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1
Acar, M., M. T. Ozludemir, S. Erol, R. N. Celik, and T. Ayan. "Kinematic landslide monitoring with Kalman filtering." Natural Hazards and Earth System Sciences 8, no. 2 (March 13, 2008): 213–21. http://dx.doi.org/10.5194/nhess-8-213-2008.
Повний текст джерелаАнотація:
Abstract. Landslides are serious geologic disasters that threat human life and property in every country. In addition, landslides are one of the most important natural phenomena, which directly or indirectly affect countries' economy. Turkey is also the country that is under the threat of landslides. Landslides frequently occur in all of the Black Sea region as well as in many parts of Marmara, East Anatolia, and Mediterranean regions. Since these landslides resulted in destruction, they are ranked as the second important natural phenomenon that comes after earthquake in Turkey. In recent years several landslides happened after heavy rains and the resulting floods. This makes the landslide monitoring and mitigation techniques an important study subject for the related professional disciplines in Turkey. The investigations on surface deformations are conducted to define the boundaries of the landslide, size, level of activity and direction(s) of the movement, and to determine individual moving blocks of the main slide. This study focuses on the use of a kinematic deformation analysis based on Kalman Filtering at a landslide area near Istanbul. Kinematic deformation analysis has been applied in a landslide area, which is located to the north of Istanbul city. Positional data were collected using GPS technique. As part of the study, conventional static deformation analysis methodology has also been applied on the same data. The results and comparisons are discussed in this paper.
2
Reyes-Carmona, Cristina, Anna Barra, Jorge Galve, Oriol Monserrat, José Pérez-Peña, Rosa Mateos, Davide Notti, et al. "Sentinel-1 DInSAR for Monitoring Active Landslides in Critical Infrastructures: The Case of the Rules Reservoir (Southern Spain)." Remote Sensing 12, no. 5 (March 3, 2020): 809. http://dx.doi.org/10.3390/rs12050809.
Повний текст джерелаАнотація:
Landslides in reservoir contexts are a well-recognised hazard that may lead to dangerous situations regarding infrastructures and people’s safety. Satellite-based radar interferometry is proving to be a reliable method to monitor the activity of landslides in such contexts. Here, we present a DInSAR (Differential Interferometric Synthetic Aperture Radar) analysis of Sentinel-1 images that exemplifies the usefulness of the technique to recognize and monitor landslides in the Rules Reservoir (Southern Spain). The integration of DInSAR results with a comprehensive geomorphological study allowed us to understand the typology, evolution and triggering factors of three active landslides: Lorenzo-1, Rules Viaduct and El Arrecife. We could distinguish between rotational and translational landslides and, thus, we evaluated the potential hazards related to these typologies, i.e., retrogression (Lorenzo-1 and Rules Viaduct landslides) or catastrophic slope failure (El Arrecife Landslide), respectively. We also observed how changes in the water level of the reservoir influence the landslide’s behaviour. Additionally, we were able to monitor the stability of the Rules Dam as well as detect the deformation of a highway viaduct that crosses a branch of the reservoir. Overall, we consider that other techniques must be applied to continue monitoring the movements, especially in the El Arrecife Landslide, in order to avoid future structural damages and fatalities.
3
Zhu, Yaru, Haijun Qiu, Zijing Liu, Jiading Wang, Dongdong Yang, Yanqian Pei, Shuyue Ma, Chi Du, Hesheng Sun, and Luyao Wang. "Detecting Long-Term Deformation of a Loess Landslide from the Phase and Amplitude of Satellite SAR Images: A Retrospective Analysis for the Closure of a Tunnel Event." Remote Sensing 13, no. 23 (November 29, 2021): 4841. http://dx.doi.org/10.3390/rs13234841.
Повний текст джерелаАнотація:
Information about the long-term spatiotemporal evolution of landslides can improve the understanding of landslides. However, since landslide deformation characteristics differ it is difficult to monitor the entire movement of a landslide using a single method. The Interferometric Synthetic Aperture Radar (InSAR) and pixel offset tracking (POT) method can complement each other when monitoring deformation at different landslide stages. Therefore, the InSAR and improved POT method were adapted to study the pre- and post-failure surface deformation characteristics of the Gaojiawan landslide to deepen understanding of the long-term spatiotemporal evolution characteristics of landslides. The results show that the deformation displacement gradient of the Gaojiawan landslide exhibited rapid movement that exceeded the measurable limit of InSAR during the first disaster. Moreover, the Gaojiawan landslide has experienced long-term creep, and while studying the post-second landslide’s failure stability, the acceleration trend was identified via time series analysis, which can be used as a precursor signal for landslide disaster warning. Our study aims to provide scientific reference for local governments to help prevent and mitigate geological disasters in this region.
4
Weiguo, Li, Liu Yali, Chen Yanhong, and Yang Libing. "Shock and Vibration of Rainfall on Rotational Landslide and Analysis of Its Deformation Characteristics." Geofluids 2021 (October 11, 2021): 1–12. http://dx.doi.org/10.1155/2021/4119414.
Повний текст джерелаАнотація:
Earthquake, flood, human activity, and rainfall are some of the trigger factors leading to landslides. Landslide monitoring data analysis indicates the deformation characteristics of landslides and helps to reduce the threat of landslide disasters. There are monitoring methods that enable efficient acquisition of real-time data to facilitate comprehensive research on landslides. However, it is challenging to analyze large amounts of monitoring data with problems like missing data and outlier data during data collection and transfer. These problems also hinder practical analysis and determination concerning the uncertain monitoring data. This work analyzes and processes the deformation characteristics of a rainfall-induced rotational landslide based on exploratory data analysis techniques. First, we found that the moving average denoising method is better than the polynomial fitting method for the repair and fitting of monitoring data. Besides, the exploratory data analysis of the Global Navigation Satellite System (GNSS) monitoring data reveals that the distribution of GNSS monitoring points has a positive correlation with the deformational characteristics of a rotational landslide. Our findings in the subsequent case study indicate that rainfalls are the primary trigger of the Zhutoushan landslide, Jiangsu Province, China. Therefore, this method provides support for the analysis of rotational landslides and more useful landslide monitoring information.
5
Zou, Yong, and Chao Zheng. "A Scientometric Analysis of Predicting Methods for Identifying the Environmental Risks Caused by Landslides." Applied Sciences 12, no. 9 (April 25, 2022): 4333. http://dx.doi.org/10.3390/app12094333.
Повний текст джерелаАнотація:
The effects of a landslide can represent a very big problem, including the death of people, damage to the land, environmental pollution and the loss of natural resources. Landslides are the most important medium for transferring sediments and polluting waterways by earth and organic materials. An excess of sediments reduces the quality of fish habitat and the potability of water. In order to understand landslides in depth, a thorough study was conducted using a scientometric analysis, as well as a thorough practical examination of landslide analysis and monitoring techniques. This review focused on methods used for landslide analysis, including physical models requiring easily prepared event-based landslide inventory, probabilistic methods which are useful for both shallow and earthquake-based landslides, and landslide monitoring performed by remote sensing techniques, which provide data helpful for prediction, monitoring and mapping. The fundamental principles of each method are described in terms of the method used, and its advantages, and limits. People and infrastructure are at danger from landslides caused by heavy rain, so this report highlights landslide-prone regions and considers the analysis methods for landslides used in these countries, with a view to identifying mitigation measures for coping with landslide risks in hilly areas. Furthermore, future landslide research possibilities, as well as possible modeling methods, are addressed. The report summarizes some landslide prediction and monitoring techniques used in landslide-prone countries which can help inform researchers seeking to protect the public from danger in landslide areas.
6
Zou, Yong, and Chao Zheng. "A Scientometric Analysis of Predicting Methods for Identifying the Environmental Risks Caused by Landslides." Applied Sciences 12, no. 9 (April 25, 2022): 4333. http://dx.doi.org/10.3390/app12094333.
Повний текст джерелаАнотація:
The effects of a landslide can represent a very big problem, including the death of people, damage to the land, environmental pollution and the loss of natural resources. Landslides are the most important medium for transferring sediments and polluting waterways by earth and organic materials. An excess of sediments reduces the quality of fish habitat and the potability of water. In order to understand landslides in depth, a thorough study was conducted using a scientometric analysis, as well as a thorough practical examination of landslide analysis and monitoring techniques. This review focused on methods used for landslide analysis, including physical models requiring easily prepared event-based landslide inventory, probabilistic methods which are useful for both shallow and earthquake-based landslides, and landslide monitoring performed by remote sensing techniques, which provide data helpful for prediction, monitoring and mapping. The fundamental principles of each method are described in terms of the method used, and its advantages, and limits. People and infrastructure are at danger from landslides caused by heavy rain, so this report highlights landslide-prone regions and considers the analysis methods for landslides used in these countries, with a view to identifying mitigation measures for coping with landslide risks in hilly areas. Furthermore, future landslide research possibilities, as well as possible modeling methods, are addressed. The report summarizes some landslide prediction and monitoring techniques used in landslide-prone countries which can help inform researchers seeking to protect the public from danger in landslide areas.
