Abstract
A range of global environmental and social problems, such as climate change or social transformation processes, are aggravated by diverse anthropogenic impacts. To monitor, analyse and combating these processes, topical information on the status, development, spatial and temporal dynamics of them is an indispensable prerequisite. The growing, frequently rapid demand for global and regional data in relevant geographical, geometric, semantic and temporal resolution can only be met by remote sensing data the majority of which are available on an operational scale. Not only does the availability of data present a major obstacle for the above applications, but also rapid processing of the acquired remote sensing data is a severe bottleneck for the provision of the required data for, e.g. time-critical investigations. These problems can be addressed by developing an automated processing chain to derive value-added data producing from the remote sensing input data. Effective automated data processing necessitates a data quality assessment prior to actual processing. This paper deals with a processor for an automated data usability assessment that can be integrated into an automated processing chain for operative value adding.
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Borg, E., Fichtelmann, B., Asche, H. (2013). Data Usability Processor for Optical Remote Sensing Imagery: Design and Implementation into an Automated Processing Chain. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2013. ICCSA 2013. Lecture Notes in Computer Science, vol 7972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39643-4_46
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DOI: https://doi.org/10.1007/978-3-642-39643-4_46
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