@article{ParedesBooAmoretal.2012,
  author    = {Paredes, E. G. and Boo, M. and Amor, M. and Bruguera, J. D. and D{\"o}llner, J{\"u}rgen Roland Friedrich},
  title     = {Extended hybrid meshing algorithm for multiresolution terrain models},
  series = {International journal of geographical information science},
  volume    = {26},
  journal   = {International journal of geographical information science},
  number    = {5},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {1365-8816},
  doi       = {10.1080/13658816.2011.615317},
  pages     = {771 -- 793},
  year      = {2012},
  abstract  = {Hybrid terrains are a convenient approach for the representation of digital terrain models, integrating heterogeneous data from different sources. In this article, we present a general, efficient scheme for achieving interactive level-of-detail rendering of hybrid terrain models, without the need for a costly preprocessing or resampling of the original data. The presented method works with hybrid digital terrains combining regular grid data and local high-resolution triangulated irregular networks. Since grid and triangulated irregular network data may belong to different datasets, a straightforward combination of both geometries would lead to meshes with holes and overlapping triangles. Our method generates a single multiresolution model integrating the different parts in a coherent way, by performing an adaptive tessellation of the region between their boundaries. Hence, our solution is one of the few existing approaches for integrating different multiresolution algorithms within the same terrain model, achieving a simple interactive rendering of complex hybrid terrains.},
  language  = {en}
}
@article{KoyanTronicke2020,
  author    = {Koyan, Philipp and Tronicke, Jens},
  title     = {3D modeling of ground-penetrating radar data across a realistic sedimentary model},
  series = {Computers \& geosciences : an international journal devoted to the publication of papers on all aspects of geocomputation and to the distribution of computer programs and test data sets ; an official journal of the International Association for Mathematical Geology},
  volume    = {137},
  journal   = {Computers \& geosciences : an international journal devoted to the publication of papers on all aspects of geocomputation and to the distribution of computer programs and test data sets ; an official journal of the International Association for Mathematical Geology},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0098-3004},
  doi       = {10.1016/j.cageo.2020.104422},
  pages     = {9},
  year      = {2020},
  abstract  = {Ground-penetrating radar (GPR) is an established geophysical tool to explore a wide range of near-surface environments. Today, the use of synthetic GPR data is largely limited to 2D because 3D modeling is computationally more expensive. In fact, only recent developments of modeling tools and powerful hardware allow for a time-efficient computation of extensive 3D data sets. Thus, 3D subsurface models and resulting GPR data sets, which are of great interest to develop and evaluate novel approaches in data analysis and interpretation, have not been made publicly available up to now. <br /> We use a published hydrofacies data set of an aquifer-analog study within fluvio-glacial deposits to infer a realistic 3D porosity model showing heterogeneities at multiple spatial scales. Assuming fresh-water saturated sediments, we generate synthetic 3D GPR data across this model using novel GPU-acceleration included in the open-source software gprMax. We present a numerical approach to examine 3D wave-propagation effects in modeled GPR data. Using the results of this examination study, we conduct a spatial model decomposition to enable a computationally efficient 3D simulation of a typical GPR reflection data set across the entire model surface. We process the resulting GPR data set using a standard 3D structural imaging sequence and compare the results to selected input data to demonstrate the feasibility and potential of the presented modeling studies. We conclude on conceivable applications of our 3D GPR reflection data set and the underlying porosity model, which are both publicly available and, thus, can support future methodological developments in GPR and other near-surface geophysical techniques.},
  language  = {en}
}