Article
Environmental Sciences
Natsuki Kasahara, Yutaka Gonda, Nejan Huvaj
Summary: This study creates landslide distribution maps and land use maps using satellite imagery and Google Earth imagery, and analyzes the relationship between landslides and land use in Rize, Turkiye. The results show that landslides are more likely to occur in tea gardens than in forests.
Article
Geosciences, Multidisciplinary
Kamila Hodasova, Martin Bednarik
Summary: This study evaluates the impact of different weighting approaches in landslide susceptibility assessment. The bivariate statistical analysis used in the assessment requires careful weighting process, with weights calculated from the landslide index and frequency ratio showing the highest accuracy.ROC curves were used to verify the final susceptibility maps, with AUC values indicating the effectiveness of the different weighting methods.
Article
Engineering, Geological
Solomon Obiri Yeboah Amankwah, Guojie Wang, Kaushal Gnyawali, Daniel Fiifi Tawiah Hagan, Isaac Sarfo, Dong Zhen, Isaac Kwesi Nooni, Waheed Ullah, Duan Zheng
Summary: This study compares two state-of-the-art attention-boosted deep Siamese neural networks to map rainfall-induced landslides, and confirms the improvement in performance by attention networks. The Siamese Nested U-Net (SNUNet) achieved the best results, demonstrating its potential in rapid landslide mapping and disaster mitigation.
Article
Environmental Sciences
Shengwu Qin, Xu Guo, Jingbo Sun, Shuangshuang Qiao, Lingshuai Zhang, Jingyu Yao, Qiushi Cheng, Yanqing Zhang
Summary: This study introduced distant domain transfer learning (DDTL) methods for landslide detection and classification, incorporating an attention mechanism (AM-DDTL) to more effectively extract information from satellite images. Experimental results showed that DDTL method outperforms traditional CNN methods, with the AM-DDTL models achieving a classification accuracy of 94%.
Article
Engineering, Electrical & Electronic
Omid Ghorbanzadeh, Yonghao Xu, Hengwei Zhao, Junjue Wang, Yanfei Zhong, Dong Zhao, Qi Zang, Shuang Wang, Fahong Zhang, Yilei Shi, Xiao Xiang Zhu, Lin Bai, Weile Li, Weihang Peng, Pedram Ghamisi
Summary: This article presents the scientific outcomes of the 2022 Landslide4Sense competition organized by the Institute of Advanced Research in Artificial Intelligence. The competition aims to automatically detect landslides using large-scale satellite imagery and foster interdisciplinary research on deep learning models for semantic segmentation. The article details the best-performing algorithms and models, as well as advanced machine learning techniques and strategies employed. The benchmark dataset and accuracy assessment results are also described, inviting researchers to submit predictions and improve upon the presented landslide detection results.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Tsai-Tsung Tsai, Yuan-Jung Tsai, Chjeng-Lun Shieh, John Hsiao-Chung Wang
Summary: Typhoon Morakot had a serious impact on Taiwan, especially in terms of large-scale landslides (LSL). This study aimed to establish a specific relationship between LSL and triggering rainfall for future early warning predictions. By collecting various data, including satellite imagery, field investigation data, major event reports, and seismic data, the study analyzed rainfall/landslide depth and friction angle/slope through linear and non-linear regression analysis. The results showed that the non-linear regression analysis had a better correlation trend and could provide more conservative indicators for early warning management. Incorporating real-time rainfall forecasts, the study suggested that these indicators could be used to guide evacuation operations and improve response time.
Article
Engineering, Geological
Sheng Fu, Steven M. M. de Jong, Axel Deijns, Marten Geertsema, Tjalling de Haas
Summary: This study proposes a novel landslide dating technique called Segmented WAvelet-DEnoising and stepwise linear fitting (SWADE), which utilizes the Landsat archive to identify temporal changes in normalized difference vegetation index (NDVI) caused by landslides. SWADE detects sudden changes in NDVI values and estimates the most probable date ranges for landslide occurrences. The evaluation in a specific area revealed that SWADE can detect a significant percentage of landslides with maximum errors of 1 or 2 years, outperforming other dating methods. SWADE provides a promising fully automatic method for dating landslides in remote areas.
Article
Computer Science, Interdisciplinary Applications
Vignesh Kumar, Kiran Yarrakula
Summary: This study assessed the environmental impact in an open cast limestone mining region using satellite image processing techniques and field studies. Various methods and approaches were used to analyze and predict the environmental changes and impacts.
EARTH SCIENCE INFORMATICS
(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 Sciences
Floriane Provost, David Michea, Jean-Philippe Malet, Enguerran Boissier, Elisabeth Pointal, Andre Stumpf, Fabrizio Pacini, Marie-Pierre Doin, Pascal Lacroix, Catherine Proy, Philippe Bally
Summary: This article introduces a toolbox called MPIC-OPT for processing optical images, which is aimed at measuring terrain deformation over time. The toolbox provides an end-to-end solution and includes options such as correction and filtering to enhance the accuracy and precision of the measurements. The performance of MPIC-OPT is tested on various use cases and is shown to produce results consistent with in-situ data. The study also highlights the importance of correlation threshold and temporal matching range parameters in the estimation of terrain deformation.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Environmental Sciences
Mujeeb Rahman Atefi, Hiroyuki Miura
Summary: This study demonstrates the applicability of a nonlinear geometric correction technique for identifying and quantifying the affected area and volume of a large-scale landslide event in Afghanistan. The quality assessment confirmed the method's effectiveness by eliminating a large-scale of geometric errors.
