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This paper reviews some recent advancements that address the challenges faced by the broad application area of datadriven site characterization (DDSC). The challenges include the ugly-data challenge, site-recognition challenge, and stratification challenge. The ugly-data challenge is about the MUSIC-3X attributes of the site investigation data, where MUSIC-3X stands for multivariate, uncertain and unique, sparse, incomplete, possibly corrupted, and 3D spatial variability (3X). The site-recognition challenge is about the site-uniqueness feature of the site investigation data. The stratification challenge is about the task of layer delineation in soil profiling. In recent years, some studies have been conducted to address these challenges with an encouraging degree of success, which are briefly reviewed in this paper. However, there are still unresolved issues yet to be addressed, which are briefly summarized in this paper as well. | This paper reviews some recent advancements that address the challenges faced by the broad application area of datadriven site characterization (DDSC). The challenges include the ugly-data challenge, site-recognition challenge, and stratification challenge. The ugly-data challenge is about the MUSIC-3X attributes of the site investigation data, where MUSIC-3X stands for multivariate, uncertain and unique, sparse, incomplete, possibly corrupted, and 3D spatial variability (3X). The site-recognition challenge is about the site-uniqueness feature of the site investigation data. The stratification challenge is about the task of layer delineation in soil profiling. In recent years, some studies have been conducted to address these challenges with an encouraging degree of success, which are briefly reviewed in this paper. However, there are still unresolved issues yet to be addressed, which are briefly summarized in this paper as well. | ||
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+ | == Full Paper == | ||
+ | <pdf>Media:Draft_Sanchez Pinedo_201199534318.pdf</pdf> |
This paper reviews some recent advancements that address the challenges faced by the broad application area of datadriven site characterization (DDSC). The challenges include the ugly-data challenge, site-recognition challenge, and stratification challenge. The ugly-data challenge is about the MUSIC-3X attributes of the site investigation data, where MUSIC-3X stands for multivariate, uncertain and unique, sparse, incomplete, possibly corrupted, and 3D spatial variability (3X). The site-recognition challenge is about the site-uniqueness feature of the site investigation data. The stratification challenge is about the task of layer delineation in soil profiling. In recent years, some studies have been conducted to address these challenges with an encouraging degree of success, which are briefly reviewed in this paper. However, there are still unresolved issues yet to be addressed, which are briefly summarized in this paper as well.
Published on 10/06/24
Submitted on 10/06/24
Volume Plenary Lectures, 2024
DOI: 10.23967/isc.2024.318
Licence: CC BY-NC-SA license
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