Potential Landslide Areas Research Articles

MICROTREMOR ANALYSIS IN DETERMINING LANDSLIDE POTENTIAL IN SEMBAHE VILLAGE, SIBOLANGIT DISTRICT, DELI SERDANG REGENCY

Sembahe Village is an area that is highly vulnerable to landslides. This is caused by steep topographic conditions and high rainfall. This research is intended to understand the characteristics and distribution of dominant frequencies, amplification factors and seismic vulnerability index on the possibility of landslides. Microtremor measurements were carried out in Hamlet 3 Sembahe Village at 2 location points which were measured using a portable seismograph / Pegasus for 2 hours with a sampling frequency. 100 Hz. Microtremor data was processed using Geopsy software using the Horizontal to Vertical Spectral Ratio (HVSR) method and each parameter was weighted using the Analytical Hierarchy Process (AHP) statistical method in determining potential landslide areas. The results obtained show that the distribution of dominant frequency values (F0) is 5.36 Hz – 5.33 Hz, amplification (A0) is 1.84 – 1.59, seismic vulnerability index (Kg) is 0.63 x 10-3s2 / cm - 0.47 x 10-3 s2/cm. Based on weight analysis using the AHP statistical method, the location point that has the highest potential for landslides is point 1.

Predicting landslide extent of satellite images based on image classification extraction

Abstract Landslide is a common geological disaster and the most destructive natural disaster at home and abroad. Therefore, automatic interpretation of landslide high-risk areas and potential landslide areas through different models and methods is one of the basic ways to prevent and reduce possible disasters. In this study, we improve the NDWI method by using the multispectral image data from the French satellite SPOT 5. Combined with infrared band sensors, the Normalized Difference Water Index (NDWI) of large exposed landslides is extracted by improving the NDWI index method by utilizing the characteristics of near-infrared (NIR) and short-wave infrared (SWIR) bands and replacing the green-wave band or the mid-infrared (MIR) band with the short-wave infrared (SWIR) band, which can be applied to the water resources management of high-risk areas, potential landslide areas, and potential landslide areas, and the water environment monitoring of water resources and disaster emergency management. We calculate the 2014 satellite images with a total area of 11351.6 ha, and after the NDWI index, the dark blue color represents the high-risk landslide area of 1609.1 ha (14175%), the light blue color represents the potential landslide area of 3971.773 ha (34.989%), and the brown color represents the vegetation area of 5770.727 ha (50.836%).

An enhanced neighborhood differential method for potential landslide identification from stacking-InSAR results

Stacking-InSAR is widely used for identifying potential landslide. However, in Stacking-InSAR results, there are often challenges to clearly identify the potential landslide due to wide-scale system errors, especially the elevation-related atmospheric disturbances, leading to low precision of potential landslide identification. This paper introduces an enhanced neighborhood differential method that employs a concept of step size to identify potential landslide from Stacking-InSAR. Applied to the mountainous regions in the northwestern part of Sichuan Province, China, this method successfully identified 117 potential landslides, verified through field investigations. Compared to traditional Stacking-InSAR, this method additionally identified 34 potential landslides. Further analysis indicates that the optimal step size in the neighborhood differential method should ensure that one differential pixel is located inside the potential landslide area while the other is outside, thereby making the step size closely related to the spatial extent of the potential landslide. The results indicate that this method could effectively reduce wide-scale system error in Stacking-InSAR results, providing an important technical reference for the rapid and efficient identification of potential landslide over a wide mountainous area in the future.

Remote sensing identification of shallow landslide based on improved otsu algorithm and multi feature threshold

In low-resolution remote sensing images under complex lighting conditions, there is a similarity in spectral characteristics between non-landslide areas and landslide bodies, which increases the probability of misjudgment in the identification process of shallow landslide bodies. In order to further improve the accuracy of landslide identification, a shallow landslide remote sensing identification method based on an improved Otsu algorithm and multi-feature threshold is proposed for the temporary treatment project of the Yangjunba disaster site in Leshan City. Using Retinex theory, remote sensing images are enhanced with local linear models and guided filtering; then, multi-feature scales and sliding window calculations of opening and closing transformations identify potential landslide areas, which are finally segmented using the Otsu algorithm. Through experimental verification, the method proposed in this article can clearly segment the target object and background after binary segmentation of remote sensing images. The recognition rate of shallow landslide bodies is not less than 95%, indicating that the method proposed in this article is relatively accurate in identifying shallow landslide bodies in the research area and has good application effects.

