Pub Date : 2023-11-10DOI: 10.1080/19475705.2023.2279493
Ling Kang, Yunliang Wen, Liwei Zhou, Hao Chen, Jinwang Ye
Under global warming, the acceleration of the water cycle has increased the risk of drought in the Yellow River Basin. Revealing the drought driving mechanisms in the basin and understanding the risk situation of drought have become particularly important. This paper uses wavelet analysis and transfer entropy to analyze the drought driving mechanisms. In addition, an Improved Particle Swarm Optimization (IPSO) coupled with Long Short-Term Memory (LSTM) is used for drought risk prediction. The results are as follows: (1) Hydrological drought lags behind meteorological drought by 2–3 months, and they show two main periods on different time scales, which are 5–6 months and 8–14 months, respectively. (2) Rainfall, runoff, temperature, humidity, and vapor pressure are the main drought driving factors, with rainfall and humidity having the most significant impact. (3) The IPSO-LSTM model has improved the process of selecting model parameters based on empirical experiences in the LSTM model, improving the prediction accuracy by an average of 3.1%. This paper provides a scientific basis for water resource management and drought risk assessment in the basin, to better cope with future climate challenges.
{"title":"Drought driving mechanism and risk situation prediction based on machine learning models in the Yellow River Basin, China","authors":"Ling Kang, Yunliang Wen, Liwei Zhou, Hao Chen, Jinwang Ye","doi":"10.1080/19475705.2023.2279493","DOIUrl":"https://doi.org/10.1080/19475705.2023.2279493","url":null,"abstract":"Under global warming, the acceleration of the water cycle has increased the risk of drought in the Yellow River Basin. Revealing the drought driving mechanisms in the basin and understanding the risk situation of drought have become particularly important. This paper uses wavelet analysis and transfer entropy to analyze the drought driving mechanisms. In addition, an Improved Particle Swarm Optimization (IPSO) coupled with Long Short-Term Memory (LSTM) is used for drought risk prediction. The results are as follows: (1) Hydrological drought lags behind meteorological drought by 2–3 months, and they show two main periods on different time scales, which are 5–6 months and 8–14 months, respectively. (2) Rainfall, runoff, temperature, humidity, and vapor pressure are the main drought driving factors, with rainfall and humidity having the most significant impact. (3) The IPSO-LSTM model has improved the process of selecting model parameters based on empirical experiences in the LSTM model, improving the prediction accuracy by an average of 3.1%. This paper provides a scientific basis for water resource management and drought risk assessment in the basin, to better cope with future climate challenges.","PeriodicalId":51283,"journal":{"name":"Geomatics Natural Hazards & Risk","volume":" 1011","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135185930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-09DOI: 10.1080/19475705.2023.2273214
Harish Khali, Kishan Singh Rawat, Rajat Subhra Chatterjee
Slope movement, the surface expressions as seated scars are the variety of surface deformation mechanisms on the earth’s outer crust. These slow-deformation mechanisms can be visualized easily, if in-situ geotechnical observations, GNSS synopticity (regional), and space-borne (Microwave) spatio-temporal data structured and interpreted accordingly. Globally, several techniques are adapted for the slope failure analysis and their zonation. Thus, the most directed with geospatial technologies. Wide area assessment, mapping, and monitoring are some complex tasks only possible and could be addressed with the space borne datasets. Their outcomes help users to implement area strategies viz. in susceptibility and vulnerability. Landslide Susceptibility mapping (LSM) quantify the problem very effectively. In LSM, soft computing analytical skills among various participatory and triggering factors for the application of complex models are required for ground simulation. In this article critical review of LSM over Uttarakhand Himalaya was primarily focussed which analyze various sections including- participatory/triggering factors, datasets, different models, and validation practices. The study exhibits multiple avenues and future pathways for various research windows, such as LSM-SAR refinement, orographic climatic and changing factor relationship, high-quality data coupling with drone/Unmanned Aerial Vehicle (UAV) data, etc. Such analysis implicates the cost-effectiveness of strategies in effective planning and management.