7
Zou, Yong, and Chao Zheng. "A Scientometric Analysis of Predicting Methods for Identifying the Environmental Risks Caused by Landslides." Applied Sciences 12, no. 9 (April 25, 2022): 4333. http://dx.doi.org/10.3390/app12094333.
Повний текст джерелаАнотація:
The effects of a landslide can represent a very big problem, including the death of people, damage to the land, environmental pollution and the loss of natural resources. Landslides are the most important medium for transferring sediments and polluting waterways by earth and organic materials. An excess of sediments reduces the quality of fish habitat and the potability of water. In order to understand landslides in depth, a thorough study was conducted using a scientometric analysis, as well as a thorough practical examination of landslide analysis and monitoring techniques. This review focused on methods used for landslide analysis, including physical models requiring easily prepared event-based landslide inventory, probabilistic methods which are useful for both shallow and earthquake-based landslides, and landslide monitoring performed by remote sensing techniques, which provide data helpful for prediction, monitoring and mapping. The fundamental principles of each method are described in terms of the method used, and its advantages, and limits. People and infrastructure are at danger from landslides caused by heavy rain, so this report highlights landslide-prone regions and considers the analysis methods for landslides used in these countries, with a view to identifying mitigation measures for coping with landslide risks in hilly areas. Furthermore, future landslide research possibilities, as well as possible modeling methods, are addressed. The report summarizes some landslide prediction and monitoring techniques used in landslide-prone countries which can help inform researchers seeking to protect the public from danger in landslide areas.
8
Yan, Shanshan, Liang Xue, Tianyang Liang, Yankai Hou, Hanlu Liu, and Hongxian Shan. "Research on Submarine landslide monitoring and early warning system." E3S Web of Conferences 257 (2021): 03016. http://dx.doi.org/10.1051/e3sconf/202125703016.
Повний текст джерелаАнотація:
Monitoring and early warning of submarine landslides could provide instant predictions for landslides, which is to avoid the destructive damage of submarine facilities such as pipelines and optical cable, etc effectively. However, researches on submarine landslide focus on numerical simulation and laboratory test, lacking support of in-situ observation data. This paper established the submarine landslide monitoring and early warning system by combining real-time monitoring data with web network platform and database technique. Based on the computational analysis of key monitoring parameters in the process of seabed deformation and sliding, the system has realized the accurate prediction and early warning of submarine landslides. The system has been applied to the submarine landslide monitoring in Zhoushan sea area, Zhejiang province, China, which has ensured the safety of offshore platforms and submarine projects in this area. The establishment of this system provides a new idea and method for submarine landslide warning.
9
Setiawan, Tedy, Fatkhan, and Ramadhani Yasyfi Cysela. "Landslide Monitoring using Inclinometer with Micro Electromechanical System (MEMS)." IOP Conference Series: Earth and Environmental Science 873, no. 1 (October 1, 2021): 012024. http://dx.doi.org/10.1088/1755-1315/873/1/012024.
Повний текст джерелаАнотація:
Abstract Being located on the Pacific Ring of Fire and a tectonically active country, Indonesia has to cope with the constant risk of volcanic eruptions, earthquakes, floods and landslides. Landslides and other mass movements are serious geo-environmental hazards in Indonesia. Following report from the Indonesia National Disaster Management Authority (BNPB), landslides are among high disaster death toll throughout the archipelago. It claimed 248 lives last year alone. The number of landslides in Indonesia increase steadily to 376 in 2014 from 291 in 2012. Hence, landslide monitoring system is required to determine style of landslide movement, for risk and even emergency risk management assessments and to assist with the design of mitigation works. A landslide instrumentation program including an inclinometer is designed for landslide monitoring. The inclinometer, or tilt sensor, is an instrument used for measuring slope, tilt, or inclination. In this paper we use Micro Electromechanical System (MEMS) as a sensor to measure changes in an angle. Then information is transferred to a central server soon after real-time accelerations are monitored. A data logger also used as a data recording. With low-cost MEMS accelerometers, the results show this instrument is able to provide reliable ground-motion data in network-scale deployments.
10
Sladic, Dubravka, Milan Vrtunski, Ivan Alargic, Aleksandra Ristic, and Dusan Petrovacki. "Development of geoportal for landslide monitoring." Glasnik Srpskog geografskog drustva 92, no. 4 (2012): 63–78. http://dx.doi.org/10.2298/gsgd1204063s.
Повний текст джерелаАнотація:
The paper presents the implementation of geoportal for landslide monitoring which which includes two subsystems: a system for acquisition, storage and distribution of data on landslides and real time alert system. System for acquisition, storage and distribution of data on landslides include raster and vector spatial data on landslides affected areas, as well as metadata. Alert system in real time is associated with a sensor for detecting displacement, which performs constant measurements and signals in case of exceeding the reference value. The system was developed in accordance with the standards in the field of GIS: ISO 19100 series of standards and OpenGIS Consortium and is based on service-oriented architecture and principles of spatial data infrastructures.
11
Zaalishvili, Vladislav, and Dmitry Melkov. "Anthropogenic landslide geodetic monitoring." E3S Web of Conferences 281 (2021): 09015. http://dx.doi.org/10.1051/e3sconf/202128109015.
Повний текст джерелаАнотація:
The first results of monitoring the slow dynamics of an anthropogenic landslide located in the mountainous part of the Republic of North Ossetia-Alania are presented in the article. Landslide motion measurements were performed using tacheometric surveying and the GPS/GLONASS global positioning system. The article considers the selection of sites for installation the basic network points for landslides monitoring.
12
Dabiri, Z., D. Hölbling, L. Abad, G. Prasicek, A. L. Argentin, and T. T. Tsai. "AN OBJECT-BASED APPROACH FOR MONITORING THE EVOLUTION OF LANDSLIDE-DAMMED LAKES AND DETECTING TRIGGERING LANDSLIDES IN TAIWAN." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W8 (August 20, 2019): 103–8. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w8-103-2019.
Повний текст джерелаАнотація:
<p><strong>Abstract.</strong> In August 2009, Typhoon Morakot caused a record-breaking rainfall in Taiwan. The heavy rainfall triggered thousands of landslides, in particular in the central-southern part of the island. Large landslides can block rivers and can lead to the formation of landslide-dammed lakes. Cascading hazards like floods and debris flows after landslide dam breaches pose a high risk for people and infrastructure downstream. Thus, better knowledge about landslides that significantly impact the channel system and about the resulting landslide-dammed lakes are key elements for assessing the direct and indirect hazards caused by the moving mass. The main objectives of this study are 1) to develop an object-based image analysis (OBIA) approach for semi-automated detection of landslides that caused the formation of landslide-dammed lakes and 2) to monitor the evolution of landslide-dammed lakes based on Landsat imagery. For landslide and lake mapping, primarily spectral indices and contextual information were used. By integrating morphological and hydrological parameters derived from a digital elevation model (DEM) into the OBIA framework, we automatically identified landslide-dammed lakes, and the landslides that likely caused the formation of those lakes, due to the input of large amounts of debris into the channel system. The proposed approach can be adapted to other remote sensing platforms and can be used to monitor the evolution of landslide-dammed lakes and triggering landslides at regional scale after typhoon and heavy rainstorm events within an efficient time range after suitable remote sensing data has been provided.</p>
13
Ma, Deming, Yongsheng Li, Jianwei Cai, Bingquan Li, Yanxiong Liu, and Xingguo Chen. "Real-Time Diagnosis of Island Landslides Based on GB-RAR." Journal of Marine Science and Engineering 8, no. 3 (March 12, 2020): 192. http://dx.doi.org/10.3390/jmse8030192.
Повний текст джерелаАнотація:
Landslides are one of the most frequent and serious geological disasters that threaten people’s lives and property safety. In recent years, with the rapid development of the coastal economy and the increasingly strained spatial resources, the island development activities have become extremely rapid, resulting in the frequent occurrence of landslides on the island. We selected Beichangshan Island in the north of China as the research area. By using high-precision ground-based real aperture radar (GB-RAR) measurement technology, the displacement changes of potential landslides are monitored continuously and dynamically to realize the real-time diagnosis and early warning of island landslides. At the same time, the data interpretation method and key processing flow are described in detail. The results show that during the whole monitoring process, an area of obvious change is found, which is mainly located in the middle of the landslide mass. The mean velocity rate shows a nonlinear deformation trend. The maximum deformation of the landslide in the five selected points reaches 4.5 mm, which indicates that the area is in an unstable stage. The deformation monitoring ability of GB-RAR technology to identify the sub-millimeter level is demonstrated, and the monitoring method is verified. The validity and reliability of the method can be applied to real-time dynamic fine deformation diagnosis of island landslides. Its accuracy can meet the needs of dynamic change monitoring of island landslides, and it can become an important tool and means for early warning and treatment of landslides. The research is conducive to further enriching and improving the monitoring method system of island geological disasters in China, provides a scientific basis and technical support for early warning and disaster prevention and mitigation of island landslides, and can be popularized and applied in the monitoring of island landslides.
