Mass movement susceptibility prediction and infrastructural risk assessment (IRA) using GIS-based Meta classification algorithms

Ali, Sk Ajim; Mohajane, Meriame; Parvin, Farhana; Varasano, Antonietta; Hitouri, Sliman; Łupikasza, Ewa; Pham, Quoc Bao

doi:10.1016/j.asoc.2023.110591

Cited by 5 publications

(1 citation statement)

References 109 publications

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“…GIS capabilities were employed to find highway sections that received multiple reconstructions over their planning prospect [136], apply geotechnical considerations in a highway layout [102], detect utility conflicts in railway projects prior to construction [38], prioritize maintenance plans [137], create a geo-enabled geometric design for highways, conduct environmental assessment of concrete mixes [138], and optimize construction site material distribution layout [139]. Studies also employed GIS for pavement performance analysis to investigate the impact of different factors such as precipitation, [140][141][142], mass movement susceptibility prediction [143], sustainability-based management [144], construction quality evaluation [27], functional road classification [145], and climate change risk assessment of critical infrastructure [146]. More innovative approaches engineered an integrated system of Augmented Reality (AR) and GIS to map subterranean utilities using mobile devices [147].…”

Section: Geospatial Analysis Tools For Project Planning (Geospatial A...mentioning

confidence: 99%

Civil Integrated Management (CIM) for Advanced Level Applications to Transportation Infrastructure: A State-of-the-Art Review

Taheri,

Sobanjo

2024

Infrastructures

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The recent rise in the applications of advanced technologies in the sustainable design and construction of transportation infrastructure demands an appropriate medium for their integration and utilization. The relatively new concept of Civil Integrated Management (CIM) is such a medium; it enhances the development of digital twins for infrastructure and also embodies various practices and tools, including the collection, organization, and data-management techniques of digital data for transportation infrastructure projects. This paper presents a comprehensive analysis of advanced CIM tools and technologies and categorizes its findings into the following research topics: application of advanced surveying methods (Advanced Surveying); geospatial analysis tools for project planning (Geospatial Analysis); multidimensional virtual design models (nD Modeling); Integrated Geospatial and Building Information Modeling (GeoBIM); and transportation infrastructure maintenance and rehabilitation planning (Asset Management). Despite challenges such as modeling complexity, technology investment, and data security, the integration of GIS, BIM, and artificial intelligence within asset-management systems hold the potential to improve infrastructure’s structural integrity and long-term performance through automated monitoring, analysis, and predictive maintenance during its lifetime.

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Section: Geospatial Analysis Tools For Project Planning (Geospatial A...mentioning

confidence: 99%

Civil Integrated Management (CIM) for Advanced Level Applications to Transportation Infrastructure: A State-of-the-Art Review

Taheri,

Sobanjo

2024

Infrastructures

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Modeling climatic, terrain and soil factors using AHP in GIS for grapevines suitability assessment

D'Antonio,

Fiorentino,

AbdelRahman

et al. 2024

Sustainable Development

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The study carried out in Matera, Italy, used multi‐criteria decision‐making techniques and geographic information systems to identify optimal area management for sustainable grape production. Terrain parameters such as temperature, pH, humidity, soil texture, slope, altitude, nutrients and precipitation were considered. ArcGIS maps were created, and the northwest part of the field was identified as a favorable area. Fuzzy maps were generated, and measurements were taken in each area to determine optimal land management. The results revealed that 51% of the area was very highly suitable for agricultural activities, and 49% was considered high suitable. Receiver operating characteristic (ROC) analysis of the AHP results demonstrated a high level of accuracy, as indicated by the area under the curve (AUC). The produced maps indicated a similar trend of increasing zone management priorities for physico‐chemicals as depth fluctuate. Additionally, results showed that remote sensing indices were the most important variables to predict physico‐chemicals zone management. The study also highlighted that the majority of the area supported plant growth due to favorable temperature and humidity conditions, with only a small portion in the northwest showing less favorable results. By identifying management zones, the study aimed to protect crops, better use of irrigation water and improve yields. This study highlights the potential of integrating satellite remote sensing, GIS technology and AHP as a valuable tool for agricultural land use planners and policy makers in identifying optimal locations for managing grape production.

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GIS-Based Landslides Risk Assessment Applying Certainty Factor (CF) and Ensemble with Deep Learning Neural Network (DLNN): a Study of Cachar District of Assam, India

Ali,

Parvin

2024

Springer Proceedings in Earth and Environmental Sciences

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Mass movement susceptibility prediction and infrastructural risk assessment (IRA) using GIS-based Meta classification algorithms

Cited by 5 publications

References 109 publications

Civil Integrated Management (CIM) for Advanced Level Applications to Transportation Infrastructure: A State-of-the-Art Review

Civil Integrated Management (CIM) for Advanced Level Applications to Transportation Infrastructure: A State-of-the-Art Review

Modeling climatic, terrain and soil factors using AHP in GIS for grapevines suitability assessment

GIS-Based Landslides Risk Assessment Applying Certainty Factor (CF) and Ensemble with Deep Learning Neural Network (DLNN): a Study of Cachar District of Assam, India

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