{"title":"Dynamic association of slope movements in the Uttarakhand Himalaya: a critical review on the landslide susceptibility assessment","authors":"Harish Khali, Kishan Singh Rawat, Rajat Subhra Chatterjee","doi":"10.1080/19475705.2023.2273214","DOIUrl":"https://doi.org/10.1080/19475705.2023.2273214","url":null,"abstract":"Slope movement, the surface expressions as seated scars are the variety of surface deformation mechanisms on the earth’s outer crust. These slow-deformation mechanisms can be visualized easily, if in-situ geotechnical observations, GNSS synopticity (regional), and space-borne (Microwave) spatio-temporal data structured and interpreted accordingly. Globally, several techniques are adapted for the slope failure analysis and their zonation. Thus, the most directed with geospatial technologies. Wide area assessment, mapping, and monitoring are some complex tasks only possible and could be addressed with the space borne datasets. Their outcomes help users to implement area strategies viz. in susceptibility and vulnerability. Landslide Susceptibility mapping (LSM) quantify the problem very effectively. In LSM, soft computing analytical skills among various participatory and triggering factors for the application of complex models are required for ground simulation. In this article critical review of LSM over Uttarakhand Himalaya was primarily focussed which analyze various sections including- participatory/triggering factors, datasets, different models, and validation practices. The study exhibits multiple avenues and future pathways for various research windows, such as LSM-SAR refinement, orographic climatic and changing factor relationship, high-quality data coupling with drone/Unmanned Aerial Vehicle (UAV) data, etc. Such analysis implicates the cost-effectiveness of strategies in effective planning and management.","PeriodicalId":51283,"journal":{"name":"Geomatics Natural Hazards & Risk","volume":" 15","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135242589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-09DOI: 10.1080/19475705.2023.2279494
Ao Guo, Nan Jiang, Yan Xu, Tianhe Xu, Yuhao Wu, Song Li, Zhaorui Gao
The Sichuan Luding earthquake that struck on September 5, 2022 is one of the strongest earthquakes in China in recent years. The analysis of precipitable water vapor (PWV) retrieved from the ground-based global navigation satellite system (GNSS), surface pressure (SP), surface latent heat flux (SLHF), and land surface temperature (LST) from the reanalysis dataset was carried out in the epicenter and the nearby areas. The results show that PWV decreases distinctly and reaches the trough at the outburst with significant minimums of 43.21 mm and 37.84 mm over the nearest SCSM and SCTQ station from the epicenter. SLHF also has the same trend, and SP increased. Additionally, the LST analysis from two-temporal series was conducted to reveal that the Luding event accompanies by a low-temperature anomaly. Based on the background field established from the same period of the last ten years, LST at the epicenter on the day of occurrence was 5.68 °C lower than in previous years. Furthermore, the strongest low-temperature anomalies were observed from September 4 to 6, with the anomaly index of −1.95, −1.71, and −1.60, respectively. It is plain that the parameters from the land and atmosphere perform the anomalies at the minimum during the Luding earthquake.
