Automated processing of high resolution airborne images for earthquake damage assessment

Nex, Francesco; Rupnik, Ewelina; Toschi, I.; Remondino, Fabio

doi:10.5194/isprsarchives-xl-1-315-2014

Cited by 13 publications

(15 citation statements)

References 41 publications

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“…UAV was also used for the environmental modelling of an open-pit gravel mine and for measuring the volumetric change [18]. Buildings and morphological changes after earthquakes can be surveyed by UAV-based technique [19] as well, and the data acquisition could also be supported by terrestrial laser scanning [20]. The investigations showcased the potential of the combined technologies in surveying vertical structures and complex buildings with high accuracy.…”

Section: Introductionmentioning

confidence: 99%

Application of UAV in Topographic Modelling and Structural Geological Mapping of Quarries and Their Surroundings—Delineation of Fault-Bordered Raw Material Reserves

Török

Bögöly

Somogyi

et al. 2020

Sensors

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A 3D surface model of an active limestone quarry and a vegetation-covered plateau was created using unmanned aerial vehicle (UAV) technique in combination with terrestrial laser scanning (TLS). The aim of the research was to identify major fault zones that dissect the inaccessible quarry faces and to prepare a model that shows the location of these fault zones at the entire study area. An additional purpose was to calculate reserves of the four identified lithological units. It was only possible to measure faults at the lowermost two meters of the quarry faces. At the upper parts of the quarry and on the vegetation-covered plateau where no field geological information was available, remote sensing was used. Former logs of core drillings were obtained for the modelling of the spatial distribution of four lithological units representing cover beds and various quality of limestone reserves. With the comparison of core data, field measurements and remote sensing, it was possible to depict major faults. Waste material volumes and limestone reserves were calculated for five blocks that are surrounded by these faults. The paper demonstrates that, with remote sensing and with localised control field measurements, it is possible: (a) to provide all geometric data of faults and (b) to create a 3D model with fault planes even at no exposure or at hardly accessible areas. The surface model with detected faults serves as a basis for calculating geological reserves.

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Section: Introductionmentioning

confidence: 99%

Application of UAV in Topographic Modelling and Structural Geological Mapping of Quarries and Their Surroundings—Delineation of Fault-Bordered Raw Material Reserves

Török

Bögöly

Somogyi

et al. 2020

Sensors

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“…RPAS has been increasingly used in engineering geology in historical landslide mapping (Jovanče-vić et al, 2016) and in slope stability analyses (Niethammer et al, 2012;Fraštia et al, 2014) as well as in other natural disasters such as earthquakes (Gerke and Kerle, 2011;Nex et al, 2014) or floods (Feng et al, 2015). RPAS can also be combined with terrestrial laser scanning (TLS) since both remote sensing tools provide high-precision terrain measurement (Fanti et al, 2013;Assali et al, 2014;Francioni et al, 2014;Manconi and Giordan, 2015).…”

Section: Introductionmentioning

confidence: 99%

Slope stability and rockfall assessment of volcanic tuffs using RPAS with 2-D FEM slope modelling

Török

Barsi

Bögöly

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. Steep, hardly accessible cliffs of rhyolite tuff in NE Hungary are prone to rockfalls, endangering visitors of a castle. Remote sensing techniques were employed to obtain data on terrain morphology and to provide slope geometry for assessing the stability of these rock walls. A RPAS (Remotely Piloted Aircraft System) was used to collect images which were processed by Pix4D mapper (structure from motion technology) to generate a point cloud and mesh. The georeferencing was made by Global Navigation Satellite System (GNSS) with the use of seven ground control points. The obtained digital surface model (DSM) was processed (vegetation removal) and the derived digital terrain model (DTM) allowed cross sections to be drawn and a joint system to be detected. Joint and discontinuity system was also verified by field measurements. On-site tests as well as laboratory tests provided additional engineering geological data for slope modelling. Stability of cliffs was assessed by 2-D FEM (finite element method). Global analyses of cross sections show that weak intercalating tuff layers may serve as potential slip surfaces. However, at present the greatest hazard is related to planar failure along ENE-WSW joints and to wedge failure. The paper demonstrates that RPAS is a rapid and useful tool for generating a reliable terrain model of hardly accessible cliff faces. It also emphasizes the efficiency of RPAS in rockfall hazard assessment in comparison with other remote sensing techniques such as terrestrial laser scanning (TLS).

