尼日尔三角洲东部深水区构造特征及其形成机理     

赵江  王秋良  卢圣力  付博  杜峰 《大地测量与地球动力学》2019,39(7):691-695

研究尼日尔三角洲东部深水区块发现，整个盆地从陆向洋具有3个大的构造分区：伸展拉张区、过渡区和挤压逆冲区。伸展区以大型同沉积断层伴生大量滚动背斜构造为特征，过渡区发育大量泥底辟构造，挤压区以复杂的逆冲叠瓦构造为主。通过分析形成机理，揭示东部深水转换带上M研究区构造特征，按构造的演化特征将该区构造分为泥底辟型、冲断-泥底辟混合型、逆冲型3种类型，提出研究区内的圈闭主要以构造-岩性圈闭为主，为尼日尔三角洲盆地深水勘探提供新的理论指导。  相似文献   

Evaluation of aquatic ecological systems through dynamics of ichthyofaunal diversity in a Himalayan torrential river,Murti     

《Limnologica》2020

The biodiversity hotspot region of the Eastern Himalayas consists of a vast freshwater network enriched with species diversity. Many small-scale torrential rivers and water reaches contribute to the species pool of all the major rivers by converging downstream. These reaches are most likely to be degraded at a faster rate as compared to the large-scale rivers following an increased rate of urbanization, habitat alterations, and changing climatic conditions. Therefore, this study aims to explore River Murti, which is a representative small scale river system characterized by a large altitudinal gradient and a diverse watershed area. Ichthyofaunal diversity (i.e., diversity, evenness & richness) and 21 environmental variables are measured through a tri-seasonal sampling effort conducted along 14 selected locations. A total of 41 fish species (including species belonging to 4 Near Threatened, 8 Vulnerable, and 1 Endangered) are found inhabiting this river. Ichthyofaunal assemblage is found to be primarily modulated by habitat diversity and landscape variables. Three Aquatic Ecological Systems (AES) have been identified along this river in a top-down approach based on recorded environmental variables. We have calculated an observed/expected ratio for each diversity indices along 14 locations based on predicted temporal variability using boosted regression (BRT) models. The evaluation of diversity status has been kept at 0.5 to account for a 50% loss or deviation from observed (O/E50). This evaluation has been successfully used to delineate AES1 with majorly “Impaired” status and thus ensures its importance in terms of species conservation. Our study indicates the contribution of 11 major environmental drivers modulating the species assemblage patterns in these AES. Amongst them, altitude, substrate coarseness, river morphology, and shelter availability are strongly associated with species diversity as per the BRT models. These underlying factors are also correlated with “basin pressure,” suggesting that anthropogenic disturbances, as well as the changing climate, might play an important role in the gradual change in environmental conditions, which in turn could cause a shift in species assemblage structure.  相似文献   

Dynamic loading tests and seismic response analysis of a stud-type damper composed of multiple friction units with disc springs     

Takeshi Sano  Kazutaka Shirai  Yasumasa Suzui  Yoshikazu Utsumi 《地震工程与结构动力学》2020,49(13):1259-1280

This paper presents an experimental study on the performance of a shear-sliding stud-type damper composed of multiple friction units with high-tension bolts and disc springs. A numerical evaluation of the response reduction effects achieved by the stud-type damper is also presented. In dynamic loading tests, the behavior of stud-type multiunit friction damper specimens was investigated. Three different full-scale damper specimens, which were composed of five, six, or seven friction units with two or four sliding surfaces, were incorporated into loading devices for testing. The stud-type friction dampers demonstrated stable rigid-plastic hysteresis loops without any remarkable decrease in the sliding force even when subjected to repetitive loading, in addition to showing no unstable behavior such as lateral buckling. The damper produced a total sliding force approximately proportional to the number of sliding surfaces and friction units. The total sliding force of the stud-type damper can thus be estimated by summing the contributions of each friction unit. In an earthquake response simulation, the control effects achieved by stud-type dampers incorporated into an analytical high-rise building model under various input waves, including long-period, long-duration and pulse-like ground motions, were evaluated. A satisfactory response reduction was obtained by installing the developed stud-type dampers into the main frame without negatively impacting usability and convenience in terms of building planning.  相似文献   

