Article
Engineering, Multidisciplinary
Sandeep Panchal, Amit Kr Shrivastava
Summary: This study utilizes the analytic hierarchy process (AHP) model to create a landslide hazard map along national highway 5, taking into account multiple factors such as slope, geology, and distance from the road. The results of the study, validated by landslide inventory and prediction accuracy analysis, can be used by construction planners and decision makers.
AIN SHAMS ENGINEERING JOURNAL
(2022)
Article
Geosciences, Multidisciplinary
Gebremedhin Berhane, Abadi Gebrehiwot, Asmelash Abay
Summary: This research developed and evaluated a landslide susceptibility map in Ethiopia using two different approaches: frequency ratio and analytical hierarchy process. The study identified and mapped 175 past landslides and analyzed eight causative factors. The resulting landslide susceptibility maps provided valuable insights for landslide hazard mitigation and adaptation.
GEOMATICS NATURAL HAZARDS & RISK
(2023)
Article
Environmental Studies
Abhik Saha, Vasanta Govind Kumar Villuri, Ashutosh Bhardwaj
Summary: Landslide susceptibility maps are important for managing, planning, and mitigating landslides. In this study, an analytical hierarchy process (AHP), a fuzzy-AHP, and an artificial neural network (ANN) were used to construct landslide susceptibility maps for a region in West Bengal, India. The ANN model performed the best in terms of accuracy.
Article
Engineering, Aerospace
Flavie Laura Zangmene, Moussa Nsangou Ngapna, Moise Christian Balla Ateba, Germain Marie Monesperance Mboudou, Pascal Landry Wabo Defo, Rodrigue Tetang Kouo, Armand Kagou Dongmo, Sebastien Owona
Summary: The main goal of this study is to create a landslide susceptibility map of the Bafoussam-Dschang region (BDR) using the Analytical Hierarchical Process (AHP). Factors such as lithology, slope, soil, land use, flow density, curvature, elevation, and aspect were combined with field observations and plotted on GIS layers according to AHP principles. Field observations revealed 100 mass movements, including landslides, mudflows, rock falls, and collapses. These results help to identify the landslide susceptibility zones associated with the steep West Cameroon Highland.
ADVANCES IN SPACE RESEARCH
(2023)
Article
Environmental Sciences
Leyla Derin Cengiz, Murat Ercanoglu
Summary: A new data-driven fuzzy AHP method (FR-AHP) is proposed for landslide susceptibility mapping. The method is compared with FEA and FGM methods in a region in Turkey, and the AUC values are calculated. The results show that the FR-AHP method has the potential to be a feasible, objective, and high-performance approach.
ENVIRONMENTAL EARTH SCIENCES
(2022)
Article
Environmental Sciences
Pijus Kanti Ghosh, Sahina Khatun
Summary: The study delineated the rural-urban fringe of Krishnanagar city using Cronbach's alpha and MCDM through AHP, and found that the sharing and growth rate of built-up are high in the urban fringe. This suggests that the city has a significant influence on surrounding villages despite not being a metropolitan area.
GEOCARTO INTERNATIONAL
(2022)
Article
Environmental Sciences
Mantu Das, Tania Parveen, Deep Ghosh, Jiarul Alam
Summary: The study focuses on the availability of groundwater and human perceptions, with a specific focus on human adaptation behavior towards groundwater storage in drought-prone areas at the fringe of the Chhotanagpur plateau region. Through GWPZ mapping, the groundwater level in the study area was determined, and recommendations were made for best management practices such as rainfall harvesting and sustainable land use planning.
ENVIRONMENTAL EARTH SCIENCES
(2021)
Article
Geochemistry & Geophysics
Osman Salih Yilmaz
Summary: This study creates flood hazard susceptibility maps of Kastamonu province using geospatial and statistical methods, and evaluates flood risk. The results show that the AHP-FR ensemble method is more successful than the other two methods.
