New Approaches for Multi Source Data Sediment Characterisation, Thickness Assessment and Clean up Strategies
The present article explain how potentially contaminated sediment thickness in Augusta harbour was estimated by using a multisource dataset characterized by a variable accuracy. Inequalities constrains on the sediment thickness are extracted from the sediment sampling stations and seismic profiles i...
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2012-07-01
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Series: | Chemical Engineering Transactions |
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doaj-b386c1e190184bf6926213ed199dfbad2021-02-22T21:06:56ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162012-07-012810.3303/CET1228038New Approaches for Multi Source Data Sediment Characterisation, Thickness Assessment and Clean up StrategiesA. AusiliS. CappucciM. GabelliniC. InnocentiM. MaffucciE. RomanoL. RossiA. TaramelliThe present article explain how potentially contaminated sediment thickness in Augusta harbour was estimated by using a multisource dataset characterized by a variable accuracy. Inequalities constrains on the sediment thickness are extracted from the sediment sampling stations and seismic profiles in which the hard irregular sub-bottom was out of detection range (soft data). It utilized the kriging-with-inequalities method that belongs to the data transformation group. The method considers the inequalities constraints as data themselves and, after a transformation, their use together with the exact hard data to estimate the thickness of the sediment layer. The results show the usefulness of an approach that permitted to extract the maximum information from multisource data, collected for different purposes, in order to assess the 3D spatial domain of recent contaminated sediment and reduce the cost of management.https://www.cetjournal.it/index.php/cet/article/view/7308 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
A. Ausili S. Cappucci M. Gabellini C. Innocenti M. Maffucci E. Romano L. Rossi A. Taramelli |
spellingShingle |
A. Ausili S. Cappucci M. Gabellini C. Innocenti M. Maffucci E. Romano L. Rossi A. Taramelli New Approaches for Multi Source Data Sediment Characterisation, Thickness Assessment and Clean up Strategies Chemical Engineering Transactions |
author_facet |
A. Ausili S. Cappucci M. Gabellini C. Innocenti M. Maffucci E. Romano L. Rossi A. Taramelli |
author_sort |
A. Ausili |
title |
New Approaches for Multi Source Data Sediment Characterisation, Thickness Assessment and Clean up Strategies |
title_short |
New Approaches for Multi Source Data Sediment Characterisation, Thickness Assessment and Clean up Strategies |
title_full |
New Approaches for Multi Source Data Sediment Characterisation, Thickness Assessment and Clean up Strategies |
title_fullStr |
New Approaches for Multi Source Data Sediment Characterisation, Thickness Assessment and Clean up Strategies |
title_full_unstemmed |
New Approaches for Multi Source Data Sediment Characterisation, Thickness Assessment and Clean up Strategies |
title_sort |
new approaches for multi source data sediment characterisation, thickness assessment and clean up strategies |
publisher |
AIDIC Servizi S.r.l. |
series |
Chemical Engineering Transactions |
issn |
2283-9216 |
publishDate |
2012-07-01 |
description |
The present article explain how potentially contaminated sediment thickness in Augusta harbour was estimated by using a multisource dataset characterized by a variable accuracy. Inequalities constrains on the sediment thickness are extracted from the sediment sampling stations and seismic profiles in which the hard irregular sub-bottom was out of detection range (soft data). It utilized the kriging-with-inequalities method that belongs to the data transformation group. The method considers the inequalities constraints as data themselves and, after a transformation, their use together with the exact hard data to estimate the thickness of the sediment layer. The results show the usefulness of an approach that permitted to extract the maximum information from multisource data, collected for different purposes, in order to assess the 3D spatial domain of recent contaminated sediment and reduce the cost of management. |
url |
https://www.cetjournal.it/index.php/cet/article/view/7308 |
work_keys_str_mv |
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