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Christine Authemayou Olivier Bellier Dominique Chardon Zaman Malekzade Mohammad Abassi 《Comptes Rendus Geoscience》2005,337(5):539-545
Field structural and SPOT image analyses document the kinematic framework enhancing transfer of strike-slip partitioned motion from along the backstop to the interior of the Zagros fold-and-thrust belt in a context of plate convergence slight obliquity. Transfer occurs by slip on the north-trending right-lateral Kazerun Fault System (KFS) that connects to the Main Recent Fault, a major northwest-trending dextral fault partitioning oblique convergence at the rear of the belt. The KFS formed by three fault zones ended by bent orogen-parallel thrusts allows slip from along the Main Recent Fault to become distributed by transfer to longitudinal thrusts and folds. To cite this article: C. Authemayou et al., C. R. Geoscience 337 (2005). 相似文献
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The characterisation the vertical profiles and cross-sections of roads is important for the verification of proper construction and road safety assessment. The goal of this paper is the extraction of geometric parameters through the automatic processing of mobile LiDAR system (MLS) point clouds. Massive and complex datasets provided by the MLS are processed using a hierarchical strategy that includes segmentation, principal component analysis (PCA)-based orthogonal regression, filtering and parameter extraction procedures. Best-fit geometric parameters act as a vertical road model for both linear parameters (slope and vertical curves) and cross-sections (superelevations). The proposed automatic processing approach gives satisfactory results for the analysed scenario. 相似文献
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Automatic urban object detection from airborne remote sensing data is essential to process and efficiently interpret the vast amount of airborne imagery and Laserscanning (ALS) data available today. This paper combines ALS data and airborne imagery to exploit both: the good geometric quality of ALS and the spectral image information to detect the four classes buildings, trees, vegetated ground and sealed ground. A new segmentation approach is introduced which also makes use of geometric and spectral data during classification entity definition. Geometric, textural, low level and mid level image features are assigned to laser points which are quantified into voxels. The segment information is transferred to the voxels and those clusters of voxels form the entity to be classified. Two classification strategies are pursued: a supervised method, using Random Trees and an unsupervised approach, embedded in a Markov Random Field framework and using graph-cuts for energy optimization. A further contribution of this paper concerns the image-based point densification for building roofs which aims to mitigate the accuracy problems related to large ALS point spacing.Results for the ISPRS benchmark test data show that to rely on color information to separate vegetation from non-vegetation areas does mostly lead to good results, but in particular in shadow areas a confusion between classes might occur. The unsupervised classification strategy is especially sensitive in this respect. As far as the point cloud densification is concerned, we observe similar sensitivity with respect to color which makes some planes to be missed out, or false detections still remain. For planes where the densification is successful we see the expected enhancement of the outline. 相似文献
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《国际泥沙研究》2016,(2):97-109
The determination of grain size distribution in alluvial channels plays a crucial role in understanding fluvial dynamics and processes (e.g., hydraulic resistance, sediment transport and erosion, and habitat suitability). However, to determine an accurate distribution, tremendous field efforts are often required. Traditionally, the grain size distribution of channel beds have been obtained by manually counting a set of randomly selected stones (the“pebble count”). Based on this elementary principle, many authors have proposed different adaptations to overcome weaknesses and problems with the original method; with the development of digital technology, photographic methods have been developed in order to sig-nificantly reduce the time spent in the field. Two of these“image-assisted”methods include Automated Grain Sizing, AGS, and Manual Photo Sieving, MPS. In this study, AGS and MPS were applied under ideal laboratory conditions, to be used as reference, and in two field conditions with different degrees of difficulty in terms of visual determination of the grain size distribution; these included an artificial unlined channel and two natural mountainous streams. The results were compared with those obtained with the pebble-count method. In general, strong agreement between the methods was found when they were applied under favorable conditions (”the laboratory”), and the differences between the image-assisted and pebble count methods were similar to those found in previous studies. Despite being more time consuming, MPS was deemed preferable to AGS when conditions are not optimal;in these cases, the time spent on image elaboration significantly increased in the AGS method (approximately three-fold), but the estimation error of the median grain size decreased by approximately 37%. The use of image-assisted analysis has proven to be robust for characterizing sediment in watercourse beds and reducing fieldwork time, but because field conditions can significantly affect the accuracy of results, the method choice must be carefully considered. 相似文献
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This paper investigates the stability of an automatic system for classifying kerogen material from images of sieved rock samples.
The system comprises four stages: image acquisition, background removal, segmentation, and classification of the segmented
kerogen pieces as either inertinite or vitrinite. Depending upon a segmentation parameter d, called “overlap”, touching pieces of kerogen may be split differently. The aim of this study is to establish how robust
the classification result is to variations of the segmentation parameter. There are two issues that pose difficulties in carrying
out an experiment. First, even a trained professional may be uncertain when distinguishing between isolated pieces of inertinite
and vitrinite, extracted from transmitted-light microscope images. Second, because manual labelling of large amount of data
for training the system is an arduous task, we acquired the true labels (ground truth) only for the pieces obtained at overlap
d=0.5. To construct ground truth for various values of d we propose here label-inheritance trees. With thus estimated ground truth, an experiment was carried out to evaluate the
robustness of the system to changes in the segmentation through varying the overlap value d. The average system accuracy across values of d spanning the range from 0 to 1 was 86.5%, which is only slightly lower than the accuracy of the system at the design value
of d=0.5 (89.07%). 相似文献