Article
Computer Science, Information Systems
Sandeep Panchal, Amit K. Shrivastava
Summary: This study compared three models, frequency ratio, Shannon's entropy, and AHP, for landslide susceptibility mapping in Shimla district, India. The frequency ratio model showed the highest accuracy, followed by Shannon's entropy, and AHP had the lowest accuracy. The results can be used by engineers and planners for better landslide management in the study area.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2021)
Article
Ecology
Manas Mondal, Subrata Haldar, Anupam Biswas, Somnath Mandal, Subhasis Bhattacharya, Suman Paul
Summary: The study assessed the multi-hazard risk in the coastal region of West Bengal, India, using multi-hazard modeling and analytical methods, finding that the western part of Sagar, Namkhana blocks and the south and eastern part of Pathar Pratima are most exposed to multi-hazards risk.
REGIONAL STUDIES IN MARINE SCIENCE
(2021)
Article
Environmental Studies
Zili Qin, Xinyao Zhou, Mengyao Li, Yuanxin Tong, Hongxia Luo
Summary: This study builds a landslide susceptibility mapping (LSM) method based on deep learning, which can effectively explore the complex relationship between landslides and their influencing factors, and accurately predict future landslide disasters. Different sampling methods and resampling operations were compared, and quantitative comparisons were made using various indices. The results show that the proposed methods can significantly improve the accuracy of the model, and all the deep learning models constructed in this study outperform traditional models in landslide susceptibility analysis.
Article
Green & Sustainable Science & Technology
Iris Bostjancic, Marina Filipovic, Vlatko Gulam, Davor Pollak
Summary: This paper presents a regional-scale 1:100,000 landslide-susceptibility map for Sisak-Moslavina County in Croatia for the first time, using a combination of frequency ratio and analytical hierarchy process to assess the spatial relationship between landslide occurrence and predictive factors. Limited LiDAR data is utilized to complete landslide inventories, resulting in the classification of the county into four susceptibility classes. The approach, although encouraging for primary regional-level studies, requires basic statistical analysis of predictive factors for accurate positioning of LiDAR polygons.
Article
Green & Sustainable Science & Technology
Jinxuan Zhou, Shucheng Tan, Jun Li, Jian Xu, Chao Wang, Hui Ye
Summary: China is actively promoting clean energy construction to achieve carbon neutrality. However, engineering constructions in mountainous regions are vulnerable to landslide disasters. Therefore, it is crucial to assess the susceptibility of landslide disasters for disaster prevention and risk management in construction projects. This study conducted a field survey at 42 landslide points in the selected planned site region and assessed landslide susceptibility based on 11 impact factors using AHP method. The resulting landslide susceptibility zone map showed high accuracy, with an AUC value of 0.845 according to the ROC curve analysis.
Article
Environmental Sciences
Nadia Eitvandi, Ramin Sarikhani, Somaye Derikvand
Summary: In this paper, a GIS-based spatial analysis method was used to create the landslide susceptibility (LS) map in the north of Lorestan province in western Iran. The integration of analytic hierarchy process (AHP), frequency ratio (FR), and fuzzy gamma operator (FGO) techniques was applied. The results can provide reliable information for landslide risk reduction strategies.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2022)
Article
Engineering, Aerospace
Fikret Saygin, Yasemin Sisman, Orhan Dengiz, Aziz Sisman
Summary: This study developed a landslide susceptibility map in the high-risk region of Atakum district, Samsun province, Turkey. The map was created using topographic, geological, land use, and soil indicators weighted by the Fuzzy-Analytic Hierarchy Process (Fuzzy-AHP) approach, and integrated with the Geographic Information System (GIS). The predictability of the susceptibility map was also assessed using the decision tree algorithm CHAID. The results showed high accuracy for the 'very low' and 'low' susceptibility classes, but lower accuracy for the 'high' class.
