A synthetic aperture radar sea surface distribution estimation by n-order Bézier curve and its application in ship detection

To dates,most ship detection approaches for single-pol synthetic aperture radar(SAR) imagery try to ensure a constant false-alarm rate(CFAR).A high performance ship detector relies on two key components:an accurate estimation to a sea surface distribution and a fine designed CFAR algorithm.First,a novel nonparametric sea surface distribution estimation method is developed based on n-order Bézier curve.To estimate the sea surface distribution using n-order Bézier curve,an explicit analytical solution is derived based on a least square optimization,and the optimal selection also is presented to two essential parameters,the order n of Bézier curve and the number m of sample points.Next,to validate the ship detection performance of the estimated sea surface distribution,the estimated sea surface distribution by n-order Bézier curve is combined with a cell averaging CFAR(CA-CFAR).To eliminate the possible interfering ship targets in background window,an improved automatic censoring method is applied.Comprehensive experiments prove that in terms of sea surface estimation performance,the proposed method is as good as a traditional nonparametric Parzen window kernel method,and in most cases,outperforms two widely used parametric methods,K and G0 models.In terms of computation speed,a major advantage of the proposed estimation method is the time consuming only depended on the number m of sample points while independent of imagery size,which makes it can achieve a significant speed improvement to the Parzen window kernel method,and in some cases,it is even faster than two parametric methods.In terms of ship detection performance,the experiments show that the ship detector which constructed by the proposed sea surface distribution model and the given CA-CFAR algorithm has wide adaptability to different SAR sensors,resolutions and sea surface homogeneities and obtains a leading performance on the test dataset.     

东山乌礁湾海滩表层沉积物粒度时空变化分析

为了进一步了解海岛岬湾海岸表层沉积物粒度的时空分布特征和形成机制,作者以福建东山岛乌礁湾为典型研究区,通过秋、春、夏3个不同季节海滩表层沉积物的采集和点位测量,综合应用激光法和筛析法进行粒度测定。结果表明,东山乌礁湾海滩表层沉积物以0.16～0.50 mm之间的中、细砂为主,并含有少量的粗砂和细砾,这与区域砂质沉积背景有关;湾内从南到北剖面沉积物粒径由粗砂到细砂逐渐变细,主要受剖面地形、局地物源、季节性风浪作用和近岸往复水动力的影响。时间变化上,各取样站位表现出沉积物粒径粗、细不同程度的多种变化趋势,以秋季为参考,整体上表现为由南到北粒级的变小、增大和稳定,这与东北、南南西季风影响下的浪、潮作用以及沿岸流系格局变化下的水动力环境有关。     

Why GPS makes distances bigger than they are

Global navigation satellite systems such as the Global Positioning System (GPS) is one of the most important sensors for movement analysis. GPS is widely used to record the trajectories of vehicles, animals and human beings. However, all GPS movement data are affected by both measurement and interpolation errors. In this article we show that measurement error causes a systematic bias in distances recorded with a GPS; the distance between two points recorded with a GPS is – on average – bigger than the true distance between these points. This systematic ‘overestimation of distance’ becomes relevant if the influence of interpolation error can be neglected, which in practice is the case for movement sampled at high frequencies. We provide a mathematical explanation of this phenomenon and illustrate that it functionally depends on the autocorrelation of GPS measurement error (C). We argue that C can be interpreted as a quality measure for movement data recorded with a GPS. If there is a strong autocorrelation between any two consecutive position estimates, they have very similar error. This error cancels out when average speed, distance or direction is calculated along the trajectory. Based on our theoretical findings we introduce a novel approach to determine C in real-world GPS movement data sampled at high frequencies. We apply our approach to pedestrian trajectories and car trajectories. We found that the measurement error in the data was strongly spatially and temporally autocorrelated and give a quality estimate of the data. Most importantly, our findings are not limited to GPS alone. The systematic bias and its implications are bound to occur in any movement data collected with absolute positioning if interpolation error can be neglected.     

Investigation of gas content of organic-rich shale:A case study from Lower Permian shale in southern North China Basin,central China

Measuring gas content is an essential step in estimating the commerciality of gas reserves. In this study,eight shale core samples from the Mouye-1 well were measured using a homemade patented gas desorption apparatus to determine their gas contents. Due to the air contamination that is introduced into the desorption canister, a mathematical method was devised to correct the gas quantity and quality.Compared to the chemical compositions of desorbed gas, the chemical compositions of residual gas are somewhat different. In residual gas, carbon dioxide and nitrogen record a slight increase, and propane is first observed. This phenomenon may be related to the exposure time during the transportation of shale samples from the drilling site to the laboratory, as well as the differences in the mass, size and adsorptivity of different gas molecules. In addition to a series of conventional methods, including the USBM direct method and the Amoco Curve Fit(ACF) method, which were used here for lost gas content estimation, a Modified Curve Fit(MCF) method, based on the 'bidisperse' diffusion model, was established to estimate lost gas content. By fitting the ACF and MCF models to gas desorption data, we determined that the MCF method could reasonably describe the gas desorption data over the entire time period, whereas the ACF method failed. The failure of the ACF method to describe the gas desorption process may be related to its restrictive assumption of a single pore size within shale samples. In comparison to the indirect method, this study demonstrates that none of the three methods studied in this investigation(USBM, ACF and MCF) could individually estimate the lost gas contents of all shale samples and that the proportion of free gas relative to total gas has a significant effect on the estimation accuracy of the selected method. When the ratio of free gas to total gas is lower than 45%, the USBM method is the best for estimating the lost gas content, whereas when the ratio ranges from 45% to 75% or is more than 75%, the ACF and MCF methods, are the best options respectively.     

