Articles | Volume 23, issue 1
https://doi.org/10.5194/nhess-23-91-2023
https://doi.org/10.5194/nhess-23-91-2023
Research article
 | 
13 Jan 2023
Research article |  | 13 Jan 2023

On the calculation of smoothing kernels for seismic parameter spatial mapping: methodology and examples

David Montiel-López, Sergio Molina, Juan José Galiana-Merino, and Igor Gómez

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Cited articles

Aki, K.: Maximum likelihood estimate of b in the formula log N = a-bM and its confidence limits, Bull. Earthq. Res. Inst., 43, 237–239, 1965. a, b
Alarcón, E. and Benito, B.: Foreword special issue Lorca's earthquake, B. Earthq. Eng., 12, 1827–1829, https://doi.org/10.1007/s10518-014-9602-4, 2014. a
Batte, A. G. and Rümpker, G.: Spatial mapping of b-value heterogeneity beneath the Rwenzori region, Albertine rift: Evidence of magmatic intrusions, J. Volcanol. Geoth. Res., 381, 238–245, https://doi.org/10.1016/j.jvolgeores.2019.05.015, 2019. a
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Carreño-Herrero, E. and Valero-Zornoza, J. F.: The Iberian Peninsula seismicity for the instrumental period: 1985–2011, Enseñ. Cienc. Tierra, 19, 289–295, 2011. a
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One of the most effective ways to describe the seismicity of a region is to map the b-value parameter of the Gutenberg-Richter law. This research proposes the study of the spatial cell-event distance distribution to define the smoothing kernel that controls the influence of the data. The results of this methodology depict tectonic stress changes before and after intense earthquakes happen, so it could enable operational earthquake forecasting (OEF) and tectonic source profiling.
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