用超导重力仪的潮汐观测资料研究海潮模型

系统研究了潮汐观测资料中海潮模型的适应性问题,用基于数值离散褶积积分方法获得的海潮负荷对武昌超导重务仪观测资料作负荷改正。结果说明,海潮负荷改正后的重力场观测残差大大降低了,与理论潮汐参数模型相比,８个主要潮流的平均振幅因子由改正前的１．３８％降至０．１３％和０．２６％。     

GPS动态测量连续周跳检验

本文针对ＧＰＳ动态测量中经常出现的连续周跳,提出了一种新的连续周跳的检验方法。该方法在理论上是最优的,与Ｋａｌｍａｎ滤波平行操作,能够实行处理周跳引起的偏差;而且,在偏差估计的同时,兼顾后续偏差检验,因而可利用尽可能多的观测历元信息来获取精度较高的偏差估值。实例计算表明,该方法在应用中是很有效的。     

A wavelet method for detecting S‐waves in seismic data

Seismic signals consist of several typically short energy bursts, called phases, exhibiting several patterns in terms of dominant frequency, amplitude and polarisation. We present a fast algorithm to detect the so‐called S‐phase in a three‐component seismic signal. This new approach combines traditional S‐phase detection methods and the discrete wavelet transform. This revised version was published online in July 2006 with corrections to the Cover Date.     

中国的空间环境研究与空间环境预报

本文主要介绍我国在空间环境研究与空间环境预报方面的进展, 包括空间环境资料和模式的收集、研究与应用; 空间环境与航天器的相互作用及其对航天器的影响; 以及空间环境预报方法和预报技术等的进展     

A 15-year-Long catalog of seismicity in the Eastern Tennessee Seismic Zone (ETSZ) using matched filter detection

We present a detailed catalog of 13 671 earthquakes in the Eastern Tennessee Seismic Zone (ETSZ) that spans January 1, 2005 to July 31, 2020. We apply a matched filter detection technique on over 15 years of continuous data, resulting in arguably the most complete catalog of seismicity in the ETSZ yet. The magnitudes of newly detected events are determined by computing the amplitude ratio between the detections and templates using a principal component fit. We also compute the b-value for the new catalog and comparatively relocate a subset of newly detected events using XCORLOC and hypoDD, which shows a more defined structure at depth. We find the greatest concentration along and to the east of the New York-Alabama Lineament, as defined by the magnetic anomaly, supporting the argument that this feature likely is related to the generation of seismicity in the ETSZ. We examine seismicity in the vicinity of the Watts Bar Reservoir, which is located about 5 ?km from the epicenter of the M_W 4.4 December 12, 2018 Decatur, Tennessee earthquake, and find possible evidence for reservoir modulated seismicity in this region. We also examine seismicity in the entire ETSZ to search for a correlation between shallow earthquakes and seasonal hydrologic changes. Our results show limited evidence for hydrologically-driven shallow seismicity due to seasonal groundwater levels in the ETSZ, which contradicts previous studies hypothesizing that most intraplate earthquakes are associated with the dynamics of hydrologic cycles.     

基于同步挤压小波变换的烃类识别技术

利用频谱分解得到的频率能量数据体进行属性提取,是烃类检测的常用手段之一.同步挤压小波变换能够提供高分辨率的时频谱,具有较好的应用潜力.本文以同步挤压小波变换为基础,提出了一套烃类检测方法,包括低频阴影检测、流体流动性估计以及高频能量衰减等,通过自适应选取优势频段,实现了多属性联合高精度刻画烃类的分布范围.实际资料处理结果与现有钻井情况吻合,具有较好的实用性,实现了对储层位置的高精度描述,对指导油气田开发具有重要的理论意义和实用价值.     

2016年1月9日河北怀来ML3.4震群发震构造分析

本文采用模板识别匹配滤波方法检测2016年1月9日河北怀来M_L3.4震群序列目录中遗漏的地震事件,并加入波形互相关信息对震相到时进行校正,采用盖革法进行精确定位。重新定位后震群震中呈NEE向分布,与怀涿次级盆地北缘断裂走向一致,并主要集中在该断裂的小水峪-黄土窑段。震群中最大地震M_L3.4的P波初动解的一个节面走向与精定位后震中展布和断裂的走向基本一致,可推测怀涿次级盆地北缘断裂可能为怀来M_L3.4震群的发震构造。震中集中分布的怀涿次级盆地北缘断裂的小水峪-黄土窑段属5个分段中滑动速率最大的段落,分析认为该震群可能是由断层慢滑动引起的。     

Region of interest extraction via common salient feature analysis and feedback reinforcement strategy for remote sensing images

Saliency detection is an effective approach to extract regions of interest (ROIs) for remote sensing images. However, existing saliency detection models mainly focus on ROI extraction from a single image and usually are not able to produce satisfactory results because of complex background interference in remote sensing images. The employment of mutual information in a set of remote sensing images can provide an effective solution to this issue. In this paper, we propose a novel saliency detection model for multiple remote sensing images to simultaneously extract ROIs and identify images without ROIs. First, common salient feature analysis based on synthesized feature clustering and global contrast is implemented to exploit global correspondence in the synthesis feature domain, thereby highlighting preliminary ROIs against background interference and assigning lower saliency values to images without ROIs. Then, we design an exclusion criterion based on saliency value judgment to remove images without ROIs, and the remaining saliency maps are refined by an enhancement strategy. Finally, the enhanced maps serve as a feedback to yield a homogenous synthesized feature space in which integral ROIs with subtle borders are extracted by the reused cluster-based saliency calculation. Experiments reveal that our model outperforms seven state-of-the-art models by achieving the best ROC curve (AUC = 0.945) and maximal F-measure at 0.729.     

Geomorphic process from topographic form: automating the interpretation of repeat survey data in river valleys

The ability to quantify the processes driving geomorphic change in river valley margins is vital to geomorphologists seeking to understand the relative role of transport mechanisms (e.g. fluvial, aeolian, and hillslope processes) in landscape dynamics. High‐resolution, repeat topographic data are becoming readily available to geomorphologists. By contrasting digital elevation models derived from repeat surveys, the transport processes driving topographic changes can be inferred, a method termed ‘mechanistic segregation.’ Unfortunately, mechanistic segregation largely relies on subjective and time consuming manual classification, which has implications both for its reproducibility and the practical scale of its application. Here we present a novel computational workflow for the mechanistic segregation of geomorphic transport processes in geospatial datasets. We apply the workflow to seven sites along the Colorado River in the Grand Canyon, where geomorphic transport is driven by a diverse suite of mechanisms. The workflow performs well when compared to field observations, with an overall predictive accuracy of 84% across 113 validation points. The approach most accurately predicts changes due to fluvial processes (100% accuracy) and aeolian processes (96%), with reduced accuracy in predictions of alluvial and colluvial processes (64% and 73%, respectively). Our workflow is designed to be applicable to a diversity of river systems and will likely provide a rapid and objective understanding of the processes driving geomorphic change at the reach and network scales. We anticipate that such an understanding will allow insight into the response of geomorphic transport processes to external forcings, such as shifts in climate, land use, or river regulation, with implications for process‐based river management and restoration. Copyright © 2017 John Wiley & Sons, Ltd.