Utilization of satellite data for landslide disaster mitigation in extreme event: a case study June 18, 2016, landslide in Banjarnegara Regency, Indonesia

Abstract Understanding the characteristics of landslides produced by rainfall and soil humidity is critical for reducing the occurrence of landslides. Extreme rain, as an external impact, has been suggested to play a role in landslide development. Many people were killed in a landslide that occurred in the Banjarnegara Regency on June 18, 2016, which was unexpected because June is not Indonesia’s rainy season. El Niño and La Niña events were observed in Indonesia in 2015-2016. The initial hypothesis is that such extreme rain conditions caused this landslide. This study aims to apply an alternative approach to detecting landslides by monitoring soil moisture and rainfall with remote sensing data during extreme events. An analysis of precipitation and moisture data has been carried out before the event and is associated with the El Niño and La Niña phenomena. The findings indicate that the natural environment of Banjarnegara Regency is unique. Landslides occur even during the extreme dry season. Rain still drops, and soil moisture is high. The impact of local variables is more significant than regional conditions. They are still at risk of a landslide during the El Niño phase. During that stage, Banjarnegara Regency’s potential landslide area would continue to be observed. Monitoring needs to be carried out rapidly, with a high level of spatial and temporal resolution. It is possible to resolve it using IMERG and SMAP data.

Geoelectric Interpretation of Wenner-Schlumberger Configuration Using Res2Dinv Software: A Case Study of 2D Mapping of Seawater Intrusion in a Landslide Potential Area, North Halmahera District, Indonesia

Research has been carried out on landslides in Saluta-Pelita Village, North Galela District, North Halmahera Regency, Indonesia using the Wenner-Schlumberger method using a Geoelectric Resistivity tool - Naunira NRD 300 HF. This research aims to determine the structure of the subsurface layer in the potential landslide area of Saluta-Pelita Village. In addition, this research aims to determine the slip plane (boundary layer) of sea water intrusion in the research area. The measurement results are processed using Res2Dinv software for 2D resistivity which describes the subsurface layer shown in color. The measurement results on track 1 show a clay layer with a resistivity value of 3.1 ohm -27 ohm at a distance of 1-80 meters (blue and green), a silt layer of 44.3 ohm - 184.1 ohm at a depth of 1-20 meters (Yellow) which is a slip plane (boundary layer) of sea water intrusion with a path length of 40 meters, conglomerate 210 ohm (red) at a depth of more than 7.50 meters. In track 2 there is a layer of clay with a resistivity of 1.4 ohm - 39 ohm at a depth of 1-24 meters (blue and green), silt 43.1 m-185.6 m (yellow) is the slip plane (layer boundary) of sea water intrusion with a 95 meter long track, a conglomerate layer with a resistivity of 203.4 ohm - 407.8 ohm (red) at a depth of more than 12.8 meters. On track 3 there is a layer of clay with a resistivity of 0.186 ohm - 31.4 ohm (blue and green) at a depth of up to 24 meters with a length of more than 120 meters, silt with a resistivity value of 44.4 ohm - 189 ohm (yellow) which is a slip plane (boundary layer) sea water intrusion with a path of 65 meters at a depth of 2.50 meters-24.9 meters.

Landslide hazard assessment and agricultural vulnerability using a geospatial approach

The village of Cukilan, Semarang Regency, Indonesia, is predominantly utilized for agricultural purposes, facilitated by its high rainfall suitable for various crops. Despite the benefits it provides to farmers, the elevated rainfall also poses natural disaster risks, particularly landslides, which can adversely affect surrounding communities. This study aims to map landslide potentials and evaluate their impacts on the agricultural sector in the Cukilan Village, Semarang Regency. The research methodology encompasses a literature review focusing on landslide potential estimation and field survey. The literature review aims to obtain landslide potential distribution maps compiled by DVMBG, considering rainfall, slope, geology, land use, and soil types. Field surveys validate conditions based on landslide potential estimations, involving random soil sampling and analyzing parameters like permeability, texture, bulk density, depth, and surface density. The research findings reveal the impact of landslide potential on the agricultural sector and the mapping of landslide potential areas in Cukilan Village, depicting various risk levels: very high (0.71% of total area, covering 5 ha), high (13.24%, 93 ha), moderate (56.55%, 397 ha), and low (29.48%, 207 ha). Based on these findings, it is evident that managing landslide disaster risks in agricultural development in the area is crucial, including the implementation of safer land use planning and appropriate mitigation strategies.

