Volume-preserving interpolation of a smooth surface from polygon-related data

 The interpolation of continuous surfaces from discrete points is supported by most GIS software packages. Some packages provide additional options for the interpolation from 3D line objects, for example surface-specific lines, or contour lines digitized from topographic maps. Demographic, social and economic data can also be used to construct and display smooth surfaces. The variables are usually published as sums for polygonal units, such as the number of inhabitants in communities or counties. In the case of point and line objects the geometric properties have to be maintained in the interpolated surface. For polygon-based data the geometric properties of the polygon boundary and the volume should be preserved, avoiding redistribution of parts of the volume to neighboring units during interpolation. The pycnophylactic interpolation method computes a continuous surface from polygon-based data and simultaneously enforces volume preservation in the polygons. The original procedure using a regular grid is extended to surface representations based on an irregular triangular network (TIN). Received: 5 October 2000 / Accepted: 20 December 2000     

地面成像光谱数据的田间杂草识别

地面成像光谱数据兼具高光谱分辨率与高空间分辨率,在田间杂草识别中具有很好的应用前景。目前基于机器视觉的杂草识别方法以形状特征为主,当作物杂草形态相似时识别的困难和利用高光谱特征以像元为单元识别时效率较低,不利于实时自动化除草,因此,本文提出一种综合面向对象与高光谱特征匹配的杂草识别方法,在对作物杂草对象样本的形状特征和光谱曲线提取分析的基础上,建立基于形状特征规则与光谱角匹配的植物对象识别决策树,用于识别实验田中的作物杂草对象。实验结果表明,当场景中某些不同种类植物对象的形态相似时,基于形状特征规则与光谱角匹配的杂草识别方法可借助高光谱特征精细区分植物对象的种类,且在形状特征规则约束下使用高光谱特征匹配法识别植物对象,可克服"同物异谱"和"同谱异物"现象带来的不确定性,该方法识别精度可优于仅使用光谱角匹配法的情况,并优于使用颜色和形状分析技术的情况。     

建筑物多边形高精度识别的傅里叶形状描述子神经网络方法EI北大核心CSCD

形状识别是地图空间认知的重要内容之一,结合有效的形状特征向量提取方法和空间认知试验的神经网络方法是提高形状识别的有效途径。本文构建了一种融合了圆形度、偏心率和矩形度等宏观形状特征参量的傅里叶形状描述子作为形状特征向量的神经网络建筑多边形状识别器。首先,利用傅里叶变换和计算几何方法分别提取建筑多边形的傅里叶形状描述子及圆形度、偏心率、矩形度参量,并组成形状特征向量。然后,通过样本数据的训练实现了建筑多边形与形状模板之间匹配的神经网络识别器。结果表明,本文方法相较于以往的方法大幅度提高了精度(达到98.7%),而且特征提取算法不受多边形点数不一致的限制。通过对武汉、郑州两大城市的真实建筑物数据进行形状识别,证实该方法具有较好的识别效果。     

克服双重约束的面目标位置聚类方法

面目标的聚集模式识别是空间聚类研究的重要方向之一,但因多边形几何信息和空间障碍阻隔的双重约束,目标的位置相似性难以快速而准确地计算。扩展点目标多尺度聚类方法,通过构建面目标的强度函数计算目标与邻近目标的位置聚集程度,提出了有效作用于双重约束下的面目标位置聚类法,并以判断相邻尺度下同一面目标类的强度函数阈值相等作为算法的收敛条件。经试验分析与比较发现,算法无须自定义参数,能够识别密度不均、任意形状分布,以及"桥"链接的面目标集群,同时能够准确判断障碍约束对面目标簇的阻隔和划分。     

Geomasking sensitive health data and privacy protection: an evaluation using an E911 database

Geomasking is used to provide privacy protection for individual address information while maintaining spatial resolution for mapping purposes. Donut geomasking and other random perturbation geomasking algorithms rely on the assumption of a homogeneously distributed population to calculate displacement distances, leading to possible under-protection of individuals when this condition is not met. Using household data from 2007, we evaluated the performance of donut geomasking in Orange County, North Carolina. We calculated the estimated k-anonymity for every household based on the assumption of uniform household distribution. We then determined the actual k-anonymity by revealing household locations contained in the county E911 database. Census block groups in mixed-use areas with high population distribution heterogeneity were the most likely to have privacy protection below selected criteria. For heterogeneous populations, we suggest tripling the minimum displacement area in the donut to protect privacy with a less than 1% error rate.     

