基于3DEC特厚水平煤层开采地表裂缝分布规律研究

针对我国中西部某矿区的特厚水平煤层综放开采导致的沉降变形、地表裂缝等问题,本文在总结该矿区各工作面地质采矿条件的基础上,结合以往沉陷预计中岩层岩块物理力学参数的选取原则,以摩尔-库伦塑性模型作为计算模型,采用离散元3DEC数值模拟的方法,分析了煤层开采后的地表下沉和水平变形情况。同时,本文结合实地采集的裂缝和塌陷区数据,对开采后上覆岩层垮落情况及裂缝发育情况进行研究,总结出该煤矿水平特厚煤层开采后地表裂缝的分布规律和地表移动变形规律,对该煤矿的生产和开采具有指导意义。     

秦岭地区NDVI与地形因子的相关性分析

秦岭山区地形因子是影响植被分布的重要因素。选取2001、2009和2017年MODIS陆地产品MOD13Q1数据和DEM数据,从DEM中提取地形因子,高程、坡度和坡向,与MODIS的NDVI数据结合,分析了地形对秦岭地区植被空间分布影响。研究结果表明:(1)NDVI随着高程的增大而逐渐增大,在高程1800 m左右时达到最大值,随后又随着高程的增大而减小;(2)NDVI在坡度0°～5°间逐渐增大,在5°～40°呈稳定趋势,从40°开始缓慢减小,60°达到乔木能够生长的坡面倾角临界值,当坡面倾角大于60°时植被指数开始快速减小;(3)受太阳辐射的影响,坡向在NW 270°～360°,SE 240°～270°之间的植被长势较好,其余坡向上长势一般。     

GIS支持下的土地资源环境承载力评价——以荣成市为例

随着人类生产活动的日益加剧,土地资源环境已逐渐成为制约社会经济发展的主要因素。基于荣成市土地资源环境要素,利用层次分析法构建了区域土地资源环境承载力评价体系。对土地资源进行基础性评价,在GIS技术支持下计算各项指标分值,并得出承载状态压力指数;在基础性评价结果的基础上,对水资源、生态条件与环境质量进行修正性评价。结果显示,荣成市土地资源环境基础性评价为可载,基于水资源系统的综合承载状态为临界,基于生态条件与环境质量系统的综合承载状态为可载。     

差分层析SAR技术研究现状分析

差分层析SAR是在层析SAR基础上发展起来的一种四维信息反演技术。它不仅实现了对雷达目标的三维分辨能力,同时可以获取目标的形变速率信息,可实现对目标方位-距离-高度-时间四维成像,这对实现城市基础设施动态形变监测、古建筑风险评估、重要工程安全监测等应用具有重要实际意义和价值。本文基于差分层析SAR成像原理,分析了成像处理过程中存在的问题,总结了差分层析SAR成像算法研究现状和特点;最后列举了差分层析SAR技术的主要应用领域,并对其技术发展趋势进行了展望。     

Estimation of crowd density from UAVs images based on corner detection procedures and clustering analysis

With rapid developments in platforms and sensors technology in terms of digital cameras and video recordings, crowd monitoring has taken a considerable attentions in many disciplines such as psychology, sociology, engineering, and computer vision. This is due to the fact that, monitoring of the crowd is necessary to enhance safety and controllable movements to minimize the risk particularly in highly crowded incidents (e.g. sports). One of the platforms that have been extensively employed in crowd monitoring is unmanned aerial vehicles (UAVs), because UAVs have the capability to acquiring fast, low costs, high-resolution and real-time images over crowd areas. In addition, geo-referenced images can also be provided through integration of on-board positioning sensors (e.g. GPS/IMU) with vision sensors (digital cameras and laser scanner). In this paper, a new testing procedure based on feature from accelerated segment test (FAST) algorithms is introduced to detect the crowd features from UAV images taken from different camera orientations and positions. The proposed test started with converting a circle of 16 pixels surrounding the center pixel into a vector and sorting it in ascending/descending order. A single pixel which takes the ranking number 9 (for FAST-9) or 12 (for FAST-12) was then compared with the center pixel. Accuracy assessment in terms of completeness and correctness was used to assess the performance of the new testing procedure before and after filtering the crowd features. The results show that the proposed algorithms are able to extract crowd features from different UAV images. Overall, the values of Completeness range from 55 to 70 % whereas the range of correctness values was 91 to 94 %.     

