Article
Geosciences, Multidisciplinary
Xinfu Xing, Chenglong Wu, Jinhui Li, Xueyou Li, Limin Zhang, Rongjie He
Summary: The study introduces a revised logistic regression method for dynamic landslide susceptibility prediction under cumulative daily rainfall, achieving a high accuracy of 91.9% in the assessment of landslide susceptibility in Shenzhen. This method utilizes five kinds of cumulative daily rainfall and updates the susceptibility model with the latest landslide events.
Article
Geosciences, Multidisciplinary
G. S. Pradeep, M. V. Ninu Krishnan, H. Vijith
Summary: The landslide susceptibility of mountainous villages in the Western Ghats of Kerala was analyzed in this research by considering multiple landslide events. The contribution of various factors to terrain susceptibility was assessed using statistical techniques, and a landslide susceptibility zonation map was generated. The study also found that factors such as land use/land cover and rainfall have a significant impact on landslide occurrence.
Article
Environmental Sciences
Ke Wang, Yuhang Liu, Zhonghao Li, Fengyin Liu, Chao Ma, Yuhua Chen, Tong Liu
Summary: This study focuses on tuff landslides in southeast coastal areas in China. Based on the landslide in Qingtian County, the deformation behavior and influencing factors of tuff landslides are analyzed using monitoring data. The results provide important insights for landslide stability analysis and geological hazard warning.
ENVIRONMENTAL EARTH SCIENCES
(2023)
Article
Environmental Studies
Firre An Suprapto, Bambang Juanda, Ernan Rustiadi, Khursatul Munibah
Summary: Batu City in East Java has a thriving tourist area, but it is also susceptible to disasters and economic vulnerability. The objective of this study is to improve disaster risk management and enhance the capacity to respond to disasters through the strengthening of disaster risk reduction instruments. The research findings reveal different levels of vulnerability to five disasters in Batu City, and the local economic vulnerability is significantly influenced by three of these disasters.
Article
Environmental Sciences
Lanhai Li, Lamek Nahayo, Gabriel Habiyaremye, Mupenzi Christophe
Summary: This study compared the effectiveness of different models on landslide susceptibility mapping in Rwanda, and found that the Frequency Ratio (FR) method performed well in both training and prediction accuracy.
GEOCARTO INTERNATIONAL
(2022)
Article
Environmental Sciences
Jiao Wu, Ya Zhang, Liu Yang, Yongxian Zhang, Jun Lei, Meixia Zhi, Guorui Ma
Summary: This study explores the essential influencing factors of landslides and investigates the effects of different datasets on landslide susceptibility mapping (LSM) at different grid resolutions. The results show that relief degree of land surface (RDLS), SPI, and rainfall have significant effects on landslide occurrence, and the impact of grid resolution varies for different factors.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Environmental Sciences
Jiao Wu, Ya Zhang, Liu Yang, Yongxian Zhang, Jun Lei, Meixia Zhi, Guorui Ma
Summary: This study explores the essential influencing factors of landslides and investigates the effects of different datasets on landslide susceptibility mapping. The results show that relief degree of land surface, SPI, and rainfall have significant effects on landslide occurrence. The study also finds that the primary elements are less affected by the grid resolution, while the secondary elements are more affected. The SCC-RFFS-RF model achieves the highest accuracy at a resolution of 30 meters.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Environmental Sciences
Luis Fernando Salazar Gutierrez, Juan Carlos Menjivar Flores, Hernan Eduardo Martinez Carvajal
Summary: This study was conducted in the coffee-growing region of the Department of Caldas, Colombia, focusing on the factors affecting landslide susceptibility in the area. Using GIS technology and field surveys, it was found that factors such as slope, altitude, and geological units are closely related to landslides. The study provides valuable insights into landslide occurrence in coffee-growing regions.
ENVIRONMENTAL EARTH SCIENCES
(2021)
Article
Chemistry, Multidisciplinary
Elanni Affandi, Tham Fatt Ng, Joy J. Pereira, Ferdaus Ahmad, Vanessa J. Banks
Summary: This study developed a landslide susceptibility model for Kuala Lumpur, Malaysia, using a new spatial partitioning technique. The model showed good compatibility with landslide conditioning factors and had high predictive accuracy. Retrospective validation was conducted to reaffirm the model's capability, especially in situations where data quality is limited.
APPLIED SCIENCES-BASEL
(2023)
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
Geosciences, Multidisciplinary
Linya Peng, Yangjie Sun, Zhao Zhan, Wenzhong Shi, Min Zhang
Summary: This article presents an FR-weighted GeoDetector method that can improve the accuracy and computational efficiency of landslide susceptibility analysis by screening out the most relevant conditioning factors. The machine learning models trained with features filtered by this method achieve higher accuracy in landslide susceptibility analysis.