{"title":"Co-seismic characterization analysis in PWV and land-atmospheric observations associated with Luding Ms 6.8 earthquake occurrence in China on September 5, 2022","authors":"Ao Guo, Nan Jiang, Yan Xu, Tianhe Xu, Yuhao Wu, Song Li, Zhaorui Gao","doi":"10.1080/19475705.2023.2279494","DOIUrl":"https://doi.org/10.1080/19475705.2023.2279494","url":null,"abstract":"The Sichuan Luding earthquake that struck on September 5, 2022 is one of the strongest earthquakes in China in recent years. The analysis of precipitable water vapor (PWV) retrieved from the ground-based global navigation satellite system (GNSS), surface pressure (SP), surface latent heat flux (SLHF), and land surface temperature (LST) from the reanalysis dataset was carried out in the epicenter and the nearby areas. The results show that PWV decreases distinctly and reaches the trough at the outburst with significant minimums of 43.21 mm and 37.84 mm over the nearest SCSM and SCTQ station from the epicenter. SLHF also has the same trend, and SP increased. Additionally, the LST analysis from two-temporal series was conducted to reveal that the Luding event accompanies by a low-temperature anomaly. Based on the background field established from the same period of the last ten years, LST at the epicenter on the day of occurrence was 5.68 °C lower than in previous years. Furthermore, the strongest low-temperature anomalies were observed from September 4 to 6, with the anomaly index of −1.95, −1.71, and −1.60, respectively. It is plain that the parameters from the land and atmosphere perform the anomalies at the minimum during the Luding earthquake.","PeriodicalId":51283,"journal":{"name":"Geomatics Natural Hazards & Risk","volume":" 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135290739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The digital twin of an earthquake disaster city constructed using digital twin technology can reflect the data of different stages of the earthquake disaster in the virtual space and can ensure high synchronisation and simulation of the two to effectively improve the safety of emergency rescue personnel and the scientific decision-making ability of decision makers. Oblique photogrammetry matched the Light Detection and Ranging (LiDAR) data to complete a high-precision three-dimensional real-scene model. The urban digital twin model was established as a module with the three-dimensional white model generated by the two-dimensional frame data with a fast update speed. Based on the shortest-fault-distance intensity-attenuation model, the seismic intensity was calculated using a known active fault and aftershock sequence, and the applicability of this method was verified. The elastic-plastic time history analysis method was used to calculate the seismic response of the building, and the seismic damage level was visualised using a three-dimensional model. The dynamic changes of earthquake disasters are monitored by sensors in real time and analysed in a digital twin model to provide an optimal scheme for earthquake emergency rescue and accurate evaluation results of earthquake disasters.
{"title":"Application research on digital twins of urban earthquake disasters","authors":"Sihan Yu, Qiyun Lei, Chao Liu, Nan Zhang, Shuaishuai Shan, Xiaoming Zeng","doi":"10.1080/19475705.2023.2278274","DOIUrl":"https://doi.org/10.1080/19475705.2023.2278274","url":null,"abstract":"The digital twin of an earthquake disaster city constructed using digital twin technology can reflect the data of different stages of the earthquake disaster in the virtual space and can ensure high synchronisation and simulation of the two to effectively improve the safety of emergency rescue personnel and the scientific decision-making ability of decision makers. Oblique photogrammetry matched the Light Detection and Ranging (LiDAR) data to complete a high-precision three-dimensional real-scene model. The urban digital twin model was established as a module with the three-dimensional white model generated by the two-dimensional frame data with a fast update speed. Based on the shortest-fault-distance intensity-attenuation model, the seismic intensity was calculated using a known active fault and aftershock sequence, and the applicability of this method was verified. The elastic-plastic time history analysis method was used to calculate the seismic response of the building, and the seismic damage level was visualised using a three-dimensional model. The dynamic changes of earthquake disasters are monitored by sensors in real time and analysed in a digital twin model to provide an optimal scheme for earthquake emergency rescue and accurate evaluation results of earthquake disasters.","PeriodicalId":51283,"journal":{"name":"Geomatics Natural Hazards & Risk","volume":"136 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135342514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A significant number of ionic rare earth tailings slopes were generated during the process of rare earth mining and the factor of safety of these slopes continued to decrease under the action of rainfall. This study focussed on a specific tailings slope located in Dayu County, Ganzhou City. Through the utilization of MatDEM numerical simulation software, the variations in infiltration distribution and destabilization evolution of the tailings slope between different seasons were comparatively examined. The results indicated that during the rainy season (May to June), increased rainfall led to increased rate of water infiltration, consequently reducing the stability of the slope and exacerbating landslide damage. Furthermore, the study provided analyses of safety distances under different seasons of rainfall, taking into account the geographical location of the tailings slope in Dayu County, Ganzhou City, and the results of the analyses provided theoretical foundation into ensuring the safety of buildings and residents downstream of the slope.
