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Managing Spatial Uncertainty in Remotely Sensed Data

机译:在远程感测数据中管理空间不确定性

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摘要

The level of spatial uncertainty in geographical information systems (GIS) products is conditional on a number of operations on the spatial database prior to final output. Although stochastic and deterministic models have been used to predict the levels of uncertainty in digital map products through GIS operations such as overlay and buffering, the extent to which each operation contributes to overall product uncertainty is neither well known nor understood. An alternative approach is to examine the level of spatial uncertainty in the output product and then to improve the accuracy of this output by applying a rule-based model. In this paper, a conceptual rule-based model is proposed to effectively manage spatial uncertainty by examining the interrelationships between and within polygons resulting from the overlay of multiple independent human interpreter realisations of a satellite image. In a previous paper by Allan (1999), a method was proposed to extract information about these polygons from the overlay of these realisations for inclusion in the database and an approach was suggested in handling the resultant uncertainty polygons. Further work has seen the development of structural knowledge (rules) and procedural knowledge (operators) for managing these uncertainty polygons based on their likelihood of belonging to a particular thematic class. The adoption of such an approach is based on the semantic, geometric and spatial relations within and among uncertainty polygons generated from these realisations.
机译:地理信息系统(GIS)产品中的空间不确定性水平在最终输出之前的空间数据库的许多操作上是有条件的。虽然已经使用随机和确定性模型来通过覆盖和缓冲等GIS操作来预测数字地图产品的不确定性水平,但是每种操作对整体产品不确定性的程度既不是众所周知的,也不是理解的。另一种方法是检查输出产品中的空间不确定性水平,然后通过应用基于规则的模型来提高该输出的精度。在本文中,提出了一种基于概念规则的模型,以通过检查由卫星图像的多个独立人体解释器实现的覆盖层的覆盖层来有效地管理空间不确定性。在先前的纸张中(1999)中,提出了一种方法,以从这些实现的覆盖中提取有关这些多边形的信息,以便包含在数据库中,并在处理所得的不确定性多边形方面提出一种方法。进一步的工作已经看到,基于其属于特定专题课程的可能性,可以制定结构知识(规则)和程序知识(运营商)的发展,用于管理这些不确定性多边形。采用这种方法是基于从这些实现产生的不确定性多边形内的语义,几何和空间关系。

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