14
Liang, Jingtao, Jihong Dong, Su Zhang, Cong Zhao, Bin Liu, Lei Yang, Shengwu Yan, and Xiaobo Ma. "Discussion on InSAR Identification Effectivity of Potential Landslides and Factors That Influence the Effectivity." Remote Sensing 14, no. 8 (April 18, 2022): 1952. http://dx.doi.org/10.3390/rs14081952.
Повний текст джерелаАнотація:
The southwest mountainous area of China is one of the areas with the most landslides in the world. In this paper, we used Ya’an City and Garzê Tibetan Autonomous Prefecture in Sichuan Province as the research areas to explore the identification application effects of large-area potential landslides using synthetic aperture radar (SAR) data with different wavelength types (Sentinel-1, ALOS-2), different processing methods (SBAS-InSAR, Stacking-InSAR), and different geological environmental conditions. The results show the following: (1) The effect of identifying landslides with different slope directions is largely affected by the satellite orbit direction; when we identify landslide hazards across a large area, the joint monitoring mode of ascending and descending orbit data is required. (2) The period of monitoring affects the identification effect of potential landslides when landslide identification is carried out in southwestern China; the InSAR monitoring period is recommended to be more than 2 years. (3) In different geological environmental regions, SBAS technology and Stacking technology have their own advantages; Stacking technology identifies more potential landslides, and SBAS technology identifies potential landslides with higher accuracy; (4) the degree of vegetation coverage has a great impact on the landslide identification effect of different SAR data sources. In low-density vegetation coverage areas, the landslide identification result using Sentinel-1 data seems to be better than the result using ALOS-2 data. In high-density vegetation coverage areas, the landslide identification result using ALOS-2 data is better than that using Sentinel-1 data.
15
Aslan, Gokhan, Michael Foumelis, Daniel Raucoules, Marcello De Michele, Severine Bernardie, and Ziyadin Cakir. "Landslide Mapping and Monitoring Using Persistent Scatterer Interferometry (PSI) Technique in the French Alps." Remote Sensing 12, no. 8 (April 20, 2020): 1305. http://dx.doi.org/10.3390/rs12081305.
Повний текст джерелаАнотація:
Continuous geodetic measurements in landslide prone regions are necessary to avoid disasters and better understand the spatiotemporal and kinematic evolution of landslides. The detection and characterization of landslides in high alpine environments remains a challenge associated with difficult accessibility, extensive coverage, limitations of available techniques, and the complex nature of landslide process. Recent studies using space-based observations and especially Persistent Scatterer Interferometry (PSI) techniques with the integration of in-situ monitoring instrumentation are providing vital information for an actual landslide monitoring. In the present study, the Stanford Method for Persistent Scatterers InSAR package (StaMPS) is employed to process the series of Sentinel 1-A and 1-B Synthetic Aperture Radar (SAR) images acquired between 2015 and 2019 along ascending and descending orbits for the selected area in the French Alps. We applied the proposed approach, based on extraction of Active Deformation Areas (ADA), to automatically detect and assess the state of activity and the intensity of the suspected slow-moving landslides in the study area. We illustrated the potential of Sentinel-1 data with the aim of detecting regions of relatively low motion rates that be can attributed to activate landslide and updated pre-existing national landslide inventory maps on a regional scale in terms of slow moving landslides. Our results are compared to pre-existing landslide inventories. More than 100 unknown slow-moving landslides, their spatial pattern, deformation rate, state of activity, as well as orientation are successfully identified over an area of 4000 km2 located in the French Alps. We also address the current limitations due the nature of PSI and geometric characteristic of InSAR data for measuring slope movements in mountainous environments like Alps.
16
Wu, Chuan, and Guo Jun Wen. "Remote Monitoring System for Landslides Based on GSM Networks." Advanced Materials Research 562-564 (August 2012): 1891–94. http://dx.doi.org/10.4028/www.scientific.net/amr.562-564.1891.
Повний текст джерелаАнотація:
Geological disasters of landslides happen occasionally because of some frequent and no planning mining activities, infrastructure construction, or geological causes. Aimed to the disadvantages of existing manual searching method for landslides, a kind of landslide remote monitoring system using mobile GSM network for data transmission is designed and tested. The experimental result shows that the launch and receiving terminal of remote monitoring system are feasible.
17
Jakopec, Ivan, Ante Marendić, and Igor Grgac. "A NOVEL APPROACH TO LANDSLIDE MONITORING BASED ON UNMANNED AERIAL SYSTEM PHOTOGRAMMETRY." Rudarsko-geološko-naftni zbornik 37, no. 5 (2022): 83–101. http://dx.doi.org/10.17794/rgn.2022.5.8.
Повний текст джерелаАнотація:
Landslides represent great dangers that can cause fatalities and huge property damage. To prevent or reduce all possible consequences that landslides cause, it is necessary to know the kinematics of the surface and undersurface sliding masses. Geodetic surveying techniques can be used for landslide monitoring and creating a kinematic model of the landslide. One of the most used surveying techniques for landslide monitoring is the photogrammetric survey by Unmanned Aerial System. The results of the photogrammetric survey are dense point clouds, digital terrain models, and digital orthomosaic maps, where landslide displacements can be determined by comparing these results in two measurement epochs. This paper presents a new data processing method with a novel approach for calculating landslide displacements based on Unmanned Aerial System photogrammetric survey data. The main advantage of the new method is that it does not require the production of dense point clouds, digital terrain models, or digital orthomosaic maps to determine displacements. The applicability and accuracy of the new method were tested in a test field with simulated displacements of known values within the range of 20-40 cm in various directions. The new method successfully determined these displacements with a 3D accuracy of ±1.3 cm.
18
Bai, Dongxin, Guangyin Lu, Ziqiang Zhu, Xudong Zhu, Chuanyi Tao, and Ji Fang. "Using Electrical Resistivity Tomography to Monitor the Evolution of Landslides’ Safety Factors under Rainfall: A Feasibility Study Based on Numerical Simulation." Remote Sensing 14, no. 15 (July 27, 2022): 3592. http://dx.doi.org/10.3390/rs14153592.
Повний текст джерелаАнотація:
Although electrical resistivity tomography (ERT) may gather the internal resistivity information from a landslide area in a large-scale, low-cost, and non-invasive manner compared to point-based sensor monitoring technology, the indirect resistivity information obtained cannot directly evaluate the landslide’s current mechanical status, such as stress, strength, etc. Based on ERT monitoring data, a framework for quantitatively and directly evaluating the evolution of the factor of safety (FOS) of landslides during rainfall is proposed. The framework first inverts ERT observation data using the inexact Gauss–Newton method based on multiple constraints to obtain a more realistic resistivity distribution, then calculates the saturation distribution using Archie’s equation, and finally calculates the FOS of landslides using the finite element strength reduction method. Twelve sets of numerical experiments were designed and carried out based on the synthetic data of a theoretical model. The experimental results show that the proposed framework is valid and reliable under various arrays, apparent resistivity noise, and uncertainty in the water-electric correlation curve, with the Dipole-Dipole array outperforming the others in terms of accuracy, sensitivity, and anti-noise capability. The proposed framework is significant in improving ERT monitoring and early warning capabilities for rainfall-induced landslides.
19
Li, Jian Feng, and Lei Wang. "Real-Time Monitoring System for Landslides Based on GPRS Technology." Advanced Materials Research 671-674 (March 2013): 2067–71. http://dx.doi.org/10.4028/www.scientific.net/amr.671-674.2067.
Повний текст джерелаАнотація:
Landslides, as a natural phenomenon, cause a large number of casualties and property losses every year, and serious problems of people's production and living, therefore,real-time monitoring of the landslide is very important.Combination landslide uncertainty, unexpected and hidden characteristics, we need to introduce a new technology to realize the all-weather monitoring of landslide strip. Therefore, this article will focus on the introduction of GPRS technology of landslide geological disaster monitoring and landslide real-time monitoring system based on GPRS technology.
20
Li, Shuang, Xiang Wu, Faming Sun, Jie Yang, and Jian Li. "Environmental Geological Problems in Southwest China: A Case Study from the Researches of Regional Landslide Hazards." Nature Environment and Pollution Technology 21, no. 1 (March 6, 2022): 159–65. http://dx.doi.org/10.46488/nept.2022.v21i01.017.
Повний текст джерелаАнотація:
Humans have paid a lot of attention to environmental geological challenges in recent years. Landslides, being one of the most prevalent geological disasters, are characterized by their suddenness and destructiveness. Southwest China is prone to landslides and debris flows due to its unique geological structure. This paper uses landslides in southwest China as an example, focusing on research on landslide initiation mechanisms and outlining modern landslide monitoring devices and prediction models. Landslides are caused by external variables such as persistent precipitation, groundwater movement, and significant seismic activity, as well as interior reasons such as fine particle rearrangement and the action of positive pore water. The reduction of the friction coefficient of the shear surface, which is induced by the increase of the shear rate, the supercritical carbon dioxide and superheated steam of the shear zone, and the mineral recrystallization process on the shear surface, all have an important impact on reducing the friction coefficient of the shear surface, is a key factor in the occurrence of high-speed remote landslides. Real-time landslide monitoring using space-air-ground and acoustic emission technology, as well as the creation of machine learning-based forecast models, have aided in the research of landslide development and early warning.