{"title":"Numerical simulation and safety distance analysis of slope instability of ionic rare earth tailings in different rainy seasons","authors":"Jiabo Geng, Zhisong Wang, Xiang Lan, Xiaoshuang Li, Dongming Zhang","doi":"10.1080/19475705.2023.2277127","DOIUrl":"https://doi.org/10.1080/19475705.2023.2277127","url":null,"abstract":"A significant number of ionic rare earth tailings slopes were generated during the process of rare earth mining and the factor of safety of these slopes continued to decrease under the action of rainfall. This study focussed on a specific tailings slope located in Dayu County, Ganzhou City. Through the utilization of MatDEM numerical simulation software, the variations in infiltration distribution and destabilization evolution of the tailings slope between different seasons were comparatively examined. The results indicated that during the rainy season (May to June), increased rainfall led to increased rate of water infiltration, consequently reducing the stability of the slope and exacerbating landslide damage. Furthermore, the study provided analyses of safety distances under different seasons of rainfall, taking into account the geographical location of the tailings slope in Dayu County, Ganzhou City, and the results of the analyses provided theoretical foundation into ensuring the safety of buildings and residents downstream of the slope.","PeriodicalId":51283,"journal":{"name":"Geomatics Natural Hazards & Risk","volume":"79 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135475857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The landslide morphology is quickly and accurately extracted from Unmanned Air Vehicle (UAV) images. It is of great significance for emergency rescue and quantitative evaluation of landslide disasters. However, due to the complexity of landslide morphology, choosing the reasonable extraction thresholds is a challenging issue. A threshold selection method of Topographic Profile along the Direction of Slope Movement (TP-DSM) was proposed. Firstly, a hierarchical extraction rule sets for landslide morphology was constructed by integrating multi-feature information such as spectral, texture, geometry, topography and space of UAV images. Second, TP-DSM was proposed to select the optimal elevation thresholds for classifying different landslide morphology. Finally, the thresholds were introduced into the rule sets to achieve effective extraction of landslide morphology. This study uses Digital Orthophoto Map (DOM) and Digital Elevation Model (DEM) generated by UAV images as data sources, and the landslide in Luquan County, Yunnan Province, China as the Study area, the results show that the overall accuracy (OA) of landslide morphology extraction was 89.58%, and the Kappa coefficient was 0.88, which is effective and more consistent with the reality. The proposed method can also be applied to other potential locations.
{"title":"Extraction of landslide morphology based on Topographic Profile along the Direction of Slope Movement using UAV images","authors":"Yujie Zhang, Jia Li, Jiajia Liu, Wenbin Xie, Ping Duan","doi":"10.1080/19475705.2023.2278276","DOIUrl":"https://doi.org/10.1080/19475705.2023.2278276","url":null,"abstract":"The landslide morphology is quickly and accurately extracted from Unmanned Air Vehicle (UAV) images. It is of great significance for emergency rescue and quantitative evaluation of landslide disasters. However, due to the complexity of landslide morphology, choosing the reasonable extraction thresholds is a challenging issue. A threshold selection method of Topographic Profile along the Direction of Slope Movement (TP-DSM) was proposed. Firstly, a hierarchical extraction rule sets for landslide morphology was constructed by integrating multi-feature information such as spectral, texture, geometry, topography and space of UAV images. Second, TP-DSM was proposed to select the optimal elevation thresholds for classifying different landslide morphology. Finally, the thresholds were introduced into the rule sets to achieve effective extraction of landslide morphology. This study uses Digital Orthophoto Map (DOM) and Digital Elevation Model (DEM) generated by UAV images as data sources, and the landslide in Luquan County, Yunnan Province, China as the Study area, the results show that the overall accuracy (OA) of landslide morphology extraction was 89.58%, and the Kappa coefficient was 0.88, which is effective and more consistent with the reality. The proposed method can also be applied to other potential locations.","PeriodicalId":51283,"journal":{"name":"Geomatics Natural Hazards & Risk","volume":"142 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135475985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-03DOI: 10.1080/19475705.2023.2275541