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“…With the goal to improve the efficiency, three major components of the Gabor texture feature images can be extracted using principal component analysis (PCA) [31], and quantified into the Gabor texture quantization feature F GAB (z) using Equations (1) and (2). By tuning to various scales and orientations in frequency space, the Gabor texture quantization feature F GAB (z) gives a detailed and robust delineation of the information.…”

Section: Feature Extractionmentioning

confidence: 99%

“…Rapid earthquake damage mapping of the affected areas is a fundamental and key task for earthquake damage assessment, relief, and mitigation [1,2]. The segmentation of post-earthquake images is particularly crucial in the process of mapping damaged areas as it directly reflects the locations that require urgent rescue efforts.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Post-Earthquake Image Segmentation with an Adaptive Spectral-Spatial Descriptor

Sun

Hao²,

Chen³

et al. 2017

Remote Sensing

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Abstract:The region merging algorithm is a widely used segmentation technique for very high resolution (VHR) remote sensing images. However, the segmentation of post-earthquake VHR images is more difficult due to the complexity of these images, especially high intra-class and low inter-class variability among damage objects. Herein two key issues must be resolved: the first is to find an appropriate descriptor to measure the similarity of two adjacent regions since they exhibit high complexity among the diverse damage objects, such as landslides, debris flow, and collapsed buildings. The other is how to solve over-segmentation and under-segmentation problems, which are commonly encountered with conventional merging strategies due to their strong dependence on local information. To tackle these two issues, an adaptive dynamic region merging approach (ADRM) is introduced, which combines an adaptive spectral-spatial descriptor and a dynamic merging strategy to adapt to the changes of merging regions for successfully detecting objects scattered globally in a post-earthquake image. In the new descriptor, the spectral similarity and spatial similarity of any two adjacent regions are automatically combined to measure their similarity. Accordingly, the new descriptor offers adaptive semantic descriptions for geo-objects and thus is capable of characterizing different damage objects. Besides, in the dynamic region merging strategy, the adaptive spectral-spatial descriptor is embedded in the defined testing order and combined with graph models to construct a dynamic merging strategy. The new strategy can find the global optimal merging order and ensures that the most similar regions are merged at first. With combination of the two strategies, ADRM can identify spatially scattered objects and alleviates the phenomenon of over-segmentation and under-segmentation. The performance of ADRM has been evaluated by comparing with four state-of-the-art segmentation methods, including the fractal net evolution approach (FNEA, as implemented in the eCognition software, Trimble Inc., Westminster, CO, USA), the J-value segmentation (JSEG) method, the graph-based segmentation (GSEG) method, and the statistical region merging (SRM) approach. The experiments were conducted on six VHR subarea images captured by RGB sensors mounted on aerial platforms, which were acquired after the 2008 Wenchuan Ms 8.0 earthquake. Quantitative and qualitative assessments demonstrated that the proposed method offers high feasibility and improved accuracy in the segmentation of post-earthquake VHR aerial images.

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Automated processing of high resolution airborne images for earthquake damage assessment

Cited by 13 publications

References 41 publications

Application of UAV in Topographic Modelling and Structural Geological Mapping of Quarries and Their Surroundings—Delineation of Fault-Bordered Raw Material Reserves

Application of UAV in Topographic Modelling and Structural Geological Mapping of Quarries and Their Surroundings—Delineation of Fault-Bordered Raw Material Reserves

Slope stability and rockfall assessment of volcanic tuffs using RPAS with 2-D FEM slope modelling

Dynamic Post-Earthquake Image Segmentation with an Adaptive Spectral-Spatial Descriptor

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