21
Li, Jin Kui, Hua Zhong Sun, and Xia Li. "Landslide Machanism in Xinghai Zhong Long Yuan and Its Reinforcement Technology." Advanced Materials Research 671-674 (March 2013): 60–64. http://dx.doi.org/10.4028/www.scientific.net/amr.671-674.60.
Повний текст джерелаАнотація:
The landslide is a global geological disasters, causing casualties and huge economic losses. This paper, the Dalian Xinghai Zhong Long Yuan landslides treatment project, analysis of landslides generated by internal causes and predisposing factors, obtained a landslide failure mechanism, and the causes of slope cutting, improve cut flood drainage structures, prestressed anchor Mississauga solid technical measures. The construction process for top of the hill horizontal displacement, deep horizontal displacement and anchor bearing capacity monitoring results show that the landslide control program is correct and effective measures to achieve the desired effect, made landslides governance success to reference for landslide control work for the Dalian region and the coastal cities.
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Liang, Xin, Lei Gui, Wei Wang, Juan Du, Fei Ma, and Kunlong Yin. "Characterizing the Development Pattern of a Colluvial Landslide Based on Long-Term Monitoring in the Three Gorges Reservoir." Remote Sensing 13, no. 2 (January 11, 2021): 224. http://dx.doi.org/10.3390/rs13020224.
Повний текст джерелаАнотація:
Since the impoundment of the Three Gorges Reservoir (TGR) in June 2003, the fluctuation of the reservoir water level coupled with rainfall has resulted in more than 2500 landslides in this region. Among these instability problems, most colluvial landslides exhibit slow-moving patterns and pose a significant threat to local people and channel navigation. Advanced monitoring techniques are therefore implemented to investigate landslide deformation and provide insights for the subsequent countermeasures. In this study, the development pattern of a large colluvial landslide, locally named the Ganjingzi landslide, is analyzed on the basis of long-term monitoring. To understand the kinematic characteristics of the landslide, an integrated analysis based on real-time and multi-source monitoring, including the global navigation satellite system (GNSS), crackmeters, inclinometers, and piezometers, was conducted. The results indicate that the Ganjingzi landslide exhibits a time-variable response to the reservoir water fluctuation and rainfall. According to the supplement of community-based monitoring, the evolution of the landslide consists of three stages, namely the stable stage before reservoir impoundment, the initial movement stage of retrogressive failure, and the shallow movement stage with stepwise acceleration. The latter two stages are sensitive to the drawdown of reservoir water level and rainfall infiltration, respectively. All of the monitoring approaches used in this study are significant for understanding the time-variable pattern of colluvial landslides and are essential for landslide mechanism analysis and early warning for risk mitigation.
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Liang, Xin, Lei Gui, Wei Wang, Juan Du, Fei Ma, and Kunlong Yin. "Characterizing the Development Pattern of a Colluvial Landslide Based on Long-Term Monitoring in the Three Gorges Reservoir." Remote Sensing 13, no. 2 (January 11, 2021): 224. http://dx.doi.org/10.3390/rs13020224.
Повний текст джерелаАнотація:
Since the impoundment of the Three Gorges Reservoir (TGR) in June 2003, the fluctuation of the reservoir water level coupled with rainfall has resulted in more than 2500 landslides in this region. Among these instability problems, most colluvial landslides exhibit slow-moving patterns and pose a significant threat to local people and channel navigation. Advanced monitoring techniques are therefore implemented to investigate landslide deformation and provide insights for the subsequent countermeasures. In this study, the development pattern of a large colluvial landslide, locally named the Ganjingzi landslide, is analyzed on the basis of long-term monitoring. To understand the kinematic characteristics of the landslide, an integrated analysis based on real-time and multi-source monitoring, including the global navigation satellite system (GNSS), crackmeters, inclinometers, and piezometers, was conducted. The results indicate that the Ganjingzi landslide exhibits a time-variable response to the reservoir water fluctuation and rainfall. According to the supplement of community-based monitoring, the evolution of the landslide consists of three stages, namely the stable stage before reservoir impoundment, the initial movement stage of retrogressive failure, and the shallow movement stage with stepwise acceleration. The latter two stages are sensitive to the drawdown of reservoir water level and rainfall infiltration, respectively. All of the monitoring approaches used in this study are significant for understanding the time-variable pattern of colluvial landslides and are essential for landslide mechanism analysis and early warning for risk mitigation.
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Qu, T., Q. Xu, C. Liu, Z. Li, B. Chen, and K. Dai. "RADAR REMOTE SENSING APPLICATIONS IN LANDSLIDE MONITORING WITH MULTI-PLATFORM INSAR OBSERVATIONS: A CASE STUDY FROM CHINA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 1939–43. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-1939-2019.
Повний текст джерелаАнотація:
<p><strong>Abstract.</strong> In China, landslides are widely distributed in the mountainous areas of western regions. Especially after the Wenchuan Earthquake in 2008, a large number of landslides were triggered. This work focuses on the deformation monitoring of Xishancun Landslide based on multi-platform spaceborne radar remote sensing techniques. The spatio-temporal deformation characteristics of landslide could be retrieved from time series InSAR processing with joint use of Sentinel-1 and TerraSAR-X datasets. Eventually, the deformation and evolution histories are cultivated thoroughly to realize an effective and comprehensive monitoring and research of Xishancun Landslide. This work concludes that spaceborne radar remote sensing applications could demonstrate great potentials to identify the spatio-temporal characteristics and investigate the kinematics for hazardous landslides, especially combined with in situ measurements and other remote sensing observations.</p>
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Dong, Xiujun, Tao Yin, Keren Dai, Saied Pirasteh, Guanchen Zhuo, Zhiyu Li, Bing Yu, and Qiang Xu. "Identifying Potential Landslides on Giant Niexia Slope (China) Based on Integrated Multi-Remote Sensing Technologies." Remote Sensing 14, no. 24 (December 14, 2022): 6328. http://dx.doi.org/10.3390/rs14246328.
Повний текст джерелаАнотація:
The Niexia slope, located in Danba County, Sichuan Province, China, with steep slope terrain and dense vegetation coverage, has a height difference of about 3002 m. A traditional manual survey cannot be performed here, and single remote sensing technology is not comprehensive enough to identify potential landslides on such high and steep slopes. In this paper, an integrated approach with multi-remote sensing techniques was proposed to identify potential landslides of the Niexia slope, which combined Interferometry Synthetic Aperture Radar (InSAR), airborne Light Detection and Ranging (LiDAR), and optical remote sensing technologies. InSAR technology was used to monitor the small displacements of the whole slope, and three potential landslides on Niexia slope were identified. The maximum cumulative displacement reached up to 11.9 cm over 1 year. Subsequently, high-resolution optical remote sensing images acquired by remote sensing satellites and a Digital Elevation Model (DEM) without vegetation influence obtained by LiDAR were used to finely interpret the sign of landslide micro-geomorphology and to determine the potential landslide geometry boundaries. As a result, four and nine potential landslides with landslide micro-geomorphic features were identified, respectively. Finally, the identification results of the three techniques were fused and analyzed to assess the potential landslides on the Niexia slope. We compared the results from multi-remote sensing technologies, showing that the three techniques have advantages and disadvantages in terms of monitoring objects, monitoring range, and monitoring accuracy. The integrated use of these three technologies can identify and monitor potential landslides more comprehensively, which could play an important role in the future.
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Idhom, Mohammad, Fetty Tri Anggraeny, Gideon Setya Budiwitjaksono, Zainal Abidin Achmad, and Munoto. "Soil Movement Monitoring System Based on IoT using Fuzzy Logic." Internasional Journal of Data Science, Engineering, and Anaylitics 1, no. 2 (November 25, 2021): 63–73. http://dx.doi.org/10.33005/ijdasea.v1i2.14.
