A table method for coded target decoding with application to 3-D reconstruction of soil specimens during triaxial testing

Photogrammetry-based method is gaining popularity in many fields. One of the main tasks of photogrammetry is to identify the homologous points in multiple images, which is commonly referred to as the corresponding problem. Coded targets are often placed on the surfaces of the targeted objects and have been widely used as a reliable method for solving the corresponding problem in photogrammetry for high-accuracy three-dimensional measurements. Automated recognition and identification of coded targets are of great importance in the coded target-based photogrammetry. However, false coded target identifications are inevitable due to large perspective distortion, unfavorable lighting conditions, and low-resolution, low-quality images, etc. As a result, manual corrections are often required, which are tedious, prone to error, and inefficient. In this paper, a faster R-CNN-based method has been proposed to recognize coded targets. Then, a table method has been developed to automatically identify and reject the falsely identified coded targets by taking advantages of the prior knowledge of the geometric arrangement of the coded targets. Based on that, missing coded targets can be recovered using either interpolation or extrapolation method. The effectiveness and accuracy of the proposed method are validated by implementing it into three-dimensional reconstruction of soil specimens during triaxial testing in geotechnical engineering. Experimental validation results indicate that the proposed method can achieve accurate and efficient coded target recognition and identification.

     

地震同震滑动分布反演平滑因子的确定

针对大地测量地震同震滑动分布反演中平滑因子（又称正则化参数）的确定问题,一般采用模型粗糙度与数据拟合残差之间的折中曲线来确定（为便于区分,本文将该方法称为"L曲线"）。本文在L曲线的基础上提出一种确定平滑因子的新方法——折中相交曲线法。模拟试验反演结果表明,利用折中相交曲线法确定的平滑因子反演地震滑动分布各参数精度要优于L曲线法。利用折中相交曲线法确定平滑因子反演拉奎拉与台湾美浓实际地震,并与L曲线法反演结果进行对比分析。分析结果表明,利用折中相交曲线法确定的平滑因子反演拉奎拉与台湾美浓实际同震滑动分布各参数结果均在国内外其他学者研究的范围内,并且利用折中相交曲线法确定平滑因子较L曲线法具有计算效率高、无需依赖数据拟合度、确定平滑因子大小更为合适等优点。     

武汉市江夏区大桥新区红旗村黏土盖层岩溶塌陷致塌模式分析

武汉市江夏区大桥新区红旗村文化大道附近发生岩溶塌陷,其上覆盖层为黏土。文章针对该类型岩溶塌陷,结合岩溶发育特征、土体物理力学性质、水文地质条件和人类工程活动等影响因素,对致塌模式进行了综合分析,得出在溶沟底部分布有软塑至流塑状的力学性质较差的红黏土,溶沟底部发育的溶蚀裂隙与下部的溶洞或通道相联通;流塑状红黏土流失至下部岩溶通道中,形成土洞;钻探施工、楼房载荷、振动作用加速黏土体的软化、崩解和溶蚀作用,进而加速土洞向上发展。此外,地基开挖减少上覆黏土厚度,降低了土体抗剪强度,最终在上覆土体自身重力和附加荷载作用下发生塌陷。根据土体受力情况,得出塌陷力学模型,并利用数据进行验证,其验证结果与实际相符合,并结合致塌模式和力学分析提出应增强土体抗塌性能、增加建筑物地基稳定性和减缓岩溶系统水动力因素变化的防治措施。      

Critical slip surface and landslide volume of a soil slope under random earthquake ground motions

Finding the critical slip surface and estimating the landslide volume are of primary importance for slope seismic design. However, this may be difficult due to the uncertainty of ground motions. To address this problem, a new method for calculating uncertainties is recommended in this paper, especially for the critical slip surface and landslide volume under random earthquake ground motions. Firstly, a series of intensity–frequency nonstationary random earthquake ground motions were generated based on an improved orthogonal expansion method. A given number of potential slip surfaces were set in a soil slope. Subsequently, the factor of safety (FOS) of each slip surface for all ground motions was calculated and the minimum FOS curves were obtained. It was found that the critical slip surfaces and failure times are uncertain under different earthquakes. The Monte Carlo method was used to verify the accuracy of probability density evolution method (PDEM), and the results of the PDEM and the Monte Carlo method are consistent, meaning that the PEDM has higher computational efficiency. Moreover, the distributions of earthquake-triggered landslide volume and landslide depth were analyzed by considering equivalent extreme events. Both landslide volume and depth exhibit a normal distribution for a homogeneous soil slope. The framework of this study is meaningful for slope seismic design in engineering, for example, the location of critical slip surface can be used for slope reinforcement, and the distribution of sliding volume can be used for disaster assessment.     

