ADAtools: Automatic Detection and Classification of Active Deformation Areas from PSI Displacement Maps

Navarro, José A.; Tomás, Roberto; Barra, Anna; Pagán, José Ignacio; Reyes-Carmona, Cristina; Solari, Lorenzo; López‐Vinielles, Juan; Falco, Salvatore Di; Crosetto, Michele

doi:10.3390/ijgi9100584

Cited by 30 publications

(34 citation statements)

References 39 publications

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“…Existing approaches for detecting ADAs from InSAR data [29][30][31][32] focus on the delineation of the more reliable deforming areas through the aggregation of subsets of points obtained by filtering the raw LOS ground velocity map. First, in order to filter the LOS ground velocity map, these approaches usually select the moving points using an absolute velocity threshold equal to 2σ (two times the standard deviation of the raw LOS ground velocity map).…”

Section: Discussionmentioning

confidence: 99%

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Combining Satellite InSAR, Slope Units and Finite Element Modeling for Stability Analysis in Mining Waste Disposal Areas

et al. 2021

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Slope failures pose a substantial threat to mining activity due to their destructive potential and high probability of occurrence on steep slopes close to limit equilibrium conditions, which are often found both in open pits and in waste and tailing disposal facilities. The development of slope monitoring and modeling programs usually entails the exploitation of in situ and remote sensing data, together with the application of numerical modeling, and it plays an important role in the definition of prevention and mitigation measures aimed at minimizing the impact of slope failures in mining areas. In this paper, a new methodology is presented; one that combines satellite radar interferometry and 2D finite element modeling for slope stability analysis at a regional scale, and applied within slope unit polygons. Although the literature includes many studies applying radar interferometry and modeling for slope stability analysis, the addition of slope units as input data for radar interferometry and modeling purposes has, to our knowledge, not previously been reported. A former mining area in southeast Spain was studied, and the method proved useful for detecting and characterizing a large number of unstable slopes. Out of the 1959 slope units used for the spatial analysis of the radar interferometry data, 43 were unstable, with varying values of safety factor and landslide size. Out of the 43 active slope units, 21 exhibited line of sight velocities greater than the maximum error obtained through validation analysis (2.5 cm/year). Finally, this work discusses the possibility of using the results of the proposed approach to devise a proxy for landslide hazard. The proposed methodology can help to provide non-expert final users with intelligible, clear, and easily comparable information to analyze slope instabilities in different settings, and not limited to mining areas.

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Section: Discussionmentioning

confidence: 99%

“…The proposed approach builds upon previously published works aimed at detecting active deformation areas [29][30][31][32]. In those studies, however, the topography was only taken into account to discern flat areas from hill slopes; the concept of SU was not considered, and no stability analyses were performed.…”

Section: Introductionmentioning

confidence: 99%

Combining Satellite InSAR, Slope Units and Finite Element Modeling for Stability Analysis in Mining Waste Disposal Areas

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…Existing approaches for detecting ADAs from InSAR data [29][30][31][32] focus on the delineation of the more reliable deforming areas through the aggregation of subsets of points obtained by filtering the raw LOS ground velocity map. Firstly, in order to filter the LOS ground velocity map, these approaches usually select the moving points using an absolute velocity threshold equal to 2σ (two times the standard deviation of the raw LOS ground velocity map).…”

Section: Discussionmentioning

confidence: 99%

“…The proposed approach builds upon previously published works aimed at detecting active deformation areas [29][30][31][32]. In these studies, however, the topography is only taken into account to discern flat areas from hill slopes-the concept of SU is not considered, and no stability analyses are performed.…”

Section: Introductionmentioning

confidence: 99%

Combining Satellite InSAR, Slope Units and Finite Element Modeling for Stability Analysis in Mining Waste Disposal Areas

López‐Vinielles¹,

Merodo²,

Ezquerro³

et al. 2021

Preprint

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Slope failures pose a substantial threat to mining activity due to their destructive potential and high probability of occurrence on steep slopes close to limit equilibrium conditions, often found both in open pits and in waste and tailing disposal facilities. The development of slope monitoring and modeling programs usually entails the exploitation of in situ and remote sensing data together with the application of numerical modeling, and it plays an important role in the definition of prevention and mitigation measures aimed at minimizing the impact of slope failures in mining areas. Here we present a new methodology combining satellite radar interferometry and 2D finite element modeling for slope stability analysis at a regional scale, applied within slope unit polygons. We studied a former mining area in southeast Spain, and the method proved useful in detecting and characterizing a considerably large number of unstable slopes. Out of 1,959 slope units used for the spatial analysis of the radar interferometry data, 43 were unstable, with varying values of safety factor and landslide size. Out of the 43 active slope units, 21 exhibited line of sight velocities greater than the maximum error obtained through the validation analysis (2.5 cm/year). Eventually, this work discusses the possibility of using the results of the proposed approach to devise a proxy for landslide hazard. The proposed methodology can help to provide non-expert final users with intelligible, clear and easily comparable information to analyze slope instabilities in different settings, not limited to mining areas.

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“…This method has been applied in geohazards mapping [26][27][28], geological motion assessment, and the intensity evaluation of landslides [26,29,30] based on the deformation velocity. On the basis of this method, some automatic identification and classification programs have been proposed [18,31]. In addition, some Geographic Information System (GIS) environment-based studies also combined the hazards and vulnerability of the study area to calculate the specific landslide risk [32,33].…”

Section: Introductionmentioning

confidence: 99%

An Improved Method for Automatic Identification and Assessment of Potential Geohazards Based on MT-InSAR Measurements

et al. 2021

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Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) has been widely used for ground motion identification and monitoring over large-scale areas, due to its large spatial coverage and high accuracy. However, automatically locating and assessing the state of the ground motion from the massive Interferometric Synthetic Aperture Radar (InSAR) measurements is not easy. Utilizing the spatial-temporal characteristics of surface deformation on the basis of the Small Baseline Subsets InSAR (SBAS-InSAR) measurements, this study develops an improved method to locate potential unstable or dangerous regions, using the spatial velocity gradation and the temporal evolution trend of surface displacements in large-scale areas. This method is applied to identify the potential geohazard areas in a mountainous region in northwest China (Lajia Town in Qinghai province) using 73 and 71 Sentinel-1 images from the ascending and descending orbits, respectively, and an urban area (Dongguan City in Guangdong province) in south China using 32 Sentinel-1 images from the ascending orbit. In the mountainous area, 23 regions with potential landslide hazards have been identified, most of which have high to very high instability levels. In addition, the instability is the highest at the center and decreases gradually outward. In the urban area, 221 potential hazards have been identified. The moderate to high instability level areas account for the largest proportion, and they are concentrated in the farmland irrigation areas, and construction areas. The experiment results show that the improved method can quickly identify and evaluate geohazards on a large scale. It can be used for disaster prevention and mitigation.

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ADAtools: Automatic Detection and Classification of Active Deformation Areas from PSI Displacement Maps

Cited by 30 publications

References 39 publications

Combining Satellite InSAR, Slope Units and Finite Element Modeling for Stability Analysis in Mining Waste Disposal Areas

Combining Satellite InSAR, Slope Units and Finite Element Modeling for Stability Analysis in Mining Waste Disposal Areas

Combining Satellite InSAR, Slope Units and Finite Element Modeling for Stability Analysis in Mining Waste Disposal Areas

An Improved Method for Automatic Identification and Assessment of Potential Geohazards Based on MT-InSAR Measurements

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