Повний текст джерелаАнотація:
Landslide is one of the disasters that often occurs in several areas in Indonesia, especially in hilly areas, valleys, and volcanoes. Soil conditions in some parts of Indonesia are classified as prone to landslides. The latest data from the Central Statistics Agency related to landslides in 2018 occurred as many as 10,246 events with the highest incidence on the island of Java IoT-based ground motion monitoring using fuzzy logic is a tool that is able to detect ground movements that can trigger landslides. The manufacture of this tool is based on the ig-norance of the community in predicting the occurrence of landslides. To avoid this, an early warning tool is needed in the delivery of information that is easily understood by anyone, especially the public. This tool consists of a Microcontroller, Weather Sensor, Rain Sensor, Ground Movement Sensor, and GSM Shield as well as programs to make it hap-pen. This system was created to provide information to the public directly in land-slide-prone areas. With this early warning system, it is hoped that people who are in landslide-prone loca-tions will know more quickly and can monitor the condition of landslide-prone areas so that they will be more alert to possible dangers that come suddenly, especially fatalities, can be minimized. Through this tool can also be known when the weather is cloudy, raining as well as movement or signs of ground movement, can be monitored and monitored automatically. directly by everyone from mobile phones through "SIPEGERTA" Land Movement System in Wonosalam District, Jombang Regency
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Lan, Hengxing, Xiao Liu, Langping Li, Quanwen Li, Naiman Tian, and Jianbing Peng. "Remote Sensing Precursors Analysis for Giant Landslides." Remote Sensing 14, no. 17 (September 4, 2022): 4399. http://dx.doi.org/10.3390/rs14174399.
Повний текст джерелаАнотація:
Monitoring and early warning systems for landslides are urgently needed worldwide to effectively reduce the losses of life and property caused by these natural disasters. Detecting the precursors of giant landslides constitutes the premise of landslide monitoring and early warning, and remote sensing is a powerful means to achieve this goal. In this work, we aim to summarize the basic types and evolutionary principles of giant landslide precursors, describe the remote sensing methods capable of identifying those precursors, and present typical cases of related sliding. Based on a review of the literature and an analysis of remote sensing imagery, the three main types of remote sensing techniques for capturing the geomorphological, geotechnical, and geoenvironmental precursors of giant landslides are optical, synthetic aperture radar (SAR), and thermal infrared methods, respectively. Time-series optical remote sensing data from medium-resolution satellites can be used to obtain abundant information on geomorphological changes, such as the extension of cracks and erosion ditches, and band algebraic analysis, image enhancement, and segmentation techniques are valuable for focusing on the locations of geomorphological landslide precursors. SAR sensors have the ability to monitor the slight slope deformation caused by unfavorable geological structures and can provide precursor information on imminent failure several days before a landslide; furthermore, persistent scatterer interferometric SAR has significant advantages in large-scale surface displacement monitoring. Thermal infrared imagery can identify landslide precursors by monitoring geoenvironmental information, especially in permafrost regions where glaciers are widely distributed; the reason may be that freeze–thaw cycles and snowmelt caused by increased temperatures affect the stability of the surface. Optical, SAR, and thermal remote sensing all exhibit unique advantages and play an essential role in the identification of giant landslide precursors. The combined application of these three remote sensing technologies to obtain the synthetic geomorphological, geotechnical, and geoenvironmental precursors of giant landslides would greatly promote the development of landslide early warning systems.
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Ning, Po, Yuan-jun Jiang, Jun-jie Tang, and Qi-jun Xie. "Research on the Early Warning Model for Pipelines Due to Landslide Geohazards under Multiple Influencing Factors." Water 15, no. 4 (February 9, 2023): 693. http://dx.doi.org/10.3390/w15040693.
Повний текст джерелаАнотація:
Because of the wide distribution of overland oil and gas pipelines, some pipelines will unavoidably pass through landslide-prone mountainous areas. Landslides may cause deformation or even damage to pipelines, affecting the normal working of the pipeline system. Therefore, it is necessary to study the multiple influence factors of pipeline deformation caused by landslides and establish a forewarning model for oil and gas pipelines buried in landslides. In the present research, the field investigation and a series of large deformation numerical simulations are conducted along four pipelines located in the southeast region of China. Results show that small soil landslides are the main types of landslides threatening the safety of pipelines, whose deformation degree mainly depends on the scale of the landslides and the location of the pipelines in the landslides. Through the investigation, the scale of landslides is the main factor determining the deformation of pipelines induced by landslides. Considering the variation of the scale of landslides, with the increase of the angles, thicknesses, and lengths of the landslides, the pipeline deformation keeps increasing. When crossing the landslides laterally, the pipeline buried in the leading edge of landslides is safer than in the tail edge. What is more, it is most dangerous when the pipeline is buried in the middle of a landslide. Considering the variation of the scale of landslides, including the longitudinal length, horizontal width, thickness, and slope of landslides, as well as the location of pipelines in the landslides, a piecewise forewarning model including those parameters was established based on the influence function for crossing pipelines in landslides. The proposed forewarning model can be used for monitoring and evaluating landslide geological disasters of pipelines and reduce the risk of pipeline landslide geological hazards in the monitored area effectively.
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Yao, Jiaming, Xin Yao, and Xinghong Liu. "Landslide Detection and Mapping Based on SBAS-InSAR and PS-InSAR: A Case Study in Gongjue County, Tibet, China." Remote Sensing 14, no. 19 (September 21, 2022): 4728. http://dx.doi.org/10.3390/rs14194728.
Повний текст джерелаАнотація:
The rock mass along the Jinsha River is relatively broken under complex geological action. Many ancient landslides were distributed along the Jinsha River in Gongjue County, which is very dangerous under the action of gravity, tectonic stress and river erosion. Efficient and accurate identification and monitoring of landslides is important for disaster monitoring and early warning. Interferometric synthetic aperture radar (InSAR) technology has been proved to be an effective technology for landslide hazard identification and mapping. However, great uncertainty inevitably exists due to the single deformation observation method, resulting in wrong judgment during the process of landslide detection. Therefore, to address the uncertainties arising from single observations, a cross-comparison method is put forward using SBAS-InSAR (small baseline subset InSAR) and PS-InSAR (permanent scatterers InSAR) technology. Comparative analysis of the spatial complementarity of interference points and temporal deformation refined the deformation characteristics and verified the reliability of the InSAR results, aiding in the comprehensive identification and further mapping of landslides. Landslides along the Jinsha River in Gongjue County were studied in this paper. Firstly, 14 landslides with a total area of 20 km2 were identified by using two time-series InSAR methods. Then, the deformation characteristics of these landslides were validated by UAV (unmanned aerial vehicle) images, multiresource remote sensing data and field investigation. Further, the precipitation data were introduced to analyze the temporal deformation characteristics of two large landslides. Lastly, the influence of fault activity on landslide formation is further discussed. Our results demonstrate that the cross-comparison of the time-series InSAR method can effectively verify the accuracy of landslide identification.
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Jiao, Runcheng, Shengyu Wang, Honglei Yang, Xuefei Guo, Jianfeng Han, Xin Pei, and Chi Yan. "Comprehensive Remote Sensing Technology for Monitoring Landslide Hazards and Disaster Chain in the Xishan Mining Area of Beijing." Remote Sensing 14, no. 19 (September 20, 2022): 4695. http://dx.doi.org/10.3390/rs14194695.
Повний текст джерелаАнотація:
The Xishan coal mine area in Beijing, China has a long history of mining. Many landslide hazards, in addition to collapses and ground fractures, have occurred in this area. This study used multi-temporal satellite images to extract this region’s deformation information, identify landslides and analyze the deformation evolution process of these landslides. Taking the Anzigou ditch as an example, we investigate the “Quarry–Landslide–Mudslide” disaster chain model. We found that the landslide evolution process is closely related to the geological conditions, and usually goes through four stages: initial deformation, slope front swelling and collapsing, rear part connecting and rupturing, and landslide creeping. The surface deformation can be identified and tracked by high-resolution optical images and InSAR monitoring. Under the combined effects of rainfall and topographic conditions, medium and large landslides may occur and trigger a “Quarry–Landslide–Mudflow” disaster chain. The identification and analysis of these landslide hazards and the disaster chain help with geological disaster prevention, and provide reference for early identification and research of similar disasters.
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Corsini, Alessandro, and Lisa Borgatti. "Mountain Landslides: Monitoring, Modeling, and Mitigation." Geosciences 9, no. 9 (August 23, 2019): 365. http://dx.doi.org/10.3390/geosciences9090365.
Повний текст джерелаАнотація:
This editorial paper summarizes the contents of the papers included in the Special Issue “Mountain Landslides: Monitoring, Modeling, and Mitigation”. The Special Issue provides an overview of methodological papers, as well as some innovative research carried out in the field and in the lab. Even if most papers adopted an integrated approach, sections representing the three research issues outlined in the title can be drawn: the first deals with monitoring, the second focuses on modeling, and the third is related to mitigation. Regardless of the section, the papers included in this special issue put forward methodological and practical implications that, more than likely, can stimulate further research efforts and support the stakeholders to gain better knowledge of landslide hazards in mountain environments, with an aim to tackle the urgent issue of sustainable development in times of global change that can affect landslide occurrences in mountain chains of the world.
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Fobert, Mary-Anne, Vern Singhroy, and John G. Spray. "InSAR Monitoring of Landslide Activity in Dominica." Remote Sensing 13, no. 4 (February 23, 2021): 815. http://dx.doi.org/10.3390/rs13040815.