An improved building detection approach using L-band POLSAR two-dimensional time-frequency decomposition over oriented built-up areas

The objective of this study is to efficiently extract detailed information about various man-made targets in oriented built-up areas using polarimetric synthetic aperture radar (POLSAR) images. This paper develops an improved approach for building detection by utilizing Two-Dimensional Time-Frequency (2-D TF) decomposition. This method performs outstandingly in distinguishing between man-made and natural targets based on the isotropic behaviors, frequency-sensitive responses, and scattering mechanisms of objects. The proposed method can preserve the spatial resolution and exploit the advantages of TF decomposition; specifically, the exact outlines of buildings can be effectively located, and more types of features (e.g., flat roofs, roads, and walls that are oblique to the radar illumination) can be distinguished from forests in complex built-up areas by 2-D TF decomposition. The coarser-resolution subaperture images that are produced in the azimuth direction, which correspond to different looking angles, are beneficial for detecting man-made structures with main scattering centers oriented at oblique angles with respect to the radar illumination. In the range direction, the obtained subaperture images, which correspond to various observation frequencies, can be helpful in distinguishing flat roofs and roads from forests. This method was successfully implemented to analyze both NASA/JPL L-band AIRSAR and L-band EMISAR data sets. The building detection results of the proposed method exhibit a significant improvement over those of other methods and reach an overall accuracy over 80%, with approximately 20% higher than the accuracies of K-means clustering and the entropy/alpha-Wishart classifier and approximately 10% higher than the accuracy of the support vector machine method. Moreover, building details can be precisely detected, obliquely oriented buildings can be identified, and the distinction between buildings and forests is significantly improved, as both visually and statistically indicated. This method is highly adaptable and has substantial application value.     

Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi District

In recent years, the rapid expansion of urban spaces has accelerated the mutual evolution of landscape types. Analyzing and simulating spatio-temporal dynamic features of urban landscape can help to reveal its driving mechanisms and facilitate reasonable planning of urban land resources. The purpose of this study was to design a hybrid cellular automata model to simulate dynamic change in urban landscapes. The model consists of four parts: a geospatial partition, a Markov chain (MC), a multi-layer perceptron artificial neural network (MLP-ANN), and cellular automata (CA). This study employed multivariate land use data for the period 2000–2015 to conduct spatial clustering for the Ganjingzi District and to simulate landscape status evolution via a divisional composite cellular automaton model. During the period of 2000–2015, construction land and forest land areas in Ganjingzi District increased by 19.43% and 15.19%, respectively, whereas farmland, garden lands, and other land areas decreased by 43.42%, 52.14%, and 75.97%, respectively. Land use conversion potentials in different sub-regions show different characteristics in space. The overall land-change prediction accuracy for the subarea-composite model is 3% higher than that of the non-partitioned model, and misses are reduced by 3.1%. Therefore, by integrating geospatial zoning and the MLP-ANN hybrid method, the land type conversion rules of different zonings can be obtained, allowing for more effective simulations of future urban land use change. The hybrid cellular automata model developed here will provide a reference for urban planning and policy formulation.     

灰关联GM(1,N)模型在建筑物沉降分析中的应用

针对建筑物沉降变形中各监测点相互关联、相互影响的情形,可将灰色系统理论中的GM(1,N)模型引入到建筑物沉降分析中。本文利用灰度关联方法确定相关因子的关联度,建立GM(1,N)模型,并与回归分析、GM(1,1)模型比较。通过工程实例,得出灰关联GM(1,N)模型预测精度明显高于另外两种模型,验证了该模型在进行建筑物沉降分析预测中应用的可行性。     

IU Cancri:a solar-type contact binary with mass transfer

We present new CCD photometry of the solar-type contact binary IU Cnc, which was observed from November 2017 to March 2018 with three small telescopes in China. BV light curves imply that IU Cnc is a W-type contact binary with total eclipses. The photometric solution indicates that the mass ratio and fill-out factor are q = 4.104 ± 0.004 and f = 30.2%± 0.3%, respectively. From all available light minimum times, the orbital period may increase at a rate of dP/dt =+6.93(4)× 10^-7 d yr^-1, which may result from mass transfer from the secondary component to the primary one. With mass transferring,IU Cnc may evolve from a contact configuration into a semi-detached configuration.     

New photometric investigation of the low-mass-ratio contact binary star V1853 Orionis

Four-color charge-coupled device(CCD) light curves in the B, V, Rc and I c bands of the totaleclipsing binary system V1853 Orionis(V1853 Ori) are presented. By comparing our light curves with those published by previous investigators, it is determined that the O'Connell effect on the light curves has disappeared. By analyzing those multi-color light curves with the Wilson-Devinney code(W-D code),it is discovered that V1853 Ori is an A-type intermediate-contact binary with a degree of contact factor of f = 33.3%(3.7%) and a mass ratio of q = 0.1896(0.0013). Combining our 10 newly determined times of light minima together with others published in the literature, the period changes of the system are investigated. We found that the general trend of the observed minus calculated(O-C) curve shows a downward parabolic variation that corresponds to a long-term decrease in the orbital period with a rate of d P/dt =-1.96(0.46)×10^-7 d yr^-1. The long-term period decrease could be explained by mass transfer from the more-massive component to the less-massive one. By combining our photometric solutions with data from Gaia DR_2, absolute parameters were derived as M_1 = 1.20 M⊙, M_2 = 0.23 M⊙, R_1 = 1.36 R⊙and R_2 = 0.66 R⊙. The long-term period decrease and intermediate-contact configuration suggest that V1853 Ori will evolve into a high fill-out overcontact binary.