Article
Computer Science, Artificial Intelligence
Antonio J. Rivera, Maria D. Perez-Godoy, David Elizondo, Lipika Deka, Maria J. del Jesus
Summary: This paper explores the performance of several unsupervised clustering algorithms for crop type identification in remote images, providing guidance and methods for building accurate and novel crop mapping models for remote sensing images.
Article
Energy & Fuels
Francisco J. Rodriguez-Benitez, Miguel Lopez-Cuesta, Clara Arbizu-Barrena, Maria M. Fernandez-Leon, Miguel A. Pamos-Urena, Joaquin Tovar-Pescador, Francisco J. Santos-Alamillos, David Pozo-Vazquez
Summary: This study proposes and evaluates methods for extending the forecasting horizon of all-sky imager (ASI)-based solar radiation nowcasts and improving the temporal resolution and latency of satellite-imagery-derived solar nowcasts. The results suggest that the use of ASI-based models provide low benefits compared to satellite-based models for point solar radiation nowcasting, and recommend the use of a simple smart persistence algorithm in combination with a low-resolution satellite nowcasting model based on the frequency of occurrence of different sky types in the study area.
Article
Environmental Sciences
Dil Kumar Rai, Xiong Donghong, Zhao Wei, Zhao Dongmei, Zhang Baojun, Nirmal Mani Dahal, Wu Yanhong, Muhammad Aslam Baig
Summary: Landslide distribution and susceptibility mapping are crucial for hazard and disaster risk management. This study investigates the landslide condition in the Dailekh district, Western Nepal, using inventory data and various contributing factors. The results show that both topographic and non-topographic factors significantly affect landslide occurrence and susceptibility in the Nepal Himalaya region. The reliability of the methods used for landslide susceptibility mapping is also verified.
CHINESE GEOGRAPHICAL SCIENCE
(2022)
Article
Engineering, Geological
Samuele Segoni, Yusuf Serengil, Fatih Aydin
Summary: This article investigates the adequacy of knowledge and technical level available before 2021 to calibrate an effective landslide early warning system (LEWS) in Rize province, Turkey. It proposes a prototypal version of a LEWS based on landslide and rainfall data from 1990 to 2020, and tests its effectiveness using events in 2021. The prototype proves to be an effective tool for managing landslide risk and is expected to be helpful in the future.
Article
Engineering, Environmental
Semih Ekercin, Cankut Ormeci
ENVIRONMENTAL ENGINEERING SCIENCE
(2008)
Article
Environmental Sciences
Bilgehan Nas, Hakan Karabork, Semih Ekercin, Ali Berktay
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2009)
Article
Environmental Sciences
Semih Ekercin, Cankut Ormeci
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2010)
Article
Environmental Sciences
Murat Kavurmaci, Semih Ekercin, Levent Altas, Yakup Kurmac
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2013)
Article
Environmental Sciences
Bilgehan Nas, Ali Berktay, Ahmet Aygun, Hakan Karabork, Semih Ekercin
ENVIRONMENTAL TECHNOLOGY
(2009)
Article
Green & Sustainable Science & Technology
Cenap Sancar
INTERNATIONAL JOURNAL OF SUSTAINABLE DEVELOPMENT AND WORLD ECOLOGY
(2010)
Article
Multidisciplinary Sciences
Osman Orhan, Semih Ekercin, Filiz Dadaser-Celik
SCIENTIFIC WORLD JOURNAL
(2014)
Article
Environmental Sciences
Bilgehan Nas, Semih Ekercin, Hakan Karabork, Ali Berktay, David J. Mulla
WATER AIR AND SOIL POLLUTION
(2010)
Article
Plant Sciences
Amjad Ur Rahman, Shujaul Mulk Khan, Zafeer Saqib, Zahid Ullah, Zeeshan Ahmad, Semih Ekercin, Abdul Samad Mumtaz, Habib Ahmad
PAKISTAN JOURNAL OF BOTANY
(2020)
Article
Construction & Building Technology
Habibe Acar, Aysel Yavuz, Engin Eroglu, Cengiz Acar, Cenap Sancar, Ahmet Salih Degermenci
Summary: With the increasing density of built spaces in urban areas, the importance of open spaces, particularly squares, has become more evident. This study in Trabzon, Turkey, aimed to determine user profiles, occupancy, facilities, and activity diversity at the Ataturk Plaza, highlighting the significance of diverse activities in urban squares for the quality of livable urban spaces. The research findings and analyses could serve as guidelines for future urban square and open space designs.
INDOOR AND BUILT ENVIRONMENT
(2021)
Article
Geosciences, Multidisciplinary
Osman Orhan, Murat Yakar, Semih Ekercin
ARABIAN JOURNAL OF GEOSCIENCES
(2020)
Article
Engineering, Geological
Osman Orhan, Filiz Dadaser-Celik, Semih Ekercin
INTERNATIONAL JOURNAL OF ENGINEERING AND GEOSCIENCES
(2019)
Article
Multidisciplinary Sciences
Cenap Sancar, Sanem Oezen Turan, Ali Lhsan Kadiogullari
SCIENTIFIC RESEARCH AND ESSAYS
(2009)