Повний текст джерелаАнотація:
Dominica is a geologically young, volcanic island in the eastern Caribbean. Due to its rugged terrain, substantial rainfall, and distinct soil characteristics, it is highly vulnerable to landslides. The dominant triggers of these landslides are hurricanes, tropical storms, and heavy prolonged rainfall events. These events frequently lead to loss of life and the need for a growing portion of the island’s annual budget to cover the considerable cost of reconstruction and recovery. For disaster risk mitigation and landslide risk assessment, landslide inventory and susceptibility maps are essential. Landslide inventory maps record existing landslides and include details on their type, location, spatial extent, and time of occurrence. These data are integrated (when possible) with the landslide trigger and pre-failure slope conditions to generate or validate a susceptibility map. The susceptibility map is used to identify the level of potential landslide risk (low, moderate, or high). In Dominica, these maps are produced using optical satellite and aerial images, digital elevation models, and historic landslide inventory data. This study illustrates the benefits of using satellite Interferometric Synthetic Aperture Radar (InSAR) to refine these maps. Our study shows that when using continuous high-resolution InSAR data, active slopes can be identified and monitored. This information can be used to highlight areas most at risk (for use in validating and updating the susceptibility map), and can constrain the time of occurrence of when the landslide was initiated (for use in landslide inventory mapping). Our study shows that InSAR can be used to assist in the investigation of pre-failure slope conditions. For instance, our initial findings suggest there is more land motion prior to failure on clay soils with gentler slopes than on those with steeper slopes. A greater understanding of pre-failure slope conditions will support the generation of a more dependable susceptibility map. Our study also discusses the integration of InSAR deformation-rate maps and time-series analysis with rainfall data in support of the development of rainfall thresholds for different terrains. The information provided by InSAR can enhance inventory and susceptibility mapping, which will better assist with the island’s current disaster mitigation and resiliency efforts.
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GANAPATHY, P., Vladislav ZAALISHVILI, S. CHANDRASEKARAN, and Dmitry MELKOV. "INTEGRATED MONITORING OF SLOPE PROCESS IN INDIA AND RUSSIA." Sustainable Development of Mountain Territories 12, no. 4 (December 30, 2020): 572–81. http://dx.doi.org/10.21177/1998-4502-2020-12-4-572-581.
Повний текст джерелаАнотація:
The common approach to landslide prediction is the integration of the observed landslide displacements, soil properties, and rainfall estimation into predictive models. In general, monitoring the evolution of an unstable slope may provide valuable information to gain a better understanding of the active prediction and early warning processes for potential geodisasters. With this background an initiation has taken between India and Russia to develop cost effective methodology to monitor landslides under the Indo Russian Bilateral Collaborative Projects by DSTRFBR. Based on the hazard assessment The Nilgiris District in Tamil Nadu and Wayanad and Idukki Districts in Kerela area identified for further detailed study on monitoring Vulnerable slopes. On the territory of North Ossetia three sites of different mass volume and differenent activity rates were selected. Landslides that have not moved for years (for example Luarskiy landslide) commonly reactivate if ground water levels change dramatically, particularly when water penetrates old ground cracks, or construction activity creates slope modification that reduces stability.
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Fata, Yulia Amirul, Hendrayanto Hendrayanto, Budi Kuncahyo, Erizal Erizal, and Suria Darma Tarigan. "Characteristics and factors affecting surface and shallow landslides in West Java, Indonesia." Journal of Degraded and Mining Lands Management 10, no. 1 (October 1, 2022): 3849. http://dx.doi.org/10.15243/jdmlm.2022.101.3849.
Повний текст джерелаАнотація:
Bogor, Cianjur, and Sukabumi areas of West Java Province, Indonesia, are vulnerable landslide areas. This study analyzes the landslide characteristic and the factors affecting landslides. The analysis was carried out on 148 landslides from 415 of 2018-2020 landslides, which were selected purposively by considering the heterogeneity of soil, geology, slope classes, land use type, and accessibility of landslide locations. Landslide characteristics and factors affecting landslides were analyzed using frequency analysis and binary logistic regression. The results showed that the most dominant characteristics of surface and shallow landslides were the landslides characterized by slopes >45%, Quaternary geological period, Andisol soil type, agriculture land use type, the occurrence of rain, and absence of earthquake. The dominant factors affecting surface and shallow landslides are human activities in land use, soil properties, steep-very steep slopes, Inceptisol and Entisol soil orders, young rocks (Quaternary geological period), rainfall events, and high earthquake magnitude.
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Lee, En-Jui, Wu-Yu Liao, Guan-Wei Lin, Po Chen, Dawei Mu, and Ching-Weei Lin. "Towards Automated Real-Time Detection and Location of Large-Scale Landslides through Seismic Waveform Back Projection." Geofluids 2019 (January 15, 2019): 1–14. http://dx.doi.org/10.1155/2019/1426019.
Повний текст джерелаАнотація:
Rainfall-triggered landslides are one of the most deadly natural hazards in many regions. Seismic recordings have been used to examine source mechanisms and to develop monitoring systems of landslides. We present a semiautomatic algorithm for detecting and locating landslide events using both broadband and short-period recordings and have successfully applied our system to landslides in Taiwan. Compared to local earthquake recordings, the recordings of landslides usually show longer durations and lack distinctive P and S wave arrivals; therefore, the back projection method is adopted for the landslide detection and location. To identify the potential landslide events, the seismic recordings are band-passed from 1 to 3 Hz and the spectrum pattern in the time-frequency domain is used to distinguish landslides from other types of seismic sources based upon carefully selected empirical criteria. Satellite images before and after the detected and located landslide events are used for final confirmation. Our landslide detection and spatial-temporal location system could potentially benefit the establishment of rainfall-triggered landslide forecast models and provide more reliable constraints for physics-based landslide modeling. The accumulating seismic recordings of landslide events could be used as a training dataset for machine learning techniques, which will allow us to fully automate our system in the near future.
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Lu, Shu Qiang, Qing Lin Yi, and Wu Yi. "The Application of Measurement Robot in Landslides Emergency Monitoring." Applied Mechanics and Materials 353-356 (August 2013): 1245–48. http://dx.doi.org/10.4028/www.scientific.net/amm.353-356.1245.
Повний текст джерелаАнотація:
The measurement robot (TCA2003 Total Station) has been adopted to solve the problems of landslides emergency monitoring. The working principle and characteristics of measurement robot were briefly introduced. Then a main frame of the deformation monitoring system based on measurement robot was presented and the corresponding software was designed. Based on the GPS deformation monitoring system, the measurement robot automatic emergency monitoring system were established. The application of measurement robot in deformation monitoring system for landslides of the Three Gorges was mainly studied in this paper. The method of monitor landslide by the robot deformation monitoring system has several advantages and extensive application foreground.
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Hao, Wu, Wu, Hu, Zou, Zhu, Zhao, et al. "Investigation of a Small Landslide in the Qinghai-Tibet Plateau by InSAR and Absolute Deformation Model." Remote Sensing 11, no. 18 (September 12, 2019): 2126. http://dx.doi.org/10.3390/rs11182126.
Повний текст джерелаАнотація:
Landslides are one of the major geohazards in the Qinghai-Tibet Plateau, and have recently increased in both frequency and size. SAR interferometry (InSAR) has been widely applied in landslide research, but studies on monitoring small-scale landslides are rare. In this study, we investigated the performance of Small Baseline Subsets method (SBAS) in monitoring small-scale landslide and further developed a new deformation model to obtain the absolute deformation time series. The results showed that SBAS could well capture the small-scale landslide characteristics including spatiotemporal abnormal displacement and progressive failure processes. The newly developed absolute deformation model further detected the process of landslide details, such as instances of noticeable creeps induced by rainfall and snowmelt. Finally, a conceptual model of the kinematics-based failure mechanism for small-scale landslide was proposed. This study extended the monitoring capability of InSAR and improved our knowledge on the deformation in the frozen ground regions.
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Shan, Zhigang, Hao Wu, Weida Ni, Miaojun Sun, Kuanjun Wang, Liuyuan Zhao, Yihuai Lou, et al. "Recent Technological and Methodological Advances for the Investigation of Submarine Landslides." Journal of Marine Science and Engineering 10, no. 11 (November 11, 2022): 1728. http://dx.doi.org/10.3390/jmse10111728.
Повний текст джерелаАнотація:
Submarine landslides have attracted widespread attention, with the continuous development of ocean engineering. Due to the recent developments of in-situ investigation and modelling techniques of submarine landslides, significant improvements were achieved in the evolution studies on submarine landslides. The general characteristics of typical submarine landslides in the world are analyzed. Based on this, three stages of submarine landslide disaster evolution are proposed, namely, the submarine slope instability evolution stage, the large deformation landslide movement stage, and the stage of submarine landslide deposition. Given these three stages, the evolution process of submarine landslide disaster is revealed from the perspectives of in-situ investigation techniques, physical simulation, and numerical simulation methods, respectively. For long-term investigation of submarine landslides, an in-situ monitoring system with long-term service and multi-parameter collaborative observation deserves to be developed. The mechanism of submarine landslide evolution and the early warning factors need to be further studied by physical modelling experiments. The whole process of the numerical simulation of submarine landslides, from seabed instability to large deformation sliding to the impact on marine structures, and economizing the computational costs of models by advanced techniques such as parallel processing and GPU-accelerators, are the key development directions in numerical simulation. The current research deficiencies and future development directions in the subject of submarine landslides are proposed to provide a useful reference for the prediction and early warning of submarine landslide disasters.
