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A detailed characterization of the pore space is crucial for understanding of transport and element transfer in rocks. Here, the effect of differences in texture and content of secondary minerals on transport in pore systems was determined for two rocks of widespread occurrence, mid-ocean ridge basalts (MORB) and granites. Pore space characteristics were analyzed by Hg-porosimetry, intrusion of a molten alloy, and synchrotron-based X-ray tomographic microscopy. For evaluating the role of pore space characteristics for the prediction of diffusive transport, data on porosity, and the effective diffusion coefficient (D eff) were compared. Extended connective pore systems due to cracks and mineral dissolution are present in samples of both rocks, indicating high internal specific surface area. Uneven pore size distributions in altered MORB samples can be assigned to secondary minerals. Pore spaces determined by X-ray tomography, used to determine main direction of pores in the 3-D orthogonal system, suggest a slight anisotropy. In log–log plots, both rocks show roughly a linear dependence of D eff for H2O and compounds with comparable diffusivities (D2O, monovalent cations, and anions) on porosity, but at same porosity D eff is clearly higher in granitic than in basaltic samples. This difference is increasing with decreasing porosity, indicating that at low porosities the efficiency of element transport in basaltic samples is diminished, mainly inherited by the presence of small pores slowing down diffusion. The fact that diffusive transport in basaltic rocks is stronger dependent on porosity than in granitic rocks shows that also other rock characteristics such as pore size distribution and tortuosity of the pore network, highly affected by the alteration degree, can markedly affect transport and reactivity of pore solution.  相似文献   
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Landslides are the fourth most common natural disasters in the world, with Costa Rica and southern Mexico being the most affected regions of Central America (Froude and Petley, 2018). In this work, we propose a semi-automated method to detect earthquake-triggered landslides for rapid mapping after a disaster event using open Sentinel-1 data. We used high-resolution TerraSAR-X data and very high-resolution Spot-7 images to compare and evaluate the accuracy of landslide distribution maps generated from the semi-automated method, applied to the M 7.1 earthquake on June 23, 2017, in Oaxaca, Mexico. The outcomes showed better accuracy in descending orbits due to ‘windward-leeward’ physiographic conditions, with a 50.56% quality percentage. This shows a reasonably good capacity to detect co-seismic landslides. However, the breaching factor was also high because several features, such as bare soils and agricultural areas, were incorrectly identified as co-seismic landslides. Finally, this semi-automated method establishes a basis for future improvements in methodologies applied to construct rapid mapping inventories using medium SAR scales.

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