Geophysical and remote sensing-based approach to model regolith thickness in a data-sparse environment

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• 作者：Muhammad Shafique^a ; ^b ; ^{shafique@itc.nl"" rel=""nofollow} ; Mark van der Meijde^a ; David G. Rossiter^a
• 关键词：Regolith thickness ; Alluvium ; Landforms ; Electrical resistivity ; Multiple linear regression ; Northern Pakistan
• 刊名：Catena
• 出版年：2011
• 出版时间：October 2011
• 年：2011
• 卷：87
• 期：1
• 页码：11-19
• 全文大小：1588 K

文摘

Mapping regolith thickness to bedrock is important for environmental modeling in general and for seismic hazard assessment in particular. However, regolith thickness is often ignored in such studies because of its presumed difficulty of mapping in many terrains. To overcome this limitation we developed a generic remote sensing and geophysics based approach to model regolith thickness for areas with limited possibility of direct field observations. The approach was tested in a seismically-active and depositional landscape in northern Pakistan. Regolith thickness was sampled at exposed bedrock outcrops along the river bed and scarps. At unexposed sites the regolith-bedrock interface was identified through electrical resistivity survey, thus providing an indirect measurement of regolith thickness. A geomorphic classification of landforms and topographic attributes were derived from a remote sensing-based (ASTER) digital elevation model and SPOT-5 satellite imagery. Landform was the most important predictor (adjusted R² = 72.1 % ), showing the importance of geomorphic interpretation. A multivariate linear model based on landform, elevation and distance to stream was able to predict the regolith thickness (adjusted R² = 91.7), including field-observed abrupt changes at landform boundaries.