Characteristics of strata movement and method for runoff disaster management for shallow multiseam mining in gully regions: A case study

Multiseam mining in gully regions has resulted in severe and complex disaster chains, including crack development, mountain landslides, river blockage, and intensified mine water inflow. To prevent and control water inrush disasters, it is imperative to investigate the characteristics and mechanizations of overburden failure under the combined effect of gully terrain and repeated mining in coal seams. This study takes multiseam mining within the gully region of the Xiqu Coal Mine as a case study. The comprehensive analytical method that integrates surface exploration, Interferometric Synthetic Aperture Radar (InSAR) measurement, numerical simulation, and rainfall-runoff analysis, is used to anatomize the entire process of overburden failure induced by downward multiseam mining and the accumulation process of runoff in the gully region. The results reveal that compared to single-seam mining activities, repeated mining and the occurrence of key stratum (KS) structure failure triggered the comprehensive subsidence of the interburden, producing a cutting-type fracture and stepped subsidence, while the overburden exhibited severe damage. Compared to gentle surface topography, gully slopes are prone to shear sliding under the effects of mining subsidence and gravity, resulting in the connection of the downward cracks of the slope and the upward cracks of the overburden. In addition, if the accumulation formed by gully landslides due to repeated mining blocks the river channel and forms a barrier lake during the flood season, it may cause a surge in underground water. High-precision terrain synthesized by UAV tilt photogrammetry is used to simulate the rainfall inundation range and time of different durations during the “100-year return period” rainstorm in the study area. This study proposes a zoning prevention and control method for surface runoff disasters based upon the characteristics of surface deformation and surface inundation time; this method involves filling surface cracks in runoff areas and submerged and crack development areas, implementing slope cutting and control in potential landslide areas, and strengthening the riverbed in submerged and maximum settlement areas.

Stability analysis of a deep and large open pit based on fine geological modeling and large-scale parallel computing: a case study of Fushun West Open-pit Mine

Accurate input of geological elements is essential for evaluating or predicting natural hazards such as subsidence, landslides, and earthquakes. This paper proposes an approach to carry out an open pit’s overall and whole-process mechanical analysis with complex geological conditions, using precise modeling and large-scale parallel calculation techniques. Taking the Fushun West Open-pit Mine (the largest open-pit coal mine in Asia) as an example, through the elaborate multi-method geological investigation, the interfaces of interbedded shales and mudstones, the unloading zones, and the small structures were identified, a detailed 3D geological model was built and finely meshed in full-size with 100 million degrees of freedom, large-scale parallel numerical simulation was then performed, the results agree well with the InSAR monitoring data and in situ observations. Besides, the simulation can replicate the landslides in recent years. Through the simulation, it is possible to locate the potential landslide area, and targeted backfilling schemes for stability treatment were put forward and further simulated. The results indicate that the proposed approach can more effectively and reliably evaluate the Fushun West Open-pit Mine’s overall slope stability and closure plan.

Research on the Carter Method for the location of sliding surfaces based on a numerical study

In order to investigate the potential location and magnitude of a landslide, the information regarding the location and shape of the sliding surface is important. However, obtaining such information through underground investigations is costly and time-consuming. A method proposed by Carter and Bentley (1985) provides an approach to predict the sliding surface based on ground surface information. With help of advanced techniques such as UAVs and SAR satellites, Carter’s method has been utilized in field sites of potential landslide areas recently. Geophysical surveys and drilling data are commonly used validation data, but the temporal and spatial resolutions of these data are rough and rare. For this problem, this study generated high temporal and spatial resolution data of landslide behaviour by a physically based model and these data were utilized to investigate the capability and limitations of Carter’s method. Firstly, a scenario of slope failure on a 30-degree slope was performed by a numerical model using the material point method (MPM). Next, Carter’s method was applied to predicted the sliding surface using ground surface data obtained from the MPM simulation, and the results were compared with the sliding surface data from the MPM simulation. Finally, we perform an error analysis using the concordance correlation coefficient (CCC) to assess the reliability of Carter’s method. The findings of this study contribute to understanding the capabilities and limitations of Carter’s method in landslide analysis and provide insights for improving landslide risk assessment and mitigation strategies.

