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Handling Uncertainty Propagation through the Buffer Operation in a Raster Environment

机译:通过栅格环境中的缓冲操作处理不确定性传播

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This study focuses on how various sources of uncertainty affect the output of the buffer operation in a raster environment. Two main sources of uncertainty are identified: source layer uncertainty and model uncertainty. When multivariate statistical classification of remotely sensed data is used, per pixel information on the magnitude and spatial structure of source layer uncertainty can be derived from the class membership probabilities. A Boolean reclassification of all cells to delimit buffers around feature cells introduces model uncertainty. A fuzzy classification provides more information and is also much less sensitive to source layer uncertainty. The use of fixed resistance values introduces an additional source of model uncertainty, which can be expressed by means of a fuzzy membership function.
机译:本研究侧重于各种不确定性源如何影响光栅环境中缓冲区操作的输出。确定了两个主要不确定性来源:源层不确定性和模型不确定性。当使用远程感测数据的多变量统计分类时,每个像素信息可以源自源层不确定性的幅度和空间结构。对特征细胞周围限定缓冲器的所有单元的布尔重新分类引入了模型不确定性。模糊分类提供了更多信息,并且对源层不确定性也不敏感。固定电阻值的使用引入了额外的模型不确定性来源,其可以通过模糊的成员函数表示。

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