The spatio-temporal variations of soil gas in the seismic fault zone produced by the 12 May 2008 Wenchuan Ms 8.0 earthquake were investigated based on the field measurements of soil gas concentrations after the main shock. Concentrations of He, H2, CO2, CH4, O2, N2, Rn, and Hg in soil gas were measured in the field at eight short profiles across the seismic rupture zone in June and December 2008 and July 2009. Soil-gas concentrations of more than 800 sampling sites were obtained. The data showed that the magnitudes of the He and H2 anomalies of three surveys declined significantly with decreasing strength of the aftershocks with time. The maximum concentrations of He and H2 (40 and 279.4 ppm, respectively) were found in three replicates at the south part of the rupture zone close to the epicenter. The spatio-temporal variations of CO2, Rn, and Hg concentrations differed obviously between the north and south parts of the fault zone. The maximum He and H2 concentrations in Jun 2008 occurred near the parts of the rupture zone where vertical displacements were larger. The anomalies of He, H2, CO2, Rn, and Hg concentrations could be related to the variation in the regional stress field and the aftershock activity.
Density-based spatial clustering of applications with noise (DBSCAN) is a density-based clustering algorithm that has the characteristics of being able to discover clusters of any shape, effectively distinguishing noise points and naturally supporting spatial databases. DBSCAN has been widely used in the field of spatial data mining. This paper studies the parallelization design and realization of the DBSCAN algorithm based on the Spark platform, and solves the following problems that arise when computing macro data: the requirement of a great deal of calculation using the single-node algorithm; the low level of resource-utilization with the multi-node algorithm; the large time consumption; and the lack of instantaneity. The experimental results indicate that the proposed parallel algorithm design is able to achieve more stable speedup at an increased involved spatial data scale.
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