Electrical resistivity tomography and digital aerial photogrammetry in the research of the “Bachledzki Hill” active landslide – in Podhale (Poland)

Kamiński, Mirosław; Zientara, Piotr; Krawczyk, Mirosław

doi:10.1016/j.enggeo.2021.106004

Cited by 19 publications

(7 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The purpose of object detection in aerial images is to locate objects of interest on the ground and recognize their categories by a bounding box [15], [34]. Each bounding box not only contains the object coordinate information, but also contains the category information.…”

Section: Related Workmentioning

confidence: 99%

“…Compared to objects in general natural scenes, objects in aerial images usually have smaller size, higher density, objects with different size, worse imaging quality, and more complex background [14], [15]. Therefore, it is difficult to directly achieve a satisfying recognition performance in aerial images using the existing natural scene object detectors.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Learning Calibrated-Guidance for Object Detection in Aerial Images

Liang¹,

Wei²,

Zhang³

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

Object detection is one of the most fundamental yet challenging research topics in the domain of computer vision. Recently, the study on this topic in aerial images has made tremendous progress. However, complex background and worse imaging quality are obvious problems in aerial object detection. Most state-of-the-art approaches tend to develop elaborate attention mechanisms for the space-time feature calibrations with arduous computational complexity, while surprisingly ignoring the importance of feature calibrations in channel-wise. In this work, we propose a simple yet effective Calibrated-Guidance (CG) scheme to enhance channel communications in a feature transformer fashion, which can adaptively determine the calibration weights for each channel based on the global feature affinity correlations. Specifically, for a given set of feature maps, CG first computes the feature similarity between each channel and the remaining channels as the intermediary calibration guidance. Then, re-representing each channel by aggregating all the channels weighted together via the guidance operation. Our CG is a general module that can be plugged into any deep neural networks, which is named as CG-Net. To demonstrate its effectiveness and efficiency, extensive experiments are carried out on both oriented object detection task and horizontal object detection task in aerial images. Experimental results on two challenging benchmarks (i.e., DOTA and HRSC2016) demonstrate that our CG-Net can achieve the new state-of-the-art performance in accuracy with a fair computational overhead. The source code has been open sourced at https://github.com/WeiZongqi/CG-Net

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Learning Calibrated-Guidance for Object Detection in Aerial Images

Liang¹,

Wei²,

Zhang³

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

show abstract

“…3D electrodes arrangement with suitable separations is time-consuming to estimate the volume of vulnerable geological materials in landslide cases (Whiteley et al 2019). However, 2D projections of parallel lines are arranged in 3D space with constant separation to perform a 3D survey, achieving incredible depth (Kamiński et al 2021). The measurements accomplished in this way can be combined into a 3D three-dimensional inversion software (e.g., Earthimager3D) with the spatial dataset for processing.…”

Section: Electrical Resistivity Tomographymentioning

confidence: 99%

“…Occasionally, they have damaged residential buildings, roads, and power grids. Hence, precise identi cation of future landslides and their extent, volume, and activity is vital for disaster management (Kamiński et al 2021). Currently, rainfall-induced landslides are dominant in the Karakorum ranges.…”

Section: Introductionmentioning

confidence: 99%

Landslide Hazard Assessment and Runout Simulation by Utilizing Remote Sensing, Geophysical, and Geological Techniques

Ullah

et al. 2022

Preprint

View full text Add to dashboard Cite

Landslide events in Karakorum ranges are frequent and have already damaged local infrastructures and roads. In the hilly regions, landslide characterization and predicting its deposition pattern are essential for accurate engineering hazard assessment. To this end, numerical simulation models are commonly used tools. However, appropriate model parameters are often not available to predict and generate real landslide scenarios. This work describes the use of multidisciplinary techniques to estimate the model parameters for a slope prone to landslide and simulate the hazard level. The first important parameter, landslide boundary, and dynamics were estimated from temporal satellite images by identifying the areas with prominent deformations using the Interferometric Synthetic Aperture Radar (InSAR) technique. The susceptible subsurface strata volume and the possible landslide initiation depth were determined with the electrical resistivity method. In addition, voxel 3D electrical resistivity models were created to present the depth of the existing rupture and the nature of subsurface strata. The soil mechanical parameters were calculated during field visits and laboratory tests. The parameters adopted from different techniques helped simulate the susceptible landslide volume and initiation depth. These parameters are a critical factor in developing an accurate high-speed landslide model through numerical simulation. The applied methodology is vital to understand the dynamics of a particular slope and perform accurate engineering hazard assessment with numerical simulation. The results are essential to predict the potential deposition areas of the landslide event accurately, minimize the risk level, and take proactive mitigation measures.

show abstract

“…집중호우시에 사면에서 무너질 가능성이 있는 구간 을 파악하는 것이 목적으로, 사면의 3D 지질모델을 구성 하는 경우도 있다 (Maio et al, 2020). 사면의 수문학적 3D 지질모델을 구성하게 되면 산사태 조기경보 시스템 을 구성할 수 있으며, 이 경우 전기비저항 탐사가 유용 하게 사용된다 (Maio et al, 2020) (Kamiński et al, 2021) Polar plots are plotted in the same color scale, with spectral amplitude normalized to f1 spectral value at S7. In each plot, frequency values and related vibration directions are highlighted in red for f1, in green for f2, and in red for f3 (Colombero et al, 2017).…”

Section: 산사태 종류와 발생 요인 별 지구 물리 특성unclassified

A Review on Past Cases of Geophysical Explorations for Assessment of Slope Stability

Cho

Joung

Jeong

et al. 2022

Econ. Environ. Geol.

View full text Add to dashboard Cite

Since landslide can cause huge damages to many facilities, close characterization of slopes is needed for appropriate reinforcements for the unstable ones in order to prevent the damages. Geophysical surveys, which can characterize a large area at a relatively low cost without disturbing slopes, have been widely employed for the assessment of slope stability in other countries. However, only conventional direct investigation methods are mainly used in Korea. In this paper, we analyzed various cases, which evaluated slope stabilities by characterizing slopes using geophysical exploration. First, we introduced changes in geophysical properties due to unstable media of slope like fracture location, fracture connectivity and distribution of groundwater level, and subsequently discussed the applicability of geophysical methods to the detection of the changes; the methods include electrical resistivity survey, seismic survey, self-potential survey, induced polarization survey and ground penetrating radar. Based on this description, we analyzed how geophysical surveys were performed on various slopes.

show abstract

Electrical resistivity tomography and digital aerial photogrammetry in the research of the “Bachledzki Hill” active landslide – in Podhale (Poland)

Cited by 19 publications

References 26 publications

Learning Calibrated-Guidance for Object Detection in Aerial Images

Learning Calibrated-Guidance for Object Detection in Aerial Images

Landslide Hazard Assessment and Runout Simulation by Utilizing Remote Sensing, Geophysical, and Geological Techniques

A Review on Past Cases of Geophysical Explorations for Assessment of Slope Stability

Contact Info

Product

Resources

About