Lidar-aided analysis of boreal forest backscatter at Ku band     

《International Journal of Applied Earth Observation and Geoinformation》2020

This paper analyzes the backscatter of the microwave signal in a boreal forest environment based on a Ku -band airborne Frequency-Modulated Continuous Waveform (FMCW) profiling radar—Tomoradar. We selected a half-managed boreal forest in the southern part of Finland for a field test. By decomposing the waveform collected by the Tomoradar, the vertical canopy structure was achieved. Based on the amplitude of the waveform, the Backscattered Energy Ratio of Canopy-to-Total (BERCT) was calculated. Meanwhile, the canopy fraction was derived from the corresponding point cloud recorded by a Velodyne VLP-16 LiDAR mounted on the same platform. Lidar-derived canopy fraction was obtained by counting the number of the first/ the strongest returns versus the total amount of returns. Qualitative and quantitative analysis of radar-derived BERCT on lidar-derived canopy fraction and canopy height are investigated. A fitted model is derived to describe the Ku-band microwave backscatter in the boreal forest to numerically analyze the proportion contributed by four factors: lidar-derived canopy fraction, radar-derived canopy height, the radar-derived distance between trees and radar sensor and other factors, from co-polarization Tomoradar measurements. The Root Mean Squared Error (RMSE) of the proposed model was 0.0958, and the coefficient of determination R2 was 0.912. The fitted model reveals that the correlation coefficient between radar-derived BERCT and lidar-derived canopy fraction is 0.84, which illustrates that lidar surface reflection explains the majority of the profiling /waveform radar response. Thus, vertical canopy structure derived from lidar can be used for the benefit of radar analysis.  相似文献   

In-season crop classification using elements of the Kennaugh matrix derived from polarimetric RADARSAT-2 SAR data     

《International Journal of Applied Earth Observation and Geoinformation》2020

Accurate spatio-temporal classification of crops is of prime importance for in-season crop monitoring. Synthetic Aperture Radar (SAR) data provides diverse physical information about crop morphology. In the present work, we propose a day-wise and a time-series approach for crop classification using full-polarimetric SAR data. In this context, the 4 × 4 real Kennaugh matrix representation of a full-polarimetric SAR data is utilized, which can provide valuable information about various morphological and dielectric attributes of a scatterer. The elements of the Kennaugh matrix are used as the parameters for the classification of crop types using the random forest and the extreme gradient boosting classifiers.The time-series approach uses data patterns throughout the whole growth period, while the day-wise approach analyzes the PolSAR data from each acquisition into a single data stack for training and validation. The main advantage of this approach is the possibility of generating an intermediate crop map, whenever a SAR acquisition is available for any particular day. Besides, the day-wise approach has the least climatic influence as compared to the time series approach. However, as time-series data retains the crop growth signature in the entire growth cycle, the classification accuracy is usually higher than the day-wise data.Within the Joint Experiment for Crop Assessment and Monitoring (JECAM) initiative, in situ measurements collected over the Canadian and Indian test sites and C-band full-polarimetric RADARSAT-2 data are used for the training and validation of the classifiers. Besides, the sensitivity of the Kennaugh matrix elements to crop morphology is apparent in this study. The overall classification accuracies of 87.75% and 80.41% are achieved for the time-series data over the Indian and Canadian test sites, respectively. However, for the day-wise data, a ∼6% decrease in the overall accuracy is observed for both the classifiers.  相似文献   

基于深度残差网络的机载LiDAR点云分类     

赵传  郭海涛  卢俊  余东行  张保明 《测绘学报》2020,49(2):202-213

机载LiDAR点云的分类是利用其进行城市场景三维重建的关键步骤之一。为充分利用现有的图像领域性能较好的深度学习网络模型,提高点云分类精度,并降低训练时间和对训练样本数量的要求,本文提出一种基于深度残差网络的机载LiDAR点云分类方法。首先提取归一化高程、表面变化率、强度和归一化植被指数4种具有较高区分度的点云低层次特征;然后通过设置不同的邻域大小和视角,利用所提出的点云特征图生成策略,得到多尺度和多视角点云特征图;再将点云特征图输入到预训练的深度残差网络,提取多尺度和多视角深层次特征;最后构建并训练神经网络分类器,利用训练的模型对待分类点云进行预测,经后处理得到分类结果。利用ISPRS三维语义标记竞赛的公开标准数据集进行试验,结果表明,本文方法可有效区分建筑物、地面、车辆等8类地物,分类结果的总体精度为87.1%,可为城市场景三维重建提供可靠的信息。  相似文献   

