochastic land-cover change model to pixel versus polygonal land units

Land-use/cover change (LUCC) projections can be generated by a variety of land-cover change models (LCMs) and applied to a range of ecological and environmental studies. Most existing spatially explicit LCMs represent land use or cover using either pixel or polygon/patch spatial units. However, the effects of the choice to use pixel versus polygonal land units on the outputs from any given model have not yet been systematically assessed. We evaluated the impacts of alternative land units on the performance of a LCM. A stochastic LCM based on a geostatistical algorithm was developed and applied using both pixel and polygons, which were derived from parcel maps. Nine possible parcel-change scenarios were generated to evaluate the effects of geometric change in management boundaries. The approach was tested through the simulation of multiple land-cover transitions in Medina County, Ohio, between 1992 and 2011. Performance of the simulations was assessed using a metric for the accuracy of spatial allocations (figure of merit (FoM)) and several landscape pattern metrics describing the shapes and sizes of resulting land-cover patches. Results support the notion that there is a clear trade-off between pixel and polygon land units: using polygon boundaries is helpful in obtaining more realistic spatial patterns, but at the cost of location accuracy. Significant differences were found among different parcel-change scenarios on both location accuracy and spatial patterns, with the primary effects being dependent on the type of land-cover transition and the resolution at which validation was assessed.     

Scale-specific automated line simplification by vertex clustering on a hexagonal tessellation

A new method of cartographic line simplification is presented. Regular hexagonal tessellations are used to sample lines for simplification, where hexagon width, reflecting sampling fidelity, is varied in proportion to target scale and drawing resolution. Tesserae constitute loci at which new sets of vertices are defined by vertex clustering quantization, and these vertices are used to compose simplified lines retaining only visually resolvable detail at target scale. Hexagon scaling is informed by the Nyquist–Shannon sampling theorem. The hexagonal quantization algorithm is also compared to an implementation of the Li–Openshaw raster-vector algorithm, which undertakes a similar process using square raster cells. Lines produced by either algorithm using like tessera widths are compared for fidelity to the original line in two ways: Hausdorff distances to the original lines are statistically analyzed, and simplified lines are presented against input lines for visual inspection. Results show that hexagonal quantization offers advantages over square tessellations for vertex clustering line simplification in that simplified lines are significantly less displaced from input lines. Visual inspection suggests lines produced by hexagonal quantization retain informative geographical shapes for greater differences in scale than do those produced by quantization in square cells. This study yields a scale-specific cartographic line simplification algorithm, following Li and Openshaw's natural principle, which is readily applicable to cartographic linework. Open-source Java code implementing the hexagonal quantization algorithm is available online.     

线对象的惯性函数描述与三角剖分方法

现有线对象三角剖分算法没有顾及线对象的整体结构特征,导致三角剖分质量不高,难以支持大数据量的矢量制图和高更新率的动态制图。本文提出线对象的惯性函数,设计了一种线对象的单调分解与三角剖分方法。惯性函数的单调递增区间作为线对象的渐变区间,连续剖分为一个优化的三角形条带;惯性函数的单调递减区间作为线对象的突变区间,离散剖分为一个优化的三角形扇。试验表明:本文方法三角剖分的顶点、三角形、图元的个数均优于基于顶点和基于线段的三角剖分方法,能够显著提升线对象的绘制效率。本文方法也适用于封闭线型、宽度渐变线型与光滑线型。     

Delaunay三角形法实现面状要素自动注记初探

地图自动注记是自动制图技术的重要环节之一。本文阐述了根据Delaunay三角形的逐点自动生成算法原理进行面状要素自动注记的方法。重点论述了图斑多边形的预处理算法和求取注记定位线的算法。在与长对角线法和水平切割中点线法相比后证明,这种算法不但能够处理所有常规形状的多边形,而且能够适应诸如凹形多边形等具有特殊形状的多边形。     

基于PDA环境的等值线自动绘制

等值线的绘制在自然科学领域上的应用十分广泛.本文介绍了一种在嵌入式终端PDA上绘制等值线的方法,该方法首先用逐点插入法生成Delaunay三角网,然后基于三角网追踪等值点,最后以MapX Mobile控件为图形平台,在Embedded Visual C 4.0环境下编程绘制等值线图,实现等值线图的放大、缩小、漫游、属性查询等GIS功能.继而以离散高程点为实验数据基于PDA环境绘制了等高线图,验证了上述方法的可行性.