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Abstract

The growing number of different models and approaches for Geographic Information Systems (GIS) brings high complexity when we want to develop new approaches and compare a new GIS algorithm. In order to test and compare different processing models and approaches, in a simple way, we identified the need of defining uniform testing methods, able to compare processing algorithms in terms of performance and accuracy regarding: large imaging processing, algorithms for GIS pattern-detection.

Taking into account, for instance, images collected during a drone flight or a satellite, it is important to know the processing cost to extract data when applying different processing models and approaches, as well as their accuracy (compare execution time vs. extracted data quality). In this work we propose a GIS Benchmark (GISB), a benchmark that allows to evaluate different approaches to detect/extract selected features from a GIS data-set. Considering a given data-set (or two data-sets, from different years, of the same region) it provides linear methods to compare different performance parameters regarding GIS information, making possible to access the most relevant information in terms of features and processing efficiency.

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Acknowledgment

This project is part of a larger software prototype, partially financed by CISUC research group from the University of Coimbra, and the Foundation for Science and Technology.

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Correspondence to Pedro Martins .

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© 2016 Springer International Publishing Switzerland

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Martins, P., Cecílio, J., Abbasi, M., Furtado, P. (2016). GISB: A Benchmark for Geographic Map Information Extraction. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery. BDAS BDAS 2015 2016. Communications in Computer and Information Science, vol 613. Springer, Cham. https://doi.org/10.1007/978-3-319-34099-9_46

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  • DOI: https://doi.org/10.1007/978-3-319-34099-9_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-34098-2

  • Online ISBN: 978-3-319-34099-9

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