基于小基线集技术的鹤岗煤矿区地表形变监测

针对煤炭资源的长期无节制开采,造成矿区地表沉降、塌陷、环境污染等诸多问题,本文基于小基线集(SBAS-InSAR)技术,使用Sentinel-1雷达数据,对鹤岗矿区进行形变监测,分析2017年3月26日至2021年12月18日期间地表形变和时空演化特征。结果表明,鹤岗矿区地表形变严重,形变量在监测期内逐渐增大,最大累计形变量达到-585 mm。空间分布上,相较于2013—2016年,振兴矿、新岭矿地表形变有减缓趋势,峻德矿有向南扩展趋势。     

甘肃金川矿区地表三维形变InSAR监测

金川矿区是我国最大的镍矿生产基地,2018年提出复采计划以来,对该矿区地表形变的监测还是空白.该文基于3个轨道(升轨128、降轨33和135)的Sentinel-1A数据,利用小基线集雷达干涉(small baseline subset In-SAR,SBAS-InSAR)和结合先验条件的最小二乘迭代法获得金川矿区20...     

基于SBAS时序分析方法的断裂带形变监测

以海原断裂带为研究区,开展了基于2015年3月~2016年7月的20景哨兵一号(Sentinel-1)数据和SBAS-InSAR技术的时序断裂带形变监测。结果表明,研究区形变累积量集中在-10~+5mm,海原县第一中学附近存在明显沉降漏斗,其沉降累积量达28mm;海原断裂带南北两盘相对形变速率约为6mm/a,运动性质为左旋走滑,与GPS和地质学研究结果基本一致。     

基于SBAS-InSAR技术的广州市白云区长时序地表形变监测与成因分析

随着我国城市化进程的推进,城市区域人类活动越来越密集,如地下水开采和地下工程等,导致地表发生沉降,影响人们的生活。为了确保城市健康稳定发展,开展城区大范围地面沉降监测具有重要意义。本文利用SBAS-InSAR技术对广州市白云区2016年2月—2022年3月获取的176景Sentinel-1 SAR影像进行处理,得到了该区域的平均形变速率和时序形变。同时,结合历史光学影像和现场调查对研究区域内的形变原因进行了分析。结果表明,形变主要与当地的地质条件、垃圾生化降解和人类活动(如建构筑物施工等)有关,最大形变速率超过40 mm/a,最大累计形变量超过350 mm。本文研究可为城市区域的地面沉降监测和成因分析提供参考。     

CRInSAR与PSInSAR联合监测矿区时序地表形变研究

正永久散射体差分干涉测量(PSInSAR)与人工角反射器差分干涉测量(CRInSAR)技术均为基于高相干目标点的时间序列形变监测手段,不受时间空间失相干严重影响,同时通过对相邻两目标点之间的相位作差,可极大地减弱模型中大气延迟相位的影响,因此本文旨在将这两种技术结合起来,应用于矿区沉降的监测中,以提高矿区地表形变监测的精度和可靠性。本文分别针对两种技术的理论、处理流程、算法及可靠性评价等方面进行了讨论与阐述,提出一套PSInSAR     

基于SBAS-InSAR技术监测西安市地表形变特征

地面沉降是西安市最为严重的地质灾害之一。本文基于SBAS-InSAR技术处理了西安市2018—2021年36景Sentinel-1A影像,获取了西安市最新的地表形变特征,并分析其成因。研究表明：(1)2018—2021年西安市主要地表形变区域为鱼化寨地区、电子城地区、三爻-凤栖原地区、城墙南部区域;(2)鱼化寨及电子城地区已转为抬升趋势,城墙南部一直处于抬升阶段,三爻-凤栖原地区呈下沉趋势;(3)西安市地表形变主要受承压水开采及回灌的影响,地裂缝则显著影响了地表形变的分布及走向,建筑载荷也对地表形变有一定的影响。     

基于Sentinel-1A数据的地表形变监测

提取滑坡形变数据、分析形变趋势对地质灾害防治工作具有指导意义.合成孔径雷达干涉测量技术(InSAR)具有全天候、全天时精确获取地表形变数据的能力,是当前形变监测的重要手段.分别利用DInSAR和SBAS-InSAR技术处理了22景哨兵一号(Sentinel-1)C波段数据,得到了四川省安州区高川乡大光包滑坡2018年3月-2020年2月的形变数据特征.结果表明,大光包滑坡点共有3个相对明显的形变区域;近两年的平均形变速率最高不超过100 mm/a,其形变时间序列随降雨量变化具有周期性;总体地表形变趋于稳定,周边地区中小型地震的发生没有造成地质灾害隐患.     