Giandomenico Mastrantoni, Claudia Masciulli, Roberta Marini, Carlo Esposito, Gabriele Scarascia Mugnozza, Paolo Mazzanti
In the context of population concentration in large cities, assessing the risks posed by geological hazards to enhance urban resilience is becoming increasingly important. This study introduces a robust and replicable procedure for assessing ground instability hazards and associated physical risks. Specifically, our comprehensive model integrates spatial hazard assessments, multi-satellite InSAR data, and physical features of the built environment to rank and prioritize assets facing multiple risks, with a focus on ground instabilities. The model generates risk scores based on hazard probability, potential damage, and displacement rates, aiding decision-makers in identifying high-risk buildings and implementing appropriate mitigation measures to reduce economic losses. The procedure was tested in Rome, Italy, where the analysis revealed that 60% of the examined buildings (90 × 103) are at risk of ground instability. Specifically, 33%, 22%, and 5% exhibit the highest multi-risk score for sinkholes, landslides, and subsidence, respectively. Landslide risk prevails among residential structures, while retail and office buildings face a higher risk of subsidence and sinkholes. Notably, our study identified a positive correlation between mitigation expenses and the multi-risk scores of nearby buildings, highlighting the practical implications of our findings for urban planning and risk management strategies.
{"title":"A novel model for multi-risk ranking of buildings at city level based on open data: the test site of Rome, Italy","authors":"Giandomenico Mastrantoni, Claudia Masciulli, Roberta Marini, Carlo Esposito, Gabriele Scarascia Mugnozza, Paolo Mazzanti","doi":"10.1080/19475705.2023.2275541","DOIUrl":"https://doi.org/10.1080/19475705.2023.2275541","url":null,"abstract":"In the context of population concentration in large cities, assessing the risks posed by geological hazards to enhance urban resilience is becoming increasingly important. This study introduces a robust and replicable procedure for assessing ground instability hazards and associated physical risks. Specifically, our comprehensive model integrates spatial hazard assessments, multi-satellite InSAR data, and physical features of the built environment to rank and prioritize assets facing multiple risks, with a focus on ground instabilities. The model generates risk scores based on hazard probability, potential damage, and displacement rates, aiding decision-makers in identifying high-risk buildings and implementing appropriate mitigation measures to reduce economic losses. The procedure was tested in Rome, Italy, where the analysis revealed that 60% of the examined buildings (90 × 103) are at risk of ground instability. Specifically, 33%, 22%, and 5% exhibit the highest multi-risk score for sinkholes, landslides, and subsidence, respectively. Landslide risk prevails among residential structures, while retail and office buildings face a higher risk of subsidence and sinkholes. Notably, our study identified a positive correlation between mitigation expenses and the multi-risk scores of nearby buildings, highlighting the practical implications of our findings for urban planning and risk management strategies.","PeriodicalId":51283,"journal":{"name":"Geomatics Natural Hazards & Risk","volume":"82 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135868830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-02DOI: 10.1080/19475705.2023.2275539
Junjie Dong, Ziqi Guo, Yindi Zhao, Mengfan Hu, Jiaxing Li
Analyzing and optimizing the spatio-temporal characteristics of terrestrial ecosystem carbon storage, as well as examining their coupling and coordination relationships with industrial mining land and landscape pattern, can become a reference in the pursuit of carbon peaking and carbon neutrality for mining cities. This research takes the typical mining city of Ordos as the study target. Based on the LULC, the Multi-objective Planning (MOP) and Patch-generating Land Use Simulation (PLUS) model are used to predict the LULC under the natural development (Q1), ecological protection (Q2) and economic development (Q3) scenarios of 2030, and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model is used to analyze the dynamics of carbon storage, finally a coupling coordination of industrial mining land, landscape pattern and carbon storage is constructed to investigate the interrelationship between them. The results show: (1) From 2000 to 2020, carbon storage shows an inverted ‘V’ shape of rising and then falling; (2) Compared to carbon storage in 2020, the Q1 demonstrates a decrease, while the Q2 and Q3 demonstrate increases; (3) From 2000 to 2020, the coupling coordination degree decreases, and in the future, Q2 and Q3 show an increase in it relative to the Q1.