Three-dimensional analyses of the sliding surface distribution in the Huangtupo No. 1 riverside sliding mass in the Three Gorges Reservoir area of China

The Huangtupo landslide is one of the largest and most destructive landslides still deforming in the Three Gorges area of China. In recent years, most studies on this landslide have been based on the data obtained from an investigation conducted in 2001. To further elucidate the geological structure and evolution of the landslide, we began building a field test site in the area of the sliding mass with the fastest deformation velocity in 2009. A group of tunnels with a total length of 1.1 km has been excavated, and nine boreholes with depths between 76.8 and 127.1 m have been drilled into the sliding body. Additionally, relative monitoring devices, such as borehole inclinometers and crack meters, have been installed. Based on the findings of the previous investigation and the latest tunneling, drilling, and monitoring data, a spatial distribution model of the sliding surfaces of the Huangtupo No. 1 riverside sliding mass has been established using the discrete smooth interpolation (DSI) method. Significant differences are revealed between the previous proposed sliding surface and the latest monitoring data. We propose that the Huangtupo No. 1 sliding mass has two sliding surfaces. Thus, the sliding mass can be further divided into two secondary sliding bodies, which are named the No. 1-1 (east) and No. 1-2 (west) sliding masses. The No. 1-1 sliding mass slid first, and the material along the western boundary slid later, producing the No. 1-2 sliding body, which has a smaller volume and shallower depth. The areas, volumes, and thicknesses of each sliding body have been calculated using a digital 3D model.     

In situ triaxial creep test for investigating deformational properties of gravelly sliding zone soil: example of the Huangtupo 1# landslide,China

In recent years, numerous landslide catastrophes have occurred, generating considerable financial losses and other tolls. The deformational and mechanical properties of sliding zone soil would be in primary significance to landslide research, as the sliding zone basically controls the initiation and mobility of the landslide. An in situ triaxial test was carried out on a sample from the sliding zone of the Huangtupo 1# landslide, a subdivision of the Huangtupo landslide in the Three Gorges area of China. The test results indicate that (a) the sliding zone exhibits low compressibility due to the high rock content (54.3%) and long-time consolidation by the overlying soil mass; (b) only decaying creep occurs without abrupt failure, and a constitutive equation with both linear and nonlinear viscoplastic terms is deduced to accurately fit the test data; (c) the surface with an orientation of 35° presents anisotropic traits in terms of displacement, possibly due to cracks that formed at similar orientations within the sample cube; and (d) the creep behavior of the landslide may be closely related to the properties of the sliding zone soil. When a similar stress magnitude to that of the in situ stress environment is applied to the sample, the sliding zone soil behavior matches the landslide deformative behavior. The test results indicate that the Huangtupo 1# landslide will continue to creep, as interpreted from the deformation traits and structural properties of the sample. However, unavoidable limitations of the test and extreme external factors, namely unexpected rainfall and water fluctuation, cannot be ignored.     

Phenological metrics-based crop classification using HJ-1 CCD images and Landsat 8 imagery

Crop type data are an important piece of information for many applications in agriculture. Extracting crop type using remote sensing is not easy because multiple crops are usually planted into small parcels with limited availability of satellite images due to weather conditions. In this research, we aim at producing crop maps for areas with abundant rainfall and small-sized parcels by making full use of Landsat 8 and HJ-1 charge-coupled device (CCD) data. We masked out non-vegetation areas by using Landsat 8 images and then extracted a crop map from a long-term time-series of HJ-1 CCD satellite images acquired at 30-m spatial resolution and two-day temporal resolution. To increase accuracy, four key phenological metrics of crops were extracted from time-series Normalized Difference Vegetation Index curves plotted from the HJ-1 CCD images. These phenological metrics were used to further identify each of the crop types with less, but easier to access, ancillary field survey data. We used crop area data from the Jingzhou statistical yearbook and 5.8-m spatial resolution ZY-3 satellite images to perform an accuracy assessment. The results show that our classification accuracy was 92% when compared with the highly accurate but limited ZY-3 images and matched up to 80% to the statistical crop areas.