Integrative Geospatial Analysis: Unveiling Insights through GIS Modeling and Statistical Evaluation of SPT-N and Soil Types Data of New Kabul City, Afghanistan
The precise evaluation of subsurface soil information is paramount for effective infrastructure design and planning. Geotechnical soil maps (GSMs) play a pivotal role in estimating subsurface properties. As Kabul City, Afghanistan’s largest metropolitan area, undergoes rapid expansion and the demand...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2024/9925038 |
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| author | Mohammad Amini Longsheng Deng Waqas Hassan Muhammad Naqeeb Nawaz Fatima Zahra Zidane Ranke Fang |
| author_facet | Mohammad Amini Longsheng Deng Waqas Hassan Muhammad Naqeeb Nawaz Fatima Zahra Zidane Ranke Fang |
| author_sort | Mohammad Amini |
| collection | DOAJ |
| description | The precise evaluation of subsurface soil information is paramount for effective infrastructure design and planning. Geotechnical soil maps (GSMs) play a pivotal role in estimating subsurface properties. As Kabul City, Afghanistan’s largest metropolitan area, undergoes rapid expansion and the demand for safer infrastructure rises, the necessity for precise geotechnical information becomes increasingly urgent. Nevertheless, there is a lack of comprehensive studies on urban geotechnical zoning maps in Afghanistan. Therefore, to this end, this study utilizes inverse distance weighting (IDW) interpolation approaches for the construction and characterization of GSMs using a traditional geographic information system (GIS). Data about soil types and standard penetration (N-value) up to 30 m depth were extracted from 130 locations in New Kabul City, Afghanistan. GSMs incorporating N-value and soil types were constructed utilizing the IDW technique within the ArcGIS platform. The outcomes reveal that the subjected region was dominated by cohesive soil with N-values varying from 7 to 45 in three different sections. The findings exhibit strong empirical correlations between N-values and depth, with an R2 value of 0.95 and an RMSD value of 0.71. Moreover, the correlation coefficient to predict soil type classification is 97%, and it stands at 95% for N-value prediction. These results facilitate the rapid evaluation of subsoil strength and stiffness, offering valuable insights for project planners and feasibility researchers. |
| format | Article |
| id | doaj-art-025155427520496dbdd8c58ecd11fc6d |
| institution | Kabale University |
| issn | 1687-8094 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-025155427520496dbdd8c58ecd11fc6d2025-02-03T06:10:21ZengWileyAdvances in Civil Engineering1687-80942024-01-01202410.1155/2024/9925038Integrative Geospatial Analysis: Unveiling Insights through GIS Modeling and Statistical Evaluation of SPT-N and Soil Types Data of New Kabul City, AfghanistanMohammad Amini0Longsheng Deng1Waqas Hassan2Muhammad Naqeeb Nawaz3Fatima Zahra Zidane4Ranke Fang5School of Geological Engineering and Geomatics of Chang’an UniversitySchool of Geological Engineering and Geomatics of Chang’an UniversityNational University of Science and TechnologyNational University of Science and TechnologySchool of Geological Engineering and Geomatics of Chang’an UniversitySchool of Geological Engineering and Geomatics of Chang’an UniversityThe precise evaluation of subsurface soil information is paramount for effective infrastructure design and planning. Geotechnical soil maps (GSMs) play a pivotal role in estimating subsurface properties. As Kabul City, Afghanistan’s largest metropolitan area, undergoes rapid expansion and the demand for safer infrastructure rises, the necessity for precise geotechnical information becomes increasingly urgent. Nevertheless, there is a lack of comprehensive studies on urban geotechnical zoning maps in Afghanistan. Therefore, to this end, this study utilizes inverse distance weighting (IDW) interpolation approaches for the construction and characterization of GSMs using a traditional geographic information system (GIS). Data about soil types and standard penetration (N-value) up to 30 m depth were extracted from 130 locations in New Kabul City, Afghanistan. GSMs incorporating N-value and soil types were constructed utilizing the IDW technique within the ArcGIS platform. The outcomes reveal that the subjected region was dominated by cohesive soil with N-values varying from 7 to 45 in three different sections. The findings exhibit strong empirical correlations between N-values and depth, with an R2 value of 0.95 and an RMSD value of 0.71. Moreover, the correlation coefficient to predict soil type classification is 97%, and it stands at 95% for N-value prediction. These results facilitate the rapid evaluation of subsoil strength and stiffness, offering valuable insights for project planners and feasibility researchers.http://dx.doi.org/10.1155/2024/9925038 |
| spellingShingle | Mohammad Amini Longsheng Deng Waqas Hassan Muhammad Naqeeb Nawaz Fatima Zahra Zidane Ranke Fang Integrative Geospatial Analysis: Unveiling Insights through GIS Modeling and Statistical Evaluation of SPT-N and Soil Types Data of New Kabul City, Afghanistan Advances in Civil Engineering |
| title | Integrative Geospatial Analysis: Unveiling Insights through GIS Modeling and Statistical Evaluation of SPT-N and Soil Types Data of New Kabul City, Afghanistan |
| title_full | Integrative Geospatial Analysis: Unveiling Insights through GIS Modeling and Statistical Evaluation of SPT-N and Soil Types Data of New Kabul City, Afghanistan |
| title_fullStr | Integrative Geospatial Analysis: Unveiling Insights through GIS Modeling and Statistical Evaluation of SPT-N and Soil Types Data of New Kabul City, Afghanistan |
| title_full_unstemmed | Integrative Geospatial Analysis: Unveiling Insights through GIS Modeling and Statistical Evaluation of SPT-N and Soil Types Data of New Kabul City, Afghanistan |
| title_short | Integrative Geospatial Analysis: Unveiling Insights through GIS Modeling and Statistical Evaluation of SPT-N and Soil Types Data of New Kabul City, Afghanistan |
| title_sort | integrative geospatial analysis unveiling insights through gis modeling and statistical evaluation of spt n and soil types data of new kabul city afghanistan |
| url | http://dx.doi.org/10.1155/2024/9925038 |
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