Potential Factors of Landslide Recurrence in Uttaradit, Thailand: A Case Study in Laplae, Mueang Uttaradit, and Tha Pla Districts

Laplae, Mueang Uttaradit, and Tha Pla district, Uttaradit province, Thailand are considered as high potential landslide areas. Still, this disaster is difficult to address because of complex factors controlling its occurrence. Therefore, the prediction of the potential landslide area using a landslide susceptibility map has been able to accomplish as a great strategy for the disaster. A landslide susceptibility map was produced by the geographic information system (GIS) data. The methods were initially conducted by the selection of potential factors related to landslides, which were lithology, slope, aspect, plan curvature, profile curvature, distance to stream, land use, and rainfall. All factors were assigned coefficients weight, and analyses frequency ratio (FR). Then, the weighted variables have been combined and ranked into five different susceptibility levels, which were very low, low, medium, high, and very high. Finally, the produced landslide susceptibility map has been validated by the success rate and prediction rate. After the analysis, the high and the very high landslide susceptibility area were dominantly covered in the northern and northwest parts of the study area; and the factor of slope, land use, and lithology potentially caused the landslide risk indicated by high frequency ratio values. In addition, the produced landslide susceptibility map had high accuracy, about 90% of success rate and prediction rate, calculated from the area under the curve (AUC), this map would be beneficial for geological hazard management and land use planning. The landslide susceptibility map and the GIS-based methods can be applied to the regional area with additional benefits to well-being, society, and the environment.

Spatial Analysis of Landslide Prone Areas in Tidore Island Indonesia

The topographic condition of Tidore Island, where 50% of the area is on a steep slope, makes Tidore Island prone to landslides during the rainy season. This research aims to spatially identify landslide prone areas in Tidore Island using slope morphology method. SMORPH method is conducted by identifying and classifying potential landslide areas based on slope shape and slope angle matrix. The result of this study shows that high landslide potential area is 2,569.42 ha, medium potential area is 3,296.99 ha, low potential area is 4,778.46 ha, and very low potential area is 1,126.55 ha. Among the sub-districts in Tidore Island, North Tidore has the largest presentation area of 892.48 ha. It can be concluded that areas with steep slopes and convex or concave slope shapes have higher landslide potential. The findings of this research are expected to help local government in future spatial planning efforts for landslide mitigation.

Landslide Susceptibility Mapping in Ampang Jaya: Comparing Probabilistic Method and Weighted Overlay Method

When it came time to produce the map, the entire district of Ampang Jaya was chosen as the area for the research. These two approaches gave very different results in terms of accuracy. The results of the map were categorised using a range of different classification techniques, some of which include Natural Breaks and Equal Interval, respectively. Various landslide susceptibility hazard zoning results were found when the two different classification systems were applied to the data. These zoning areas need to go through an accuracy assessment process in order to be validated. The accuracy of the model was evaluated by comparing the findings about the historical locations of landslide occurrences with the findings regarding the susceptibility hazard locations of potential landslide areas. Because the accuracy of the Probabilistic technique was 66.67% for Equal Interval and 73.33% for Natural Breaks, respectively, this demonstrates that the Probabilistic method produces more dependable results than the Weighted Overlay method produces. Therefore, the accuracy assessment results indicate that the probabilistic method provides more reliable information for accuracy assessment than the Weighted Overlay method. This is due to the fact that the result of the accuracy assessment obtained from Weighted Overlay is significantly lower than that obtained from Probabilistic for each classification technique.

Early detection of potential landslides along high‐speed railway lines: A pressing issue

AbstractEarly detection of landslides is important for prevention and mitigation of landslide disasters. Especially, accurately identifying potential landslides along high‐speed railway is becoming a pressing issue for operation safety of high‐speed railway. Here, 161 Sentinel‐1A satellite images from March 2017 to September 2022 were acquired to detect potential landslides along the Lanzhou‐Urumqi high‐speed railway (LUHR) in Qinghai. Results show that rainfall is the main cause for the transition from secondary creep (steady state) to tertiary creep (accelerated) at the Jiujiawan landslide. The hot spot analysis method was used to cluster the average line‐of‐sight deformation velocity along the LUHR, effectively extracting five deformation zones that may pose a threat. Optical satellite image analysis revealed four potential landslides and one unstable slope. Furthermore, the rescaled range analysis documented that the Hurst exponent is greater than 0.8 for all four potential landslide instability points, implying that the identified potential landslide areas are still in motion and may pose a threat to the operation of the LUHR. On this basis, we propose a framework for early identification and monitoring of landslides along the high‐speed railway lines that supports landslide hazard managing with the goal to reduce landslide risk.

