Detecting Duplicates in Geoinformatics: from Intervals and Fuzzy Numbers to General Multi-D Uncertainty

S. Starks, L. Longpré, R. Araiza, V. Kreinovich, Hung T. Nguyen
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Abstract

Geospatial databases generally consist of measurements related to points (or pixels in the case of raster data), lines, and polygons. In recent years, the size and complexity of these databases have increased significantly and they often contain duplicate records, i.e., two or more close records representing the same measurement result. In this paper, we address the problem of detecting duplicates in a database consisting of point measurements. As a test case, we use a database of measurements of anomalies in the Earth's gravity field that we have compiled. In our previous papers (2003,2004), we have proposed a new fast (O(n ldr log(n))) duplication deletion algorithm for the case when closeness of two points (x1,y1) and (x2,y2) is described as closeness of both coordinates. In this paper, we extend this algorithm to the case when closeness is described by an arbitrary metric. Both algorithms have been successfully applied to gravity databases.
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地理信息学中的重复检测:从区间和模糊数到一般多维不确定性
地理空间数据库通常由与点(或光栅数据中的像素)、线和多边形相关的测量值组成。近年来,这些数据库的规模和复杂性显著增加,它们经常包含重复记录,即代表相同测量结果的两个或多个接近记录。在本文中,我们解决了在由点测量组成的数据库中检测重复的问题。作为一个测试案例,我们使用了一个我们编译的地球重力场异常测量数据数据库。在我们之前的论文(2003,2004)中,我们提出了一种新的快速(O(n ldr log(n)))重复删除算法,用于将两点(x1,y1)和(x2,y2)的接近度描述为两个坐标的接近度。在本文中,我们将该算法推广到用任意度量来描述接近度的情况。这两种算法都成功地应用于重力数据库。
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