Article
Engineering, Electrical & Electronic
Pingheng Li
Summary: This study explores the pollution risk and resource utilization potential of vegetable waste on land resources through the analysis of remote sensing data and literature collection. By establishing a land use reference database and using geographical information system, key areas for controlling vegetable waste pollution are determined, and the possibility of waste utilization is compared. In addition, the study conducts a preliminary analysis of the causes and cumulative characteristics of polluted soil.
JOURNAL OF SENSORS
(2022)
Article
Environmental Sciences
Ali Polat
Summary: This study utilized the LSAT toolbox to produce landslide susceptibility maps for the Akincilar region, achieving prediction rates ranging from 70% to 73% using five different methods. LSAT proved to be effective in reducing time-consuming processes associated with constructing LSM, allowing for quick and automated data preparation, visualization of modeling results, and accuracy assessment of LSM.
ENVIRONMENTAL EARTH SCIENCES
(2021)
Article
Green & Sustainable Science & Technology
Jaydip Dey, Saurabh Sakhre, Ritesh Vijay, Hemant Bherwani, Rakesh Kumar
Summary: Landslides pose a significant challenge in mountainous regions like Nainital district in India, where geological structures make the area particularly susceptible. In order to mitigate the risk of landslides, susceptibility mapping using remote sensing and geographic information systems is crucial for identifying vulnerable areas and implementing appropriate measures.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2021)
Article
Environmental Studies
Minu Treesa Abraham, Neelima Satyam, Revuri Lokesh, Biswajeet Pradhan, Abdullah Alamri
Summary: Data driven methods such as Machine Learning algorithms are widely used for Landslide Susceptibility Mapping (LSM). The choice of algorithm and sampling strategy play crucial roles in obtaining accurate results. Random Forest, K Nearest Neighbors, and Support Vector Machine algorithms perform better than Naive Bayes and Logistic Regression, with the former three being more sensitive to sampling strategy and data points. Increasing data points leads to better performance for KNN, RF, and SVM algorithms, while NB and LR algorithms are less affected by sampling strategy and data splitting ratio.
Article
Engineering, Civil
Lei-Lei Liu, Can Yang, Xiao-Mi Wang
Summary: Machine learning models have been widely used for landslide susceptibility assessment, where feature selection plays a crucial role in reducing input variables and improving computational efficiency. This study compared the performance of 13 feature selection-based machine learning models with 5 ordinary machine learning models on LSA, demonstrating that RFE-optimized RF is the best FS-ML model.
GEOMECHANICS AND ENGINEERING
(2021)
Article
Computer Science, Information Systems
Masanori Kohno, Yuki Higuchi
Summary: Although it is difficult to implement preventive measures in all areas prone to dangerous landslides, this study conducted landslide susceptibility mapping along the entire slope of the Japanese archipelago using the analytical hierarchy process (AHP) method. It also extracted slopes with similar hazard/risk levels to areas where landslides have occurred in the past, based on ancient landslide topography. The obtained landslide susceptibility map showed good correspondence with landslide distribution and past occurrences, indicating the effectiveness of the method for prioritizing and implementing preventative measures.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2023)
Article
Chemistry, Multidisciplinary
Diego Renza, Elsa Adriana Cardenas, Estibaliz Martinez, Serena Sarah Weber
Summary: In this study, a new convolutional neural network architecture is proposed for evaluating landslide susceptibility, trained with data obtained through geological, geomorphological, and land use information. The method shows high performance with low computational cost and pixel-level accuracy on test data.
APPLIED SCIENCES-BASEL
(2022)
Article
Environmental Sciences
Long Nguyen Thanh, Yao-Min Fang, Tien-Yin Chou, Thanh-Van Hoang, Quoc Dinh Nguyen, Chen-Yang Lee, Chin-Lun Wang, Hsiao-Yuan Yin, Yi-Chia Lin
Summary: This study assessed the landslide susceptibility in a mountainous commune in Vietnam and created a landslide susceptibility zonation map. The map showed different levels of landslide susceptibility and could be considered reliable for practical use.
