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On the Description-based Spatial Positioning and the Associated Uncertainty

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  • 1. Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, China;
    2. School of Geomatics and Urban Information, Beijing University of Civil Engineering and Architecture, Beijing 100044, China

Received date: 2012-10-19

  Revised date: 2012-12-11

  Online published: 2013-02-25

Abstract

In the representation and communication of geographical knowledge of human beings, locations are often textually expressed. In addition to place names and addresses, a spatial assertion, which consists of reference objects and spatial relations, can roughly describe a locality. Typical examples of spatial assertions are "the vicinity of Peking University" and "Between Peking University and Tsinghua University". The objective of spatial positioning is to infer the location of a target object and the associated uncertainty for a given spatial assertion. In this research, we investigate four levels of uncertainty associated with spatial assertions. They are uncertainty of spatial assertions, imperfection of reference objects, imprecision and vagueness of spatial relations, and distribution of target objects. If a target object is abstracted to a point, the concept of an uncertainty field can be used to represent the possible spatial distribution of the target object. An uncertainty field is a 2-dimensional probability density function that satisfies 45p(x,y)dxdy=1 where denotes the field and F is its support. For a point T and a reference object A, if the probability that an observer make a description X is high, then the probability density at O is also high when X is known. This argument is proved using Bayes' theorem and can be viewed as the theoretical foundation to establish an uncertainty field. We also implemented a toolkit to generate uncertainty fields based on a number of spatial assertions.

Cite this article

ZHANG Yi, WU Yang, GAO Yong, LIU Yu . On the Description-based Spatial Positioning and the Associated Uncertainty[J]. Journal of Geo-information Science, 2013 , 15(1) : 38 -45 . DOI: 10.3724/SP.J.1047.2013.00038

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