ADVANCES IN SPACE RESEARCH
(2023)
Article
Water Resources
Abhijit Manna, Ramkrishna Maiti
MINE WATER AND THE ENVIRONMENT
(2016)
Article
Geosciences, Multidisciplinary
Abhijit Manna, Ramkrishna Maiti
GEOSCIENCE FRONTIERS
(2018)
Article
Green & Sustainable Science & Technology
Sumanta Prakash Shee, Ramkrishna Maiti
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2019)
Article
Ecology
Rakesh Bera, Ramkrishna Maiti
REGIONAL STUDIES IN MARINE SCIENCE
(2019)
Article
Geosciences, Multidisciplinary
Hirak Kumar Mahata, Ramkrishna Maiti
JOURNAL OF THE GEOLOGICAL SOCIETY OF INDIA
(2019)
Article
Environmental Sciences
Abhishek Ghosh, Ramkrishna Maiti
Summary: This study aimed to predict severe soil erosion probability in the Mayurakshi river basin using LR, DT, and RF models. The analysis found that soil erosion is more likely in the undulating western parts of the basin compared to other sectors, with DT and RF models achieving higher prediction accuracy than LR model.
ENVIRONMENTAL EARTH SCIENCES
(2021)
Article
Environmental Sciences
Rakesh Bera, Ramkrishna Maiti
Summary: This study utilized GIS technology to assess coastal vulnerability in the Indian Sundarbans, finding that nearly half of the coastlines are in a state of moderate to very high vulnerability. Inhabited areas with high population densities were shown to be highly vulnerable, while uninhabited islands with lower elevations and a higher rate of sea level rise also faced high vulnerability.
ENVIRONMENTAL EARTH SCIENCES
(2021)
Article
Ecology
Rakesh Bera, Ramkrishna Maiti
Summary: The study conducted a comprehensive risk assessment of the Indian Sundarbans using GIS-based AHP method, revealing that around 26% and 23% of the population in the area are in high to very high risk categories. Factors such as higher effective sea level rise, lower tidal range, and high population densities are associated with increased risk levels in certain areas.
REGIONAL STUDIES IN MARINE SCIENCE
(2021)
Article
Ecology
Abhishek Ghosh, Ramkrishna Maiti
Summary: This study developed a new Ecological Susceptibility Index (ESI) for the Mayurakshi river in Eastern India and its adjacent corridors, using scientific analysis to predict the ecological geomorphological and aesthetic quality of the river and riparian corridor. The research found that anthropogenic factors have a greater impact on the river than other factors, and identified the lower-middle segments of the Mayurakshi river as highly susceptible to ecological changes.
ECOLOGICAL INFORMATICS
(2021)
Article
Geosciences, Multidisciplinary
Suman Bera, Ramkrishna Maiti
Summary: This study examines the availability of water flow in the transboundary Ganga river basin using the hydrological model SWAT. The results show that while the Ganga basin in India is rich in water annually, it still faces water shortage during the lean season, and the water flow in Bangladesh is significantly lower, impacting the overall water availability in the basin.
JOURNAL OF THE GEOLOGICAL SOCIETY OF INDIA
(2021)
Article
Water Resources
Abhishek Ghosh, Ramkrishna Maiti
Summary: The study aims to understand the morphological sensitivity of the Mayurakshi river due to eco-geomorphological variations and haphazard human interferences. The channel sensitivity is combinedly determined by natural geomorphic set-up, anthropogenic interventions, and resilience factors. High-resolution Google Earth Image and Global Positioning System were combinedly used to detect different forms of anthropogenic interferences.
INTERNATIONAL JOURNAL OF RIVER BASIN MANAGEMENT
(2022)
Article
Environmental Sciences
Prasenjit Bhunia, Pritha Das, Ramkrishna Maiti
EARTH SYSTEMS AND ENVIRONMENT
(2020)
Article
Environmental Sciences
Pravat Kumar Shit, Gouri Sankar Bhunia, Ramkrishna Maiti
MODELING EARTH SYSTEMS AND ENVIRONMENT
(2016)
Article
Environmental Sciences
Gouri Sankar Bhunia, Pravat Kumar Shit, Ramkrishna Maiti
MODELING EARTH SYSTEMS AND ENVIRONMENT
(2016)
Article
Environmental Sciences
Pravat Kumar Shit, Gouri Sankar Bhunia, Ramkrishna Maiti
MODELING EARTH SYSTEMS AND ENVIRONMENT
(2016)