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Peternel, Tina, Mitja Janža, Ela Šegina, Nejc Bezak, and Matej Maček. "Recognition of Landslide Triggering Mechanisms and Dynamics Using GNSS, UAV Photogrammetry and In Situ Monitoring Data." Remote Sensing 14, no. 14 (July 7, 2022): 3277. http://dx.doi.org/10.3390/rs14143277.
Повний текст джерелаАнотація:
Detecting the mechanism of landslides and evaluating their dynamics is challenging, especially concerning composite landslides. For this purpose, several investigation and monitoring techniques should be implemented to obtain reliable information on landslide characteristics (e.g., geological and hydrogeological conditions and type of landslide processes), kinematics (displacement rate), and potential triggering mechanisms (e.g., change in groundwater table and precipitation). The Urbas landslide in northwest Slovenia has been studied for decades through geological, geotechnical, geodetic, and remote sensing investigations. However, due to the complexity of the landslide and the short duration of continuous monitoring, no assessment of its dynamics has been made. To meet this need, this study analysed continuous and periodic monitoring of landslide displacements using data from the global navigation satellite system (GNSS), a wire extensometer, unmanned aerial vehicle (UAV) photogrammetry, and hydrometeorological sensing (groundwater table, precipitation). The results of this study show that the dynamics of the Urbas landslide differ along the landslide area, depending on local geological and hydrogeological conditions. Consequently, certain parts of the landslide are at different evolutionary states and respond differently to the same external triggers.
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Wu, Yongbo, Ruiqing Niu, Yi Wang, and Tao Chen. "A Fast Deploying Monitoring and Real-Time Early Warning System for the Baige Landslide in Tibet, China." Sensors 20, no. 22 (November 19, 2020): 6619. http://dx.doi.org/10.3390/s20226619.
Повний текст джерелаАнотація:
Landslide early warning systems (EWSs) have been widely used to reduce disaster losses. The effectiveness of a landslide EWS depends highly on the prediction methods, and it is difficult to correctly predict landslides in a timely manner. In this paper, we propose a real-time prediction method to provide real-time early warning of landslides by combining the Kalman filtering (KF), fast Fourier transform (FFT), and support vector machine (SVM) methods. We also designed a fast deploying monitoring system (FDMS) to monitor the displacement of landslides for real-time prediction. The FDMS can be quickly deployed compared to the existing system. This system also has high robustness due to the usage of the ad-hoc technique. The principle of this method is to extract the precursory features of the landslide from the surface displacement data obtained by the FDMS and, then, to train the KF-FFT-SVM model to make a prediction based on these precursory features. We applied this fast monitoring and real-time early warning system to the Baige landslide, Tibet, China. The results showed that the KF-FFT-SVM model was able to provide real-time early warning for the Baige landslide with high accuracy.
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Bao, Xun, Deshan Cui, Jiale Peng, Mingke Liao, and Guangcheng Zhang. "Revival Mechanism and Prevention Measures of Composite Landslides: A Case Study of the Wenma Expressway Composite Landslide." Applied Sciences 13, no. 4 (February 14, 2023): 2449. http://dx.doi.org/10.3390/app13042449.
Повний текст джерелаАнотація:
The resurrection of landslides often occurs in complex strata, where there are often multiple water-resisting zones and weak interlayers. The groundwater level has a significant influence on landslide stability and can lead to the formation of composite landslides and increase the probability of landslide resurrection. In a field investigation of the K39 +400 composite landslide of Wenma Expressway, the deformation characteristics of the landslide surface were obtained by analyzing 34 cracks on the landslide surface. The deep deformation characteristics of the landslide were analyzed by studying the deformation data obtained from deep borehole monitoring. The deformation zone characteristics of landslides were assessed by integrating surface and deep deformation data in the landslide area. The resurrections of shallow landslides in Area I and deep landslides in Area III were due mainly to the long-term high underground water level in the landslide. The stability of the landslide was calculated under various depths of drainage tunnel, and the results showed that the slope was in critical condition when the depth of the drainage tunnel was 15 m; the slope was basically stable when the depth of the drainage tunnel was 20 m and 25 m. When the depth of the drainage tunnel reached more than 30 m, the slope was in a stable state. Groundwater level was found to be the main factor affecting landslide deformation. This case study shows the importance of zoning the deformation characteristics of composite landslides, and the important influence of the groundwater level on landslide resurrection.
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Zhang, Xingchen, Lixia Chen, and Chao Zhou. "Deformation Monitoring and Trend Analysis of Reservoir Bank Landslides by Combining Time-Series InSAR and Hurst Index." Remote Sensing 15, no. 3 (January 20, 2023): 619. http://dx.doi.org/10.3390/rs15030619.
Повний текст джерелаАнотація:
Landslides along the Three Gorges Reservoir in China pose a threat to coastal residents and waterway safety. To reduce false positive misjudgments caused by a sudden local change in the landslide deformation curve, in this paper, we propose an effective method for predicting the deformation trend of reservoir bank landslides. We take reservoir bank landslides in the Wanzhou District of the Three Gorges Reservoir area as the research object. The Time-Series Interferometric Synthetic Aperture Radar (InSAR) method and 62 Sentinel-1A images from 2018 to 2022 were selected for landslide deformation monitoring, and the Hurst index was calculated to characterize the deformation trend. Furthermore, we propose a method for predicting the deformation trend based on the statistical distribution of deformation rates and the physical significance of the Hurst index. After the field survey and Global Positioning System (GPS) verification, the Time-Series InSAR results are shown to be reliable. We take the Sifangbei landslide as a representative case to analyze the validation results. It is found that the determined Sifangbei landslide deformation trend is consistent with the conclusions for the region. In addition, the deformation trend of a reservoir bank slope has obvious spatial and temporal differences. Changes in the reservoir water level and concentrated rainfall play roles similar to those of catalysts. The proposed method, involving the combination of Time-Series InSAR and the Hurst index, can effectively monitor deformation and predict the stability trend of reservoir bank landslides. The presented research results provide new ideas and solutions for landslide prevention and risk mitigation in reservoir areas.
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Shao, Xiaoyi, Siyuan Ma, Chong Xu, Lingling Shen, and Yongkun Lu. "Inventory, Distribution and Geometric Characteristics of Landslides in Baoshan City, Yunnan Province, China." Sustainability 12, no. 6 (March 20, 2020): 2433. http://dx.doi.org/10.3390/su12062433.
Повний текст джерелаАнотація:
Inventorying landslides in mountainous areas is of great importance for prevention of geologic hazards. This study aimed to establish a detailed landslide inventory of Baoshan City, Yunnan Province, China, based on a large set of high-resolution satellite images from Google Earth. The landslides of this region were divided into two groups, i.e., recent landslides and old landslides. The spatial distribution and geometric characteristics of the two kinds of landslides were analyzed, respectively. Results show that 2427 landslides are present in the study area, including 2144 recent landslides and 283 old landslides with a total area of 7.2 km2 and 97.6 km2, respectively. The recent landslides occurred primarily at steep slopes with higher elevation, while old landslides took place at gentle terrains. For the slope position, most landslides, whether old or recent, cluster near ridges. The lower boundary of the recent landslides is far away from the valley, while the accumulation area of the old landslide is closer to the valley. The H/L (height to length) ratios are basically the same for all landslides, ranging from 0.2 to 0.5. Old landslides have larger mobility, as their travel distances are longer than recent landslides at the same height. The results would be helpful for further understanding the development and spatial distribution of the landslides in Southwest China, and also provide essential support for the subsequent landslide susceptibility mapping and geologic hazard assessment in this area.
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Bednarczyk, Zbigniew. "Landslide Geohazard Monitoring, Early Warning and Stabilization Control Methods." Studia Geotechnica et Mechanica 36, no. 1 (March 1, 2014): 3–13. http://dx.doi.org/10.2478/sgem-2014-0001.