利用Sentinel-1A数据监测地表形变案例分析

雷达卫星结合InSAR技术已广泛应用于高精度地表形变监测领域。本文选取2017年九寨沟地震为研究案例,利用Sentinel-1A地震前后的单视复数影像,基于D-InSAR技术获取该次地震的同震形变场。结果显示:震中西北侧表现出相对均匀的下沉现象,沉降漏斗区雷达视线向最大沉降量达25.1 cm;东南侧呈现不均匀抬升状态,地表破碎较为明显,最大抬升量为11.6 cm。研究表明基于Sentinel-1A数据的D-InSAR技术可以为地震形变场的定量分析提供一种快速有效的手段,为阐释地震发震机理及评估受灾情况提供必要的数据支撑,具有广阔的应用前景。     

D-InSAR技术在矿区形变监测中的应用研究

D-InSAR技术作为20世纪90年代发展起来的新型空间对地观测技术,凭借着全天候、全天时、高分辨率和连续空间覆盖的特点得到了广泛的应用.本文介绍了D-InSAR技术的基本原理和处理流程,以内蒙古营盘壕煤矿为例,利用哨兵数据,通过二轨差分干涉测量方法得到沉降数据.在ArcGIS中通过对沉降区域的提取、剖面分析和叠加分析...     

基于SBAS-InSAR技术的煤炭坝矿区地表沉降监测与分析

为满足能源的需求,煤炭坝矿区对煤矿进行了大规模的开采,给当地环境带来了巨大的危害.传统监测方法已无法满足监测要求,InSAR技术凭借其大范围、无接触、监测精度高的优点在矿区沉降监测中广泛应用.本文基于SBAS-InSAR对11景ALOS1数据进行处理,获取了煤炭坝矿区2008年7月至2011年1月期间的时序形变结果和平...     

Data field for mining big data

Abstract

Big data is a highlighted challenge for many fields with the rapid expansion of large-volume, complex, and fast-growing sources of data. Mining from big data is required for exploring the essence of data and providing meaningful information. To this end, we have previously introduced the theory of physical field to explore relations between objects in data space and proposed a framework of data field to discover the underlying distribution of big data. This paper concerns an overview of big data mining by the use of data field. It mainly discusses the theory of data field and different aspects of applications including feature selection for high-dimensional data, clustering, and the recognition of facial expression in human–computer interaction. In these applications, data field is employed to capture the intrinsic distribution of data objects for selecting meaningful features, fast clustering, and describing variation of facial expression. It is expected that our contributions would help overcome the problems in accordance with big data.     

矿区地表移动变形监测数据处理

本文采用AutoCAD VBA二次开发技术,实现了地表移动观测数据处理、成图自动一体化.克服了传统方法成图只能查看、不易定量分析的缺点;在输出下沉、倾斜、曲率、水平移动、水平变形计算结果的同时,将各移动变形曲线和对应的地下煤层开采情况按一定比例尺在CAD中成图.可实现从图中曲线上直接量取任意点的对应值;较方便地从图中求取地表移动盆地各角量、距离参数;有利于直观分析开采沉陷对地表的影响.     

Monitoring ground deformation in Beijing, China with persistent scatterer SAR interferometry

This paper investigated the long term ground deformation in Beijing, China, using persistent/permanent scatterer interferometry (PSI) techniques. GEOS-PSI (Geodesy and Earth Observing Systems-PSI), an in-house software developed at UNSW for PSI, has been applied to 41 ENVISAT ASAR images acquired over the metropolitan area of Beijing City between June 2003 and March 2009 and 24 ALOS PALSAR images (two Paths: 10 acquisitions from January 2007 to October 2008 and 14 acquisitions from February 2007 to September 2009). The results generated using these datasets from the two satellites were cross-validated. Correlations between the results of ENVISAT ASAR and ALOS PALSAR agreed very well. The horizontal and vertical displacement rate maps over Beijing City were obtained from the results generated with data acquired by both satellites over the period from 1st February 2007 to 1st November 2008. The results indicate that the displacements in Beijing City were mainly in the vertical direction. The majority of the easting displacement rates were in the range of ?10 mm/year to 10?mm/year, while the vertical rates were in the range of ?115 mm/year to 6?mm/year. The possible cause for the ground deformation is groundwater extraction based on our research as well as earlier published studies.     