利用等距同构建立多尺度空间实体相似性度量模型

从度量几何学的观点，建立多尺度空间实体等距同构模型。将多尺度空间实体分别看作刚性图形和弹性图形，利用等距同构不变性的概念，构建多尺度空间实体几何相似性图形距离和拓扑相似性图形距离。通过统一几何和拓扑相似性图形距离，构成一个二元集值距离，作为多尺度空间实体相似性的评价指标。通过对不同复杂性的面状和线状空间实体多尺度表达图形的几何和拓扑相似性度量实验表明，该方法能同时顾及多尺度空间实体几何和拓扑结构的改变，且符合空间实体的多尺度抽象规律。     

Combined object-based classification and manual interpretation–synergies for a quantitative assessment of parcels and biotopes

Recent technical advances in remote sensing data capture and spatial resolution lead to a widening gap between increasing data availability on the one hand and insufficient methodology for semi-automated image data processing and interpretation on the other hand. At the interface of GIS and remote sensing, object-based image analysis methodologies are one possible approach to close this gap. With this, methods from either side are integrated to use both the capabilities of information extraction from image data and the power to perform spatial analysis on derived polygon data. However, dealing with image objects from various sources and in different scales implies combining data with inconsistent boundaries. A landscape interpretation support tool (LIST) is introduced which seeks to investigate and quantify spatial relationships among image objects stemming from different sources by using the concept of spatial coincidence. Moreover, considering different categories of object fate, LIST enables a change categorization for each polygon of a time series of classifications. The application of LIST is illustrated by two case-studies, using Landsat TM and ETM as well as CIR aerial photographs: the first showing how the tool is used to perform object quantification and change analysis; the latter demonstrating how superior aggregation capabilities of the human brain can be combined with the fine spatial segmentation and classification. Possible fields of application are identified and limitations of the approach are discussed.     

基于ArcIMS的农业立体污染空间信息网

针对农业立体污染及时发布和数据共享的需求,运用ArcIMS建立了农业立体污染空间信息网,以达到农业立体污染防治的现代化、信息化、规范化和高效化。     

Chain-based polyline tessellation algorithm for cartographic rendering

ABSTRACT

Although the extrusion of 1D polylines into a 2D polygon and the tessellation of the polygon into primitives has been performed in the field of computer graphics, the efficient, robust, and high-quality tessellation of thick polylines that supports various cartographic styles for polyline rendering remains a practical challenge. We examined and compared existing vertex-, segment-, and polygon-based algorithms, and present a chain-based tessellation algorithm for cartographic rendering: points in the polyline are classified into abrupt and smooth points according to their point spacing, angle and thickness. The polylines are then divided into abrupt and smooth chains by clustering points that are adjacent and of the same type. An optimal algorithm is also presented to continuously tessellate the smooth chains into minimum geometric primitives and efficiently tessellate the abrupt chains into geometric primitives. We implemented the proposed algorithm and present the results of robustness, efficiency, quality, and cartographic styling tests conducted on real-world polylines. The results indicate that this approach has substantial advantages when considering all four requirements (robustness, efficiency, quality, and the support for various cartographic styles).     

Multi‐Scale Qualitative Location: A Topology‐Based Model

Qualitative locations describe spatial objects by relating the spatial objects to a frame of reference (e.g. a regional partition in this study) with qualitative relations. Existing models only formalize spatial objects, frames of reference, and their relations at one scale, thus limiting their applicability in representing location changes of spatial objects across scales. A topology‐based, multi‐scale qualitative location model is proposed to represent the associations of multiple representations of the same objects with respect to the frames of reference at different levels. Multi‐scale regional partitions are first presented to be the frames of reference at multiple levels of scale. Multi‐scale locations are then formalized to relate multiple representations of the same objects to the multiple frames of reference by topological relations. Since spatial objects, frames of reference, and topological relations in qualitative locations are scale dependent, scale transformation approaches are presented to derive possible coarse locations from detailed locations by incorporating polygon merging, polygon‐to‐line and polygon‐to‐point operators.     

Dealing with spatial relations for spatial objects with randomness in GIS

To design retrieval algorithm of spatial relations for spatial objects with randomness in GIS, this paper builds up the membership functions based on set theory idea, used for determination of topological spatial relations between random objects, such as between point and point, point and line or polygon, which provides theoretical basis for retrieving spatial relations between certain and random objects. Finally, this paper interprets detailed methods and steps of realizing them by means of some simple examples under the GIS's environment.     

DEALING WITH SPATIAL RELATIONS FOR SPATIAL OBJECTS WITH RANDOMNESS IN GIS

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Line segment confidence region-based string matching method for map conflation

In this paper, a method to detect corresponding point pairs between polygon object pairs with a string matching method based on a confidence region model of a line segment is proposed. The optimal point edit sequence to convert the contour of a target object into that of a reference object was found by the string matching method which minimizes its total error cost, and the corresponding point pairs were derived from the edit sequence. Because a significant amount of apparent positional discrepancies between corresponding objects are caused by spatial uncertainty and their confidence region models of line segments are therefore used in the above matching process, the proposed method obtained a high F-measure for finding matching pairs. We applied this method for built-up area polygon objects in a cadastral map and a topographical map. Regardless of their different mapping and representation rules and spatial uncertainties, the proposed method with a confidence level at 0.95 showed a matching result with an F-measure of 0.894.     