Article
Environmental Sciences
Muhittin Ozan Karaman, Saye Nihan Cabuk, Emrah Pekkan
Summary: Geographical information systems (GIS) were used to create landslide susceptibility maps in the Karaburun Peninsula in Izmir. This study provides important inputs for sustainable planning in the region.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Engineering, Environmental
Hamid Bourenane, Aghiles Abdelghani Meziani, Dalila Ait Benamar
Summary: The research validated and compared landslide susceptibility maps in the urban area of Azazga using four GIS-based statistical approaches. The study found that the FR method provided more accurate prediction in generating LSMs than the other three models, and all the statistical models showed good accuracy in landslide susceptibility mapping.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2021)
Article
Engineering, Civil
Yaser A. Nanehkaran, Yimin Mao, Mohammad Azarafza, Mustafa K. Kockar, Hong-Hu Zhu
Summary: Using fuzzy logic-based multi-criteria decision-making method, this study evaluated landslide hazard zonation in the Tabriz region of Iran. By identifying five main factors and creating hazard maps as well as susceptibility maps, risk zones were delineated, with high sensitivity areas identified in the northern parts of the region.
GEOMECHANICS AND ENGINEERING
(2021)
Article
Chemistry, Multidisciplinary
Gaetano Pecoraro, Gianfranco Nicodemo, Rosa Menichini, Davide Luongo, Dario Peduto, Michele Calvello
Summary: This paper presents a procedure to assess the risk level of stretches of roads exposed to slow-moving landslides at the municipal scale. It proposes an analysis method that combines landslide susceptibility maps, a road-damage database developed using Google Street View images, and ground-displacement measurements from satellite SAR images. The results demonstrate the importance of integrating these different approaches and data to understand the behavior of slow-moving landslides affecting road networks.
APPLIED SCIENCES-BASEL
(2023)
Article
Green & Sustainable Science & Technology
Zhu Liang, Wei Liu, Weiping Peng, Lingwei Chen, Changming Wang
Summary: This paper aims to explore a comprehensive model with high reliability, accuracy, and intelligibility for landslide susceptibility assessment (LSA) by combining statistical methods and ensemble learning techniques. The results indicate that the performance of the Stacking method is enhanced, and the basic classifiers (random forest, gradient boosting decision tree, and adaptive boosting decision tree) also perform well. Regions with a shorter distance to streams and roads and lower elevation are susceptible to landslide hazards.
Article
Geosciences, Multidisciplinary
Hassan Abedi Gheshlaghi, Bakhtiar Feizizadeh
Summary: This study proposed and verified an ensemble approach based on fuzzy system and bivariate statistics for landslide susceptibility assessment in Azarshahr Chay Basin, Iran. The FMV_IOE model showed the best performance in terms of sensitivity, accuracy, and specificity, with altitude, lithology, and slope degree identified as the main drivers of landslide occurrence based on the results of the IOE analysis.