GEOMATICS NATURAL HAZARDS & RISK
(2023)
Article
Engineering, Environmental
Cheng Chen, Lei Fan
Summary: Understanding the probability of landslides is crucial for mitigating their impact. Machine learning and deep learning models can improve prediction accuracy by selecting important contributing factors. However, the effects of different factor selection methods on different models are not well understood.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2023)
Article
Medicine, Research & Experimental
Hirwa Nteyumwete, Alyssa M. Civantos, Gaelen B. Stanford-Moore, Jenny Yau, Gratien Tuyishimire, Josiane Umutoni, Victor Nyabyenda, Isaie Ncogoza, David A. Shaye
Summary: This study investigates the factors contributing to delays in head and neck cancer diagnosis at the University Teaching Hospital of Kigali (CHUK). The findings indicate that there are delays in both initial medical consultation and referral to the hospital. Financial reasons and visits to traditional healers are the main factors contributing to the delays.
Article
Engineering, Geological
Yu Zhuang, Aiguo Xing, Qiang Sun, Yuehua Jiang, Yaoming Zhang, Chunling Wang
Summary: On August 10, 2019, a large landslide caused by typhoon Lekima and heavy rainfall occurred in Yongjia County, Zhejiang, China, resulting in 32 deaths. The landslide was triggered by a combination of rock mass characteristics, wind load, heavy rainfall, and human activities. The presence of roots and cracks in the strongly weathered tuff allowed rainwater to infiltrate rapidly, destabilizing the slope. The landslide movement lasted for about 30 s with a maximum velocity of 21 m/s, generating an air blast and blocking the river, which led to a barrier lake disaster and the submersion of houses in the nearby village.
Article
Environmental Sciences
Taskin Kavzoglu, Alihan Teke, Elif Ozlem Yilmaz
Summary: This study proposed an ensemble deep learning architecture based on shared blocks to improve the prediction capability of individual deep learning models. The research found that the proposed model performed best in modeling landslide susceptibility in Trabzon province, Turkey, with up to 7% improvement in performance compared to individual DL models.
Article
Environmental Sciences
Lamek Nahayo, Felix Ndayisaba, Fidele Karamage, Jean Baptiste Nsengiyumva, Egide Kalisa, Richard Mind'je, Christophe Mupenzi, Lanhai Li
INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT
(2019)
Article
Public, Environmental & Occupational Health
Jean Baptiste Nsengiyumva, Geping Luo, Egide Hakorimana, Richard Mind'je, Aboubakar Gasirabo, Valentine Mukanyandwi
Article
Geosciences, Multidisciplinary
Richard Mind'je, Lanhai Li, Amobichukwu Chukwudi Amanambu, Lamek Nahayo, Jean Baptiste Nsengiyumva, Aboubakar Gasirabo, Mapendo Mindje
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2019)
Article
Green & Sustainable Science & Technology
Jean de Dieu Nambajimana, Xiubin He, Ji Zhou, Meta Francis Justine, Jinlin Li, Dil Khurram, Richard Mind'je, Gratien Nsabimana
Article
Ecology
Patient Mindje Kayumba, Yaning Chen, Richard Mind'je, Mapendo Mindje, Xiaoyang Li, Albert Poponi Maniraho, Adeline Umugwaneza, Solange Uwamahoro
Summary: The study predicts landscape changes and quantifies the Bayanbulak ecological risk evolution by assessing susceptibility-hazard indices. Results indicate a decline in water, meadow, and marsh areas, with an increase in wetland hazard and susceptibility. Overall, Bayanbulak's ecological risk is slightly evolving, highlighting the need to focus on factors driving land surface temperature increment and implement climate adaptation measures for ecosystem management.
Article
Environmental Sciences
Jiansheng Hao, Richard Mind'je, Yang Liu, Farong Huang, Hao Zhou, Lanhai Li
Summary: This study investigated the characteristics and hazards of different types of avalanches in the mid-altitude region of the Central Tianshan Mountains, using data collected over four snow seasons. Results showed that surface-layer dry snow avalanches had the highest avalanche hazard degree in the continental snow climate region, and the overall avalanche hazard exhibited a single peak pattern during the snow season, with the greatest hazard occurring in the second half of February.
