首页> 外文会议>NATO Advanced Research Workshop on Fuzziness and Uncertainty in GIS for Environmental Security and Protection >FUZZY MODELS FOR HANDLING UNCERTAINTY IN THE INTEGRATION OF HIGH RESOLUTION REMOTELY SENSED DATA AND GIS
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FUZZY MODELS FOR HANDLING UNCERTAINTY IN THE INTEGRATION OF HIGH RESOLUTION REMOTELY SENSED DATA AND GIS

机译:用于处理高分辨率集成的不确定性的模糊模型远程感测数据和GIS

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The advent of new high resolution sensors, either airborne or spaceborne, leads to new applications and further impulses for an integration of remotely sensed and GIS data. Along with these new data sources, existing processing methods have to be adopted which is in particular also valid for the assessment of the post classification quality. In this overall context our contribution will outline general uncertainty aspects in the integration process and particular problems with the accuracy assessment based on high resolution data. These problems lead to the motivation to develop a new characteristic value, called the Fuzzy Certainty Measure (FCM), which considers indeterminate boundaries in the classification result as well as in the reference data, and can be applied in a class- and even object-specific manner.
机译:新的高分辨率传感器的出现,无论是空中的或空间传单,都会导致新的应用和进一步的冲动,用于遥感和GIS数据的整合。除了这些新的数据源之外,必须采用现有的处理方法,特别是对于评估后分类质量也有效。在这一整体背景下,我们的贡献将在整合过程中概述一般不确定性方面,以及基于高分辨率数据的准确性评估的特殊问题。这些问题导致动力开发出一种新的特征值,称为模糊确定性测量(FCM),其认为在分类结果中的不确定边界以及参考数据中,并且可以应用于类甚至对象 - 具体方式。

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