{"title":"Coupling coordination analysis of industrial mining land, landscape pattern and carbon storage in a mining city: a case study of Ordos, China","authors":"Junjie Dong, Ziqi Guo, Yindi Zhao, Mengfan Hu, Jiaxing Li","doi":"10.1080/19475705.2023.2275539","DOIUrl":"https://doi.org/10.1080/19475705.2023.2275539","url":null,"abstract":"Analyzing and optimizing the spatio-temporal characteristics of terrestrial ecosystem carbon storage, as well as examining their coupling and coordination relationships with industrial mining land and landscape pattern, can become a reference in the pursuit of carbon peaking and carbon neutrality for mining cities. This research takes the typical mining city of Ordos as the study target. Based on the LULC, the Multi-objective Planning (MOP) and Patch-generating Land Use Simulation (PLUS) model are used to predict the LULC under the natural development (Q1), ecological protection (Q2) and economic development (Q3) scenarios of 2030, and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model is used to analyze the dynamics of carbon storage, finally a coupling coordination of industrial mining land, landscape pattern and carbon storage is constructed to investigate the interrelationship between them. The results show: (1) From 2000 to 2020, carbon storage shows an inverted ‘V’ shape of rising and then falling; (2) Compared to carbon storage in 2020, the Q1 demonstrates a decrease, while the Q2 and Q3 demonstrate increases; (3) From 2000 to 2020, the coupling coordination degree decreases, and in the future, Q2 and Q3 show an increase in it relative to the Q1.","PeriodicalId":51283,"journal":{"name":"Geomatics Natural Hazards & Risk","volume":"9 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135933966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-02DOI: 10.1080/19475705.2023.2272575
Lukas Schild, Thomas Scheiber, Paula Snook, Reza Arghandeh, Stig Frode Samnøy, Alexander Maschler, Lene Kristensen
Unstable rock slopes pose a hazard to inhabitants and infrastructure in their vicinity, necessitating advanced monitoring methodologies for timely risk assessment and mitigation. Recent geotechnical monitoring techniques often rely on sensor data fusion to enhance forecasting for imminent failures. Our investigation extends beyond a single sensor type to data fusion for heterogeneous sensor networks using a Multimodal Asynchronous Kalman Filter. We illustrate the application of the proposed method on a case study data set consisting of data from an on-site sensor network enriched by remote sensing data. Employing a Multimodal Asynchronous Kalman Filter, we capitalise on the distinct resolutions inherent in each sensor input. The outcome was a combined dataset with a high spatiotemporal resolution. Our approach facilitates the estimation of essential physical attributes for monitored objects, encompassing translation, rotation, velocities and accelerations. The case study site was an unstable rock section of ca. 50.000 m3 in Aurland, Norway, which collapsed as a multi-stage failure in July 2023. Our method can be transposed to various sites with distinct sensor networks, enhancing state estimations for objects on unstable rock slopes. These estimations can significantly improve applications such as risk assessment and robust early-warning systems, enhancing predictions of critical failure points.
