A framework for the modelling of uncertainty between remote sensing and geographic information systems
A framework for the modelling of uncertainty between remote sensing and geographic information systems
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DOI：
10.1016/s0924-2716(00)00018-6
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发表时间：
2000-09-01
影响因子：
12.7
通讯作者：
Ehlers, M
中科院分区：
文献类型：
--
作者：
Gahegan, M;Ehlers, M
本文讨论了集成地理信息系统 (GIS) 中的不确定性建模，特别关注 GIS 和遥感之间活动的融合。当数据从“原始”形式抽象为 GIS 使用的更高表示形式时，它会通过一系列转换传递到许多不同的概念数据模型。每个模型和每个转换过程都会导致数据中存在的整体不确定性。本文讨论的问题有三个。首先，根据适用的固有不确定性特征给出了各种地理空间模型的描述；然后将其转化为简单的形式主义。其次，描述了用于从图像数据形成地理类或对象的各种变换过程，并阐述了它们对数据不确定性属性的影响。第三，使用形式主义来描述转换过程，导出了通过集成GIS传播不确定性的框架。通过总结，得出了一个表格，描述了四种地理空间基础模型中累积的不确定性的来源。 (C) 2000 Elsevier Science B.V. 保留所有权利。
This paper addresses the modelling of uncertainty in an integrated geographic information system (GIS), specifically focused on the fusion of activities between GIS and remote sensing. As data is abstracted from its 'raw' form to the higher representations used by GIS, it passes through a number of different conceptual data models via a series of transformations. Each model and each transformation process contributes to the overall uncertainty present within the data. The issues that this paper addresses are threefold. Firstly, a description of various models of geographic space is given in terms of the inherent uncertainty characteristics that apply; this is then worked into a simple formalism. Secondly, the various transformation processes that are used to form geographic classes or objects from image data are described, and their effects on the uncertainty properties of data are stated. Thirdly, using the formalism to describe the transformation processes, a framework for the propagation of uncertainty through an integrated GIS is derived. By way of a summary, a table describing sources of accumulated uncertainty across four underlying models of geographic space is derived. (C) 2000 Elsevier Science B.V. All rights reserved.