同名边界点的面状居民地要素匹配

针对空间数据集成与地图增量更新过程中的面实体匹配环节,该文提出利用同名边界点集进行面状居民地要素匹配的方法。该方法从边界点的相似性考虑面状居民地要素的相似性,通过计算候选匹配要素上边界点在位置、转角、关联边等方面的一致性,把面实体相似性的比较转换为同名要素边界点集相似性的比较,简化了面状居民地实体匹配的复杂度。在面状居民地要素的匹配过程中,该文方法可以处理一对一、一对多和多对一的匹配关系。实验证明,该方法在匹配面状居民地要素时,准确率可以达到98%。     

一种用于空间数据整合的建筑物面实体对齐方法

提出了一种用于空间数据整合的建筑物面实体对齐方法,可用来改善空间数据的位置精度。首先,采用基于最小外接矩形（minimum bounding rectangle,MBR）组合优化算法的匹配方法识别整合数据之间的同名实体;然后,提出基于几何相似性的成对约束谱匹配算法检测1:1、1:N和M:N同名实体之间的共轭点对;针对1:N和M:N匹配中不可避免存在弱对应点对和错误对应点对的问题,提出基于IGG1权重的最小二乘法来有效对齐同名实体。将所提出的方法应用于对齐较高位置精度的基础测绘地图数据和较低位置精度的谷歌地图数据中,结果表明,该方法不仅可检测存在复杂轮廓对应的1:N和M:N同名实体的共轭点对,而且可实现它们之间的有效对齐,使同名实体的位置信息差异最小化。     

基于空间行为的面向对象空间数据模型

本文根据面向对象空间数据模型的相关概念和特点,将地理空间中的空间行为进行建模后纳入面向对象空间数据模型的框架中。面向对象空间数据模型由数据模型和空间行为模型两个部分组成:数据模型包括空间特征数据和属性特征数据;同时将空间行为模型分为两大类,即静态空间行为模型(地理目标间关系)和动态行为模型(地理目标行为)两部分。在此框架提出的基础上,本文利用二进制、XML流等格式文件对该空间数据模型进行了整合和组织。     

基于特征边重构的建筑物化简方法

针对轮廓模糊建筑物多边形的化简问题,提出一种基于特征边重构的建筑物化简方法。该方法定义了建筑物的主方向和控制其整体结构的特征边,以保持建筑物的规则形态。首先利用统计加权方法计算建筑物的主方向,基于主方向对建筑物执行直角化操作。然后按照特征边的定义检测直角化建筑物的特征边,将特征边组合并抽象出几种局部结构,建立重组规则。最后通过判别特征边组合的空间关系,选择合适的结构重组规则来化简建筑物。结合真实数据进行多组试验,结果表明该方法有效还原了建筑物的直角特征,面积和形状保持良好,适用性强。     

不规则体体积计算三维激光点云切片法

体积参数是空间体对象形态分析的基本内容,难点是不规则体的体积计算。本文提出的点云"切片法",快捷准确地解决了由三维激光扫描空间体对象所得点云体的体积计算难题。该法先将三维激光扫描空间体对象所得点云按特定方向顺序进行等间距的切片处理,得到与点云体相对应的、离散的系列点云切片;再依切割次序逐一搜索点云切片外轮廓多边形,并计算多边形(即点云切片)的面积;最后,利用切片面积和相邻切片间距求解点云段块体积,并求和得到整体点云体(即所扫描空间体对象)的体积。算例计算结果与分析表明,基于切片的不规则体的三维激光扫描点云的体积计算方法正确、简洁、可靠、高效、可控,可以解决不规则体的体积计算问题。     

空间物体分类及空间物体构造

空间物体描述是ＧＩＳ的基本任务之一，而空间物体的分类是空间物体描述的基础。理想的空间物体分类模型不但应具有完备描述（构造）各种空间物体的能力，而且应能够揭示基本的空间关系，有助于空间分析的规范化系统化。本文在分析空间概念模型和现有的几种空间物体分类模型的基础上，提出了空间物体分类的基本原则，给出了新的空间物体分类模型：简单点、复合点、简单线、有向简单线、复合线、有向复合线、多边形，并说明了以这类基本物体类型构造复杂物体的一般性方法。     

A Tool Assessing Optimal Multi-Scale Image Segmentation

Image segmentation to create representative objects by region growing image segmentation techniques such as multi resolution segmentation (MRS) is mostly done through interactive selection of scale parameters and is still a subject of great research interest in object-based image analysis. In this study, we developed an optimum scale parameter selector (OSPS) tool for objective determination of multiple optimal scales in an image by MRS using eCognition software. The ready to use OSPS tool consists of three modules and determines optimum scales in an image by combining intrasegment variance and intersegment spatial autocorrelation. The tool was tested using WorldView-2 and Resourcesat-2 LISS-IV Mx images having different spectral and spatial resolutions in two areas to find optimal objects for ground features such as water bodies, trees, buildings, road, agricultural fields and landslides. Quality of the objects created for these features using scale parameters obtained from the OSPS tool was evaluated quantitatively using segmentation goodness metrics. Results show that OSPS tool is able determine optimum scale parameters for creation of representative objects from high resolution satellite images by MRS method.