复杂地区机载SAR数据获取航线规划

本文主要论述机载SAR数据获取航线规划,提出了适合于地形复杂地区机载SAR航摄的航线规划方案。详细说明了航线设计方法,并引入低分辨率的DEM数据,对航线规划结果进行了模拟;最后对机载合成孔径雷达航摄进行三维模拟,以期更好地显示并检验航线规划结果。     

GPS技术在矿区井筒变形监测中的应用

本文介绍了有用GPS技术对矿区井筒变形进行监测时监测网设计要求和实测方案，数据处理所采用的模型和变形分析的方法与结果，并简要讨论了在矿区进行GPS监测所存在的问题和解决的基本思路。     

Behavior mining of spatial objects with data field

The advanced data mining technologies and the large quantities of remotely sensed Imagery provide a data mining opportunity with high potential for useful results. Extracting interesting patterns and rules from data sets composed of images and associated ground data can be of importance in object identification, community planning, resource discovery and other areas. In this paper, a data field is presented to express the observed spatial objects and conduct behavior mining on them. First, most of the important aspects are discussed on behavior mining and its implications for the future of data mining. Furthermore, an ideal framework of the behavior mining system is proposed in the network environment. Second, the model of behavior mining is given on the observed spatial objects, including the objects described by the first feature data field and the main feature data field by means of the potential function. Finally, a case study about object identification in public is given and analyzed. The experimental results show that the new model is feasible in behavior mining.     

基于数据场的空间目标行为挖掘

The advanced data mining technologies and the large quantities of remotely sensed Imagery provide a data mining opportunity with high potential for useful results. Extracting interesting patterns and rules from data sets composed of images and associated ground data can be of importance in object identification, community planning, resource discovery and other areas. In this paper, a data field is presented to express the observed spatial objects and conduct behavior mining on them. First, most of the important aspects are discussed on behavior mining and its implications for the future of data mining. Furthermore, an ideal framework of the behavior mining system is proposed in the network environment. Second, the model of behavior mining is given on the observed spatial objects, including the objects described by the first feature data field and the main feature data field by means of the potential function. Finally, a case study about object identification in public is given and analyzed. The experimental results show that the new model is feasible in behavior mining. Supported by the National 973 Program of China(No.2006CB701305,No.2007CB310804), the National Natural Science Fundation of China (No.60743001), the Best National Thesis Fundation (No.2005047), the National New Century Excellent Talent Fundation (No.NCET-06-0618).     

井区沉陷与边坡稳定监测及预报分析方法研究

深入研究井区沉降和边坡的稳定性监测方法、分析预报方法,并对不同煤层情况下的监测成果采用多项式数学模型、指数数学模型进行了趋势分析,利用得到的趋势函数,通过公式推导,获得了不同煤层对应岩层最大沉降的位置和时间。     

基于哨兵数据的云南地表形变监测

云南省作为我国西南地区与西藏相连的省份,其地势由西北向东南逐渐降低且山峦众多,山区面积占全省面积的88％.除此之外,云南省还位于印度洋板块和亚欧板块交界处附近,其地震带众多,地质运动频繁,经常出现地震、滑坡、泥石流等地质灾害.因此,本文选取覆盖地势较高的云南西北部地区的哨兵数据,利用SBAS-InSAR技术进行数据处理...     

D-InSAR的黄土高原矿区地表形变监测

D-InSAR技术已在数字高程建模、地表微小变形、地壳形变等方面显示出广阔前景,但其对黄土高原矿区复杂、剧烈、动态的地表形变监测能否有效,目前仍存在争议。针对此问题,该文以大同市南郊区采煤沉陷地为研究区域,利用两轨法D-InSAR技术,采用ALOS PALSAR数据获取了研究区域2008年1月1日至2月16日间的沉陷面积和最大沉降值。然后以晋华宫矿某工作面为例,利用开采沉陷预计方法进行验证,预计结果显示该工作面的最大沉陷值与D-InSAR测量值相差达24.04mm,并分析差异主要来源于SAR数据、地形、预计参数选取的限制。实验结果表明,D-InSAR技术能够比较准确且有效地监测黄土高原矿区地表形变。