Permanent displacement characteristics of landslides taking into consideration the frequency and energy behaviour of historical seismic ground motions

Landslides often occur along motorways in earthquake-prone areas, leading to casualties and the loss of property. Most previous studies have applied the simplified Newmark method to assess landslide susceptibility at a regional scale, ignoring the characteristics of local ground motions. In this study, we investigated permanent displacement characteristics of three potential landslide areas along the Dayong Expressway using the rigorous Newmark method that considers the frequency and energy characteristics of historical seismic waves. First, the frequency characteristics of historical earthquakes in the study areas were analysed using the fast Fourier transform method and were adopted as input ground motions in calculating the Newmark displacement. Next, the critical accelerations of the three study areas were computed. Parameters such as the elevation, soil layer thickness and soil strength that are required for critical acceleration calculations were obtained using high-precision ( c. 3 cm) unmanned aerial vehicle mapping technology, drilling operations and laboratory tests. Finally, the Newmark displacement was calculated and the landslide susceptibility of the study areas was evaluated. The results showed that the predominant frequency of historical seismic waves in the study areas was 0.38–3.36 Hz, indicating low-frequency characteristics. The results also indicated that the frequency and energy characteristics of the seismic ground motions significantly influenced the Newmark displacement. The maximum Newmark displacement under different waveforms at Damieju ranged from 2 to 18 cm. Under the most dangerous conditions, all three areas showed a potential for landslides. The maximum Newmark displacement positively correlated with the energy of the predominant frequency. The large-energy and low-frequency characteristics of the seismic wave correspond to a large displacement. The simplified Newmark method when used in regional landslide susceptibility analysis did not reflect this effect and may be unsuitable to determine the size of landslides.

A Case Study Integrating Numerical Simulation and InSAR Monitoring to Analyze Bedding-Controlled Landslide in Nanfen Open-Pit Mine

Bedding-controlled landslides are a common geological hazard for open-pit metal mines and occur on layered rock slopes. It can spread spatially over the final boundary of the dip slope and persist throughout the entire life cycle of the mine, substantially compromising the safety of mining operations. Identifying potential landslide areas and determining the landslide mechanism is crucial for the safety production and slope management of mines. This study proposes a combination of satellite radar interferometry measurement and numerical simulation to determine the landslide mechanism of the bedding-controlled slope in open-pit mines. First, the multidimensional small baseline subset (MSBAS) technique of interferometric synthetic aperture radar (InSAR) is used to capture deformation information in the vertical and east–west directions of the slope, locate large-scale and long-term movements, and preliminarily determine the trend of landslides. Then, a layered slope damage constitutive model is established, and a three-dimensional stability calculation of the layered slope is performed using COMSOL Multiphysics 5.3 software based on the strength reduction method to study the development and evolution process of landslides. The effectiveness of the method is validated by a large-scale bedding-controlled slope failure in the Nanfen open-pit mine in Liaoning, China, revealing the failure mechanism of the slope under excavation conditions. The study shows that the eastern slope bedding-controlled landslide in the Nanfen open-pit mine is a multizone composite-mode landslide caused by excavation, which belongs to the shear–slip–tension deformation failure mechanism as a whole. This study provides a new method for analyzing the mechanism of layered rock slope landslides under mining activities in open-pit mines, which can be used to assess and predict similar landslides.