JOURNAL OF ARID LAND
(2021)
Article
Water Resources
Hao Jiansheng, Richard Mind'je, Feng Ting, Li Lanhai
Summary: The study compared the performance of gravimetric and dielectric permittivity measurement systems in different snow conditions, finding differences in accuracy and precision between the two systems. This information can help field operators choose a more suitable measurement system based on snowpack characteristics to obtain reliable density data and optimize field measurements.
HYDROLOGY RESEARCH
(2021)
Article
Multidisciplinary Sciences
Edovia Dufatanye Umwali, Alishir Kurban, Alain Isabwe, Richard Mind'je, Hossein Azadi, Zengkun Guo, Madeleine Udahogora, Anathalie Nyirarwasa, Jeanine Umuhoza, Vincent Nzabarinda, Aboubakar Gasirabo, Gulnur Sabirhazi
Summary: This study used various methods including NSF-WQI, PCA, CA, and PLS-PM to assess the spatio-seasonal variation of water quality in Lake Muhazi, Rwanda. Results showed seasonal changes in water quality and identified significant influences of cropland on water quality parameters. Recommendations were made for sustainable land-use management decisions near the lake.
SCIENTIFIC REPORTS
(2021)
Article
Environmental Sciences
Patient Mindje Kayumba, Gonghuan Fang, Yaning Chen, Richard Mind'je, Yanan Hu, Sikandar Ali, Mapendo Mindje
Summary: This study adjusted the calibration mechanism of SEBAL's sensible heat flux to high-resolution satellite data and in-situ observations, successfully modeling energy fluxes and evapotranspiration in the Yanqi basin. The results demonstrated the competence of SEBAL in predicting vapor fluxes in this region with high accuracy.
Article
Biodiversity Conservation
Jeanine Umuhoza, Guli Jiapaer, Hanmin Yin, Richard Mind'je, Aboubakar Gasirabo, Vincent Nzabarinda, Edovia Dufatanye Umwali
Summary: This study analyzed the grassland carrying capacity dynamics in Tajikistan and Kyrgyzstan mountains using GIS and RS techniques, finding that the highest grassland carrying capacity was in summer and it increased from 2000 to 2015.
ECOLOGICAL INDICATORS
(2021)
Article
Engineering, Civil
Adeline Umugwaneza, Xi Chen, Tie Liu, Richard Mind'je, Aline Uwineza, Patient Mindje Kayumba, Solange Uwamahoro, Jeanine Umuhoza, Aboubakar Gasirabo, Albert Poponi Maniraho
Summary: This study identified suitable sites for rainwater harvesting in the Nyabugogo catchment using geospatial information and multi-criteria decision-making techniques. The results showed highly suitable areas for different types of rainwater harvesting systems, with surface runoff, sediment yield, and topography identified as key factors influencing suitability. Integration of geospatial and MCDM techniques proved to be a useful and efficient method for planning rainwater harvesting at a basin scale.
AQUA-WATER INFRASTRUCTURE ECOSYSTEMS AND SOCIETY
(2022)
Article
Environmental Sciences
Adeline Umugwaneza, Xi Chen, Tie Liu, Zhengyang Li, Solange Uwamahoro, Richard Mind'je, Edovia Dufatanye Umwali, Romaine Ingabire, Aline Uwineza
Summary: This study analyzed the impact of climate change on the water balance in the Nyabugogo catchment using downscaled global climate models and projected changes in streamflow and surface runoff under different emission scenarios. The findings suggest that future changes in hydrological components may lead to increased water stress, highlighting the importance of integrated water resource management in response to climate change.
Article
Environmental Sciences
Richard Mind'je, Lanhai Li, Patient Mindje Kayumba, Mapendo Mindje, Sikandar Ali, Adeline Umugwaneza
Summary: The study aimed to develop a hydrological modeling system for the Nyabarongo River catchment in Rwanda and assess its hydrological response to rainfall events through discharged flow and volume simulation. The model exhibited high performance in simulating peak flows and volumes, with satisfactory computing proficiency and accuracy under changing rainfall patterns. The findings provide insights into river flow mechanisms and can assist in establishing systems for river monitoring and early flood warning in Rwanda.
Article
Environmental Studies
Albert Poponi Maniraho, Richard Mind'je, Wenjiang Liu, Vincent Nzabarinda, Patient Mindje Kayumba, Lamek Nahayo, Adeline Umugwaneza, Solange Uwamahoro, Lanhai Li
Summary: The study examined the impact of land use and land cover dynamics on soil erosion risk in an agricultural area of Rwanda, utilizing a modified C-factor estimation approach. Results showed the need for urgent soil conservation planning in the region, with terracing identified as an effective practice for soil erosion control. The CvkA approach was found to provide reasonable soil loss prediction results in the western province of Rwanda.