Article
Engineering, Environmental
Jian Hu, Kaibin Xu, Genglong Wang, Youcun Liu, Muhammad Asim Khan, Yimin Mao, Maosheng Zhang
Summary: The study proposes a novel method for constructing landslide susceptibility maps using the OPTICS algorithm and Hausdorff distance. This approach effectively divides mapping units into multiple subclasses and categorizes them into five susceptibility levels based on landslide density values. Applying this method can significantly enhance the assessment of landslide susceptibility.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2021)
Article
Engineering, Environmental
J. Chacon, P. Alameda-Hernandez, E. Chacon, J. Delgado, R. El Hamdouni, P. Fernandez, T. Fernandez, J. M. Gomez-Lopez, C. Irigaray, J. Jimenez-Peralvarez, L. Llopis, J. Moya, F. Oloriz, J. A. Palenzuela
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2019)
Article
Environmental Sciences
Sabatino Buonanno, Giovanni Zeni, Adele Fusco, Michele Manunta, Maria Marsella, Paola Carrara, Riccardo Lanari
Article
Environmental Sciences
Peppe J. V. D'Aranno, Alessandro Di Benedetto, Margherita Fiani, Maria Marsella, Ilaria Moriero, Jose Antonio Palenzuela Baena
Summary: This study aims to analyze ground displacement using satellite remote sensing data and PSI technique to assess the stability of viaducts and embankments in the metropolitan area of the Gulf of Salerno, as well as understand the activity of the surrounding slopes. By utilizing data from European Space Agency missions and COSMO-SkyMed constellations, the analysis showed a consistency in displacement patterns in different subareas, highlighting the importance of remotely monitoring infrastructure behavior over long periods of time in a complex geological area.
Article
Environmental Sciences
Jose Francisco Guerrero Tello, Mauro Coltelli, Maria Marsella, Angela Celauro, Jose Antonio Palenzuela Baena
Summary: This paper focuses on the detection and segmentation of volcanic ash plumes using convolutional neural networks. The study provides a toolset for volcano monitoring to detect, segment, and track ash plume emissions through the processing and labeling of in situ images.
Article
Environmental Sciences
Angela Celauro, Jose Antonio Palenzuela Baena, Ilaria Moriero, Alexander Maass, Jose Francisco Guerrero Tello, Peppe Junior Valentino D'Aranno, Maria Marsella
Summary: The quarrying landscape in the southeast area of Rome was analyzed in terms of its dimensions, typology, preservation and interface with the urban environment. A geomatic methodology was used to combine information from air raids, historical aerial photographs, and recent satellite data to reconstruct the quarry landscape and identify patterns of exploitation and collapse. The relationship between these factors and ground instabilities and subsidence events was examined, revealing a spatial correlation between these multiple aspects.
Article
Construction & Building Technology
Felipe Orellana, Peppe J. V. D'Aranno, Silvia Scifoni, Maria Marsella
Summary: Monitoring structural stability in urban areas and infrastructure networks is crucial for population security. DInSAR technique provides precise measurements of building deterioration, and GIS application ensures long-term spatial and temporal records for effective management.
Article
Environmental Sciences
Felipe Orellana, Jose Manuel Delgado Blasco, Michael Foumelis, Peppe J. D'Aranno, Maria A. Marsella, Paola Di Mascio
Article
Water Resources
Jose Antonio Palenzuela Baena, John Soto Luzuriaga, Clemente Irigaray Fernandez
Article
Water Resources
Dario Costanzo, Clemente Irigaray
Article
Physics, Multidisciplinary
Saverio Avino, Enrico Calloni, Sergio Caprara, Martina De Laurentis, Rosario De Rosa, Tristano Di Girolamo, Luciano Errico, Gianluca Gagliardi, Marco Grilli, Valentina Mangano, Maria Antonietta Marsella, Luca Naticchioni, Giovanni Piero Pepe, Maurizio Perciballi, Gabriel Pillant, Paola Puppo, Piero Rapagnani, Fulvio Ricci, Luigi Rosa, Carlo Rovelli, Paolo Ruggi, Naurang L. Saini, Daniela Stornaiuolo, Francesco Tafuri, Arturo Tagliacozzo
Proceedings Paper
Architecture
A. Celauro, M. A. Marsella, P. J. D'Aranno, A. Maass, J. A. Palenzuela Baena, J. F. Guerrero Tello, I Moriero
2ND INTERNATIONAL CONFERENCE OF GEOMATICS AND RESTORATION (GEORES 2019)
(2019)
Article
Engineering, Environmental
John Soto, Jose Antonio Palenzuela, Jorge P. Galve, Juan Antonio Luque, Jose Miguel Azanon, Jose Tamay, Clemente Irigaray
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2019)