Hydrologic-geotechnical modelling of shallow landslide and flood hazards caused by heavy rainfall

Landslides and flooding are two of the most common hazards associated with heavy rainfall. Most studies, however, tackle the occurrence of these hazards separately or independently. Therefore, this study introduces a catchment-scale, multihazard approach that unifies the assessment of both phenomena through a combination of hydrological and geotechnical principles. By incorporating surface flow, infiltration, and slope stability analyses, the spatio-temporal response of both landslides and flooding during intense or heavy rainfall is characterized. To improve computational efficiency, a hybrid approach, consisting of the zero- and local-inertia flow models, is introduced to approximate the surface flow. Additionally, rainfall infiltration is estimated using the one-dimensional Green-Ampt model, and the results are incorporated in a deterministic slope stability analysis whose failure mechanism is generated from the forces arising from the effects of surface flow and the downward propagation of water along the assumed failure surface. The model is applied in the catchment of Marumori Town, Japan which suffered numerous landslide and flooding disasters during Typhoon Hagibis in 2019. The results indicate that the proposed model successfully simulates the hydrologic and geotechnical response of the catchment showing the distribution of both unstable slopes and inundated areas indicative of landslide and flooding hazards. The model’s capability to identify the timing and location of potential landslide and flood-prone areas could provide a practical framework for a unified early warning system, enhancing emergency planning and response efforts during heavy rainfall.

Landslide susceptibility prediction using frequency ratio model: a case study of Uttarakhand, Himalaya (India)

The purpose of this study is to develop a landslide susceptibility prediction model by applying the Frequency Ratio (FR) model and remote sensing data sets for the Northern part of Uttarakhand, India. First, a landslide inventory was carried out from the interpretation of satellite images. Thereafter, the landslide inventory points were randomly separated into training and validation datasets. Subsequently, the significant landslide causative factors such as slope, lithology, lineament density, land use/land cover, drainage density, aspect, elevation, road buffer, normalized differential vegetation index (NDVI), stream power index, and topographic wetness index were identified to run the model set up. Next, applying the FR statistical model in a GIS environment for development of landslide susceptibility index map and divided into five distinct landslide susceptibility zones (very low, low, moderate, high, and very high). To validate the results, the Receiver Operating Characteristics (ROC) curve were developed to check the accurrancy of the model, and it was observed that the prediction value of the FR model was reasonably accurate (86.1% at 95% confidence level). The output LSI map would be helpful for the government and planners to map and monitor potential landslide areas and mitigate the hazards.

Spatial Analysis of Landslide-Prone Areas in Damer District, Maluku Barat Daya Regency, Maluku Province

Based on historical data on landslide events, Damer District is an area prone to landslides in Southwest Maluku Regency. One of the first steps in mitigating landslides in Damer District is to map areas that have the potential for landslides. The purpose of this study was to determine the spatial distribution of landslide-prone areas in Damer District, Southwest Maluku Regency. This study uses the SMORPH method to identify and classify areas that have the potential for landslides based on the matrix between the shape of the slope and the angle of the slope. This study resulted in 4 levels of landslide potential areas, namely very low, low, medium and high potential. Villages with high landslide potential are Wulur Village and villages with very low landslide potential are Ilih Village. The results of this study also illustrate that the higher the slope accompanied by the formation of convex or concave slopes, the higher the potential for landslides to occur. The results of the research are expected to help the Southwest Maluku Regency government, especially the Damer District government, in an effort to spatial planning based on disaster mitigation.Spatial Analysis

Modeling the area of co-seismic landslides via data-driven models: The Kaikōura example

The last three decades have witnessed substantial developments in data-driven models for landslide prediction. However, this improvement has been mostly devoted to models that estimate locations where landslides may occur, i.e., landslide susceptibility. Although susceptibility is crucial when assessing landslide hazard, another equally important piece of information is the potential landslide area once landslides initiate on a given slope.This manuscript addresses this gap in the literature by using a Generalized Additive Model whose target variable is the topographically-corrected landslide areal extent at the slope unit level. In our case, the underlying assumption is that the variability of landslide areas across the geographic space follows a Log-Normal probability distribution. We test this framework on co-seismic landslides triggered by the Kaikōura earthquake (7.8 Mw on November 13th 2016). The model performance was evaluated using random and spatial cross-validation. Additionally, we simulated the expected landslide area over slopes in the entire study area, including those that did not experience slope failures in the past.The performance scores revealed a moderate to strong correlation between the observed and predicted landslide areas. Moreover, the simulations show coherent patterns, suggesting that it is worth extending the landslide area prediction further. We share data and codes in a GitHub repository https://github.com/mmorenoz/GAM_LandslideSize to promote the repeatability and reproducibility of this research.