Повний текст джерелаАнотація:
Abstract This paper is a presentation of landslide monitoring, early warning and remediation methods recommended for the Polish Carpathians. Instrumentation included standard and automatic on-line measurements with the real-time transfer of data to an Internet web server. The research was funded through EU Innovative Economy Programme and also by the SOPO Landslide Counteraction Project. The landslides investigated were characterized by relatively low rates of the displacements. These ranged from a few millimetres to several centimetres per year. Colluviums of clayey flysch deposits were of a soil-rock type with a very high plasticity and moisture content. The instrumentation consisted of 23 standard inclinometers set to depths of 5-21 m. The starting point of monitoring measurements was in January 2006. These were performed every 1-2 months over the period of 8 years. The measurements taken detected displacements from several millimetres to 40 cm set at a depth of 1-17 m. The modern, on-line monitoring and early warning system was installed in May 2010. The system is the first of its kind in Poland and only one of several such real-time systems in the world. The installation was working with the Local Road Authority in Gorlice. It contained three automatic field stations for investigation of landslide parameters to depths of 12-16 m and weather station. In-place tilt transducers and innovative 3D continuous inclinometer systems with sensors located every 0.5 m were used. It has the possibility of measuring a much greater range of movements compared to standard systems. The conventional and real-time data obtained provided a better recognition of the triggering parameters and the control of geohazard stabilizations. The monitoring methods chosen supplemented by numerical modelling could lead to more reliable forecasting of such landslides and could thus provide better control and landslide remediation possibilities also to stabilization works which prevent landslides.
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Gian, Quoc-Anh, Dinh-Chinh Nguyen, Duc-Nghia Tran, and Duc-Tan Tran. "Monitoring of Landslides in Mountainous Regions based on FEM Modelling and Rain Gauge Measurements." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 5 (October 1, 2016): 2106. http://dx.doi.org/10.11591/ijece.v6i5.10482.
Повний текст джерелаАнотація:
<p><span>Vietnam is a country heavily influenced by climate change. The effect of climate change leads to a series of dangerous phenomena, such as landslides. Landslides occur not only in the mountainous province, but also in Delta provinces, where hundreds of landslides are reported annually in the North-Western provinces of Vietnam. These events have catastrophic impact to the community as well as the economy. In mountainous areas, the conditions for landslides to occur are met frequently, especially after heavy rains or geological activity, causing harm to the community as well as damaging or destroying much needed infrastructure and key transport routes. However, in Vietnam, investment in mountainous regions has been often lower than in urban areas. The meteorology monitoring and forecasting systems are ill equipped and overloaded, so they cannot deliver earlier and more accurate forecasts for complex weather events, unable to provide timely warnings. It can be seen that in countries that landslide often occur, researchers have been trying to develop low cost and efficient landslide detection system. This paper precisely addressed the problems mentioned, by designing and implementing an efficient and reliable Landslide Monitoring and Early Warning (LMnE) system based on the 3G/2G mobile communication system, and a rain gauge at the field site along with a carefully FEM (finite element method) simulation using the rain density information on the server. The system uses advanced processing algorithms combining obtained data at the central station.</span></p>
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Gian, Quoc-Anh, Dinh-Chinh Nguyen, Duc-Nghia Tran, and Duc-Tan Tran. "Monitoring of Landslides in Mountainous Regions based on FEM Modelling and Rain Gauge Measurements." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 5 (October 1, 2016): 2106. http://dx.doi.org/10.11591/ijece.v6i5.pp2106-2113.
Повний текст джерелаАнотація:
<p><span>Vietnam is a country heavily influenced by climate change. The effect of climate change leads to a series of dangerous phenomena, such as landslides. Landslides occur not only in the mountainous province, but also in Delta provinces, where hundreds of landslides are reported annually in the North-Western provinces of Vietnam. These events have catastrophic impact to the community as well as the economy. In mountainous areas, the conditions for landslides to occur are met frequently, especially after heavy rains or geological activity, causing harm to the community as well as damaging or destroying much needed infrastructure and key transport routes. However, in Vietnam, investment in mountainous regions has been often lower than in urban areas. The meteorology monitoring and forecasting systems are ill equipped and overloaded, so they cannot deliver earlier and more accurate forecasts for complex weather events, unable to provide timely warnings. It can be seen that in countries that landslide often occur, researchers have been trying to develop low cost and efficient landslide detection system. This paper precisely addressed the problems mentioned, by designing and implementing an efficient and reliable Landslide Monitoring and Early Warning (LMnE) system based on the 3G/2G mobile communication system, and a rain gauge at the field site along with a carefully FEM (finite element method) simulation using the rain density information on the server. The system uses advanced processing algorithms combining obtained data at the central station.</span></p>
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Long, Leijin, Feng He, and Hongjiang Liu. "The use of remote sensing satellite using deep learning in emergency monitoring of high-level landslides disaster in Jinsha River." Journal of Supercomputing 77, no. 8 (January 26, 2021): 8728–44. http://dx.doi.org/10.1007/s11227-020-03604-4.
Повний текст джерелаАнотація:
AbstractIn order to monitor the high-level landslides frequently occurring in Jinsha River area of Southwest China, and protect the lives and property safety of people in mountainous areas, the data of satellite remote sensing images are combined with various factors inducing landslides and transformed into landslide influence factors, which provides data basis for the establishment of landslide detection model. Then, based on the deep belief networks (DBN) and convolutional neural network (CNN) algorithm, two landslide detection models DBN and convolutional neural-deep belief network (CDN) are established to monitor the high-level landslide in Jinsha River. The influence of the model parameters on the landslide detection results is analyzed, and the accuracy of DBN and CDN models in dealing with actual landslide problems is compared. The results show that when the number of neurons in the DBN is 100, the overall error is the minimum, and when the number of learning layers is 3, the classification error is the minimum. The detection accuracy of DBN and CDN is 97.56% and 97.63%, respectively, which indicates that both DBN and CDN models are feasible in dealing with landslides from remote sensing images. This exploration provides a reference for the study of high-level landslide disasters in Jinsha River.
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Tan, Weixian, Yadong Wang, Pingping Huang, Yaolong Qi, Wei Xu, Chunming Li, and Yuejuan Chen. "A Method for Predicting Landslides Based on Micro-Deformation Monitoring Radar Data." Remote Sensing 15, no. 3 (February 1, 2023): 826. http://dx.doi.org/10.3390/rs15030826.
Повний текст джерелаАнотація:
Mine slope landslides seriously threaten the safety of people’s lives and property in mining areas. Landslide prediction is an effective way to reduce losses due to such disasters. In recent years, micro-deformation monitoring radar has been widely used in mine slope landslide monitoring. However, traditional landslide prediction methods are not able to make full use of the diversified monitoring data from these radars. This paper proposes a landslide time prediction method based on the time series monitoring data of micro-deformation monitoring radar. Specifically, deformation displacement, coherence and deformation volume, and the parametric degree of deformation (DOD) are calculated and combined with the use of the tangent angle method. Finally, the effectiveness of the method is verified by using measured data of a landslide in a mining area. The experimental results show that our proposed method can be used to identify the characteristics of an imminent sliding slope and landslide in advance, providing monitoring personnel with more reliable landslide prediction results.
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Liu, Wen-Cheng, and Wei-Che Huang. "CLOSE RANGE DIGITAL PHOTOGRAMMETRY APPLIED TO TOPOGRAPHY AND LANDSLIDE MEASUREMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B5 (June 16, 2016): 875–80. http://dx.doi.org/10.5194/isprs-archives-xli-b5-875-2016.
Повний текст джерелаАнотація:
Landslide monitoring is a crucial tool for the prevention of hazards. It is often the only solution for the survey and the early-warning of large landslides cannot be stabilized. The objective of present study is to use a low-cost image system to monitor the active landslides. We adopted the direct linear transformation (DLT) method in close range digital photogrammetry to measure terrain of landslide at the Huoyen Shan, Miaoli of central Taiwan and to compare measured results with e-GPS. The results revealed that the relative error in surface area was approximately 1.7% as comparing the photogrammetry with DLT method and e-GPS measurement. It showed that the close range digital photogrammetry with DLT method had the availability and capability to measure the landslides. The same methodology was then applied to measure the terrain before landslide and after landslide in the study area. The digital terrain model (DTM) was established and then was used to calculate the volume of the terrain before landslide and after landslide. The volume difference before and after landslides was 994.16 m<sup>3</sup>.
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Liu, Wen-Cheng, and Wei-Che Huang. "CLOSE RANGE DIGITAL PHOTOGRAMMETRY APPLIED TO TOPOGRAPHY AND LANDSLIDE MEASUREMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B5 (June 16, 2016): 875–80. http://dx.doi.org/10.5194/isprsarchives-xli-b5-875-2016.
Повний текст джерелаАнотація:
Landslide monitoring is a crucial tool for the prevention of hazards. It is often the only solution for the survey and the early-warning of large landslides cannot be stabilized. The objective of present study is to use a low-cost image system to monitor the active landslides. We adopted the direct linear transformation (DLT) method in close range digital photogrammetry to measure terrain of landslide at the Huoyen Shan, Miaoli of central Taiwan and to compare measured results with e-GPS. The results revealed that the relative error in surface area was approximately 1.7% as comparing the photogrammetry with DLT method and e-GPS measurement. It showed that the close range digital photogrammetry with DLT method had the availability and capability to measure the landslides. The same methodology was then applied to measure the terrain before landslide and after landslide in the study area. The digital terrain model (DTM) was established and then was used to calculate the volume of the terrain before landslide and after landslide. The volume difference before and after landslides was 994.16 m<sup>3</sup>.