{"title":"Multimodal Asynchronous Kalman Filter for monitoring unstable rock slopes","authors":"Lukas Schild, Thomas Scheiber, Paula Snook, Reza Arghandeh, Stig Frode Samnøy, Alexander Maschler, Lene Kristensen","doi":"10.1080/19475705.2023.2272575","DOIUrl":"https://doi.org/10.1080/19475705.2023.2272575","url":null,"abstract":"Unstable rock slopes pose a hazard to inhabitants and infrastructure in their vicinity, necessitating advanced monitoring methodologies for timely risk assessment and mitigation. Recent geotechnical monitoring techniques often rely on sensor data fusion to enhance forecasting for imminent failures. Our investigation extends beyond a single sensor type to data fusion for heterogeneous sensor networks using a Multimodal Asynchronous Kalman Filter. We illustrate the application of the proposed method on a case study data set consisting of data from an on-site sensor network enriched by remote sensing data. Employing a Multimodal Asynchronous Kalman Filter, we capitalise on the distinct resolutions inherent in each sensor input. The outcome was a combined dataset with a high spatiotemporal resolution. Our approach facilitates the estimation of essential physical attributes for monitored objects, encompassing translation, rotation, velocities and accelerations. The case study site was an unstable rock section of ca. 50.000 m3 in Aurland, Norway, which collapsed as a multi-stage failure in July 2023. Our method can be transposed to various sites with distinct sensor networks, enhancing state estimations for objects on unstable rock slopes. These estimations can significantly improve applications such as risk assessment and robust early-warning systems, enhancing predictions of critical failure points.","PeriodicalId":51283,"journal":{"name":"Geomatics Natural Hazards & Risk","volume":"31 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135974826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-01DOI: 10.1080/19475705.2023.2274810
Jianming Wang, Zihan Zhou, Wei Dou, Zhonghui Chen
Instability of the rock slopes in open pit mines during the excavation unloading is an increasingly serious problem in the field of slope engineering. To explain the mechanical mechanism of slope unloading damage from a theoretical point of view, a simplified mechanical model of slope excavation based on the theory of fracture mechanics and the rock strength damage criterion is established. The damage process of the slope under excavation disturbance is dynamically analyzed by combining the interstructural characteristics of the slope. The solution equations for the extent of the plastic zone at the end of the crack of the excavated slope and its propagation length are derived. Calculation method of unloaded slope stability coefficient is proposed based on the mechanical model of crack propagation. The results show that (1) the stress intensity factor (SIF) at crack end in the slope under the action of unloading was larger than that under the original condition. (2) The range of the plastic zone at crack end in the slope rock mass can be attributed to the slope height, inverse logarithmic function to the slope angle, positive proportional function to the crack length, and the periodic fluctuation function of the crack angle. (3) The slope safety factor (SF) was found to be negatively related with the slope angle, slope height, crack angle, and the crack length unloading factor and positively related with the friction factor. Finally, the reasonableness of the theoretical derivation is verified by an engineering case study.
{"title":"Theoretical unloading fracture mechanism and stability analysis of the slope rock masses in open-pit mines","authors":"Jianming Wang, Zihan Zhou, Wei Dou, Zhonghui Chen","doi":"10.1080/19475705.2023.2274810","DOIUrl":"https://doi.org/10.1080/19475705.2023.2274810","url":null,"abstract":"Instability of the rock slopes in open pit mines during the excavation unloading is an increasingly serious problem in the field of slope engineering. To explain the mechanical mechanism of slope unloading damage from a theoretical point of view, a simplified mechanical model of slope excavation based on the theory of fracture mechanics and the rock strength damage criterion is established. The damage process of the slope under excavation disturbance is dynamically analyzed by combining the interstructural characteristics of the slope. The solution equations for the extent of the plastic zone at the end of the crack of the excavated slope and its propagation length are derived. Calculation method of unloaded slope stability coefficient is proposed based on the mechanical model of crack propagation. The results show that (1) the stress intensity factor (SIF) at crack end in the slope under the action of unloading was larger than that under the original condition. (2) The range of the plastic zone at crack end in the slope rock mass can be attributed to the slope height, inverse logarithmic function to the slope angle, positive proportional function to the crack length, and the periodic fluctuation function of the crack angle. (3) The slope safety factor (SF) was found to be negatively related with the slope angle, slope height, crack angle, and the crack length unloading factor and positively related with the friction factor. Finally, the reasonableness of the theoretical derivation is verified by an engineering case study.","PeriodicalId":51283,"journal":{"name":"Geomatics Natural Hazards & Risk","volume":"37 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135220811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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