曲靖非相干散射雷达电离层F区日间电子温度变化特征初步分析   总被引：1，自引：0，他引：1       下载免费PDF全文

丁宗华  代连东  杨嵩  唐志美  吴健  许正文 《地球物理学报》2020,63(4):1282-1293

利用曲靖非相干散射雷达2017-2018年春夏季观测数据首次分析了电离层日间150~450km电子温度的地方时与高度变化特征及其与电子密度的相关性.发现hmF2及以上的电子温度在日出日落时具有两个峰值,在11∶00-16∶00LT之间变化较小,高度越高午后上升的时间越早;从150km开始迅速增加,在约220km达到最大值,然后开始降低,在约300~350km达到最小值,最后单调上升;200km以下电子温度与电子密度成正相关(主要由热传导控制),200~450km之间存在明显的反相关(光电离过程占主导),电子-离子温度差与电子密度对数之间存在近似线性关系,电子温度逐日变化与光电离因子的变化趋势相似,这种相关性在中午与午后更明显;以上结果与其他非相干散射雷达观测和电离层模型计算结果基本一致,但也存在一些差别,需要结合更多数据深入分析.  相似文献   

利用模板匹配技术检测米尺度岩石断层黏滑实验中的声发射事件   总被引：1，自引：0，他引：1       下载免费PDF全文

侯金欣  谢凡  任雅琼  王宝善 《地球物理学报》2020,63(4):1630-1641

声发射观测是岩石摩擦实验中研究强震孕育机制的重要观测手段之一.传统的声发射观测以触发记录为主,难以捕捉并提取微弱的声发射信号.近年来天然地震学中发展的模板匹配技术可以在连续波形记录中识别出微弱的事件,大大提升事件检测能力.本文发展了适用于多通道连续记录的声发射信号的模板匹配技术,并将该技术应用于分析米尺度岩石断层黏滑失稳过程.研究结果显示:模板匹配技术识别出的声发射数量约为传统方法识别的5倍,相对完备震级降低约0.3.临近失稳,检测目录完备震级以上声发射率表现出幂律增加的特征,且声发射事件聚集在失稳破裂起始点附近.失稳后,检测目录完备震级以上声发射率表现出幂律衰减,其中失稳后早期表现出较慢的衰减速度.另外,失稳后早期声发射事件表现出随对数时间沿断层迁移的趋势.最后,通过与天然地震学观测的结果对比表明,声发射模板匹配识别技术是研究大尺度岩石摩擦滑动失稳过程中前震和余震时空演化规律的有效手段,该技术助于在方法上为室内实验和野外观测进行融合研究提供思路.  相似文献   

Tree species identification within an extensive forest area with diverse management regimes using airborne hyperspectral data     

《International Journal of Applied Earth Observation and Geoinformation》2020

Information on tree species composition is crucial in forest management and can be obtained using remote sensing. While the topic has been addressed frequently over the last years, the remote sensing-based identification of tree species across wide and complex forest areas is still sparse in the literature. Our study presents a tree species classification of a large fraction of the Białowieża Forest in Poland covering 62 000 ha and being subject to diverse management regimes. Key objectives were to obtain an accurate tree species map and to examine if the prevalent management strategy influences the classification results. Tree species classification was conducted based on airborne hyperspectral HySpex data. We applied an iterative Support Vector Machine classification and obtained a thematic map of 7 individual tree species (birch, oak, hornbeam, lime, alder, pine, spruce) and an additional class containing other broadleaves. Generally, the more heterogeneous the area was, the more errors we observed in the classification results. Managed forests were classified more accurately than reserves. Our findings indicate that mapping dominant tree species with airborne hyperspectral data can be accomplished also over large areas and that forest management and its effects on forest structure has an influence on classification accuracies and should be actively considered when progressing towards operational mapping of tree species composition.  相似文献   

An evaluation of Guided Regularized Random Forest for classification and regression tasks in remote sensing     

《International Journal of Applied Earth Observation and Geoinformation》2020

New Earth observation missions and technologies are delivering large amounts of data. Processing this data requires developing and evaluating novel dimensionality reduction approaches to identify the most informative features for classification and regression tasks. Here we present an exhaustive evaluation of Guided Regularized Random Forest (GRRF), a feature selection method based on Random Forest. GRRF does not require fixing a priori the number of features to be selected or setting a threshold of the feature importance. Moreover, the use of regularization ensures that features selected by GRRF are non-redundant and representative. Our experiments based on various kinds of remote sensing images, show that GRRF selected features provides similar results to those obtained when using all the available features. However, the comparison between GRRF and standard random forest features shows substantial differences: in classification, the mean overall accuracy increases by almost 6% and, in regression, the decrease in RMSE almost reaches 2%. These results demonstrate the potential of GRRF for remote sensing image classification and regression. Especially in the context of increasingly large geodatabases that challenge the application of traditional methods.  相似文献