HPC-ICTM: a Parallel Model for Geographic Categorization

HPC-ICTM: a Parallel Model for Geographic Categorization

This paper presents a parallel version of the interval categorizer tessellation-based model (ICTM) for the simultaneous categorization of geographic regions considering several characteristics (e.g., relief vegetation, land use etc.) in clusters, called HPC-ICTM. Interval techniques are used for the...

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Hauptverfasser: Silva, R.K.S., De Rose, C.A.F., de Aguiar, M.S., Dimuro, G.P., Costa, A.C.R.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Biological system modeling
Character generation
Environmental factors
Error analysis
Error correction
Geophysics
Informatics
Performance analysis
Satellites
Vegetation mapping
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Zusammenfassung:This paper presents a parallel version of the interval categorizer tessellation-based model (ICTM) for the simultaneous categorization of geographic regions considering several characteristics (e.g., relief vegetation, land use etc.) in clusters, called HPC-ICTM. Interval techniques are used for the modeling of uncertain data and the control of discretization errors. We analyze the performance of the HPC-ICTM and present results concerning its application to the relief/land-use categorization of the region surrounding the lagoon Lagoa Pequena (RS, Brazil), which is extremely important from an ecological point of view
DOI:10.1109/JVA.2006.23