RS & GIS-based landslide susceptibility mapping of the Balason River basin,Darjeeling Himalaya,using logistic regression (LR) model

The present study deals with the preparation of a landslide susceptibility map of the Balason River basin, Darjeeling Himalaya, using a logistic regression model based on Geographic Information System and Remote Sensing. The landslide inventory map was prepared with a total of 295 landslide locations extracted from various satellite images and intensive field survey. Topographical maps, satellite images, geological, geomorphological, soil, rainfall and seismic data were collected, processed and constructed into a spatial database in a GIS environment. The chosen landslide-conditioning factors were altitude, slope aspect, slope angle, slope curvature, geology, geomorphology, soil, land use/land cover, normalised differential vegetation index, drainage density, lineament number density, distance from lineament, distance to drainage, stream power index, topographic wetted index, rainfall and peak ground acceleration. The produced landslide susceptibility map satisfied the decision rules and ?2 Log likelihood, Cox &; Snell R-Square and Nagelkerke R-Square values proved that all the independent variables were statistically significant. The receiver operating characteristic curve showed that the prediction accuracy of the landslide probability map was 96.10%. The proposed LR method can be used in other hazard/disaster studies and decision-making.     

南图尔盖盆地Aryskum坳陷钾盐的测井响应特征及其分布

钾盐作为战略资源,在农业、工业等领域具有重要的使用价值。世界大多数固态钾资源发现于大规模的石油勘探过程中,充分利用各种油气地质、地球物理资料开展钾盐勘探对于国家发展尤为重要。位于哈萨克斯坦的南图尔盖盆地地质构造简单、资源勘探潜力较大。文中以南图尔盖盆地Aryskum坳陷为研究区块,基于其沉积地质特点,结合多口井的常规测井资料及前人研究成果,综合分析自然伽马、自然电位、三孔隙度等测井曲线的响应特征,含钾层段具体表现为自然伽马异常高值,并通过无铀伽马曲线等排除铀、钍元素影响,扩径使得中子值偏高,自然电位异常幅度由砂岩层的负异常变化为正异常,电阻率值偏高,密度值介于2.25~2.45 g/cm³,声波时差在270~350 μs/m范围内。基于含钾层测井曲线特点,利用测井曲线综合识别法、重叠法、交会图法进行研究区钾盐识别。在研究区30余口井中发现有可溶性钾盐层分布,分布在M-Ⅱ-3、M-Ⅱ-2小层底部,其中M-Ⅱ-3层底部为主要钾盐层段,并对各井含钾层段累计厚度进行统计分析。最后,借助地层对比分析含钾层段在横向和纵向上的展布情况,通过等厚图的绘制开展了找钾有利区分析,拓展了测井资料在南图尔盖盆地钾盐勘查中的应用,进而为今后研究区钾盐找矿提供重点方向。     

基于省区协调发展的GDP预测模型

基于柯布-道格拉斯生产函数与自回归移动平均模型(ARIMA)构建出一个GDP综合预测模型,并且考虑十九大全面建成小康社会与实现共同富裕的精神与国家关于技术、资本、劳动力等方面的区域平衡发展战略调整模型的参数,计算了2016—2050年中国分省的GDP总量与人均GDP,进一步通过计算省区间人均GDP的基尼系数来分析省区协调发展的水平。研究结果表明,在考虑省区协调发展时,各省区在2016—2050年间的GDP总量与人均GDP的差距逐渐缩小,省区间人均GDP的基尼系数将从2015年的0.219下降到2030年的0.176和2050年的0.137,未来区域间发展不均衡的态势在实现经济稳步增长同时可以得到缓解。     

温室气体排放的环境库兹涅茨曲线检验与减排路径的冲击动态——基于黑龙江省统计核算数据

基于2001-2015年黑龙江省温室气体排放统计核算数据,对地区GDP与温室气体排放的环境库兹涅茨曲线关系检验呈现倒U型,预期2019年达到理论拐点;通过偏最小二乘回归模型得到4个减排路径的年平均减排效果顺序依次为单位GDP化石能源消费量减少、经济结构调整、人均GDP增长、贸易结构变化;减排路径对应脉冲响应函数的动态冲击效果分别为波动性增排、收敛性减排、发散性减排、转变的排放作用;推动黑龙江省温室气体减排的路径顺序为控制化石能源消费量、优化经济结构、发展低碳经济、调整贸易结构。     

基于Hv方法的三轴液压振动系统频响函数估计的研究

三轴液压振动系统是实验室内模拟振动环境的主要设备,其主要功能是精确地复现给定的功率谱和时间历程。振动控制技术是实现这一目标的关键技术,它以频响函数估计为基础。频响函数估计的精度影响控制过程的快速性和稳定性。本文对几种典型的频响函数估计方法进行了分析,针对传统方法精度低且受到矩阵病态条件约束等缺点,应用特征分析与摄动理论构造了一种多入多出的Hv方法,并且应用三轴液压振动系统的实测数据对其进行了检验。结果表明该方法是适用的。