Micro Landform Extraction Based on UAV Photography Technology?Taking Kunzhong Fault (Balong Wenquan Section) as An Example

无人机测量具有高清晰度、大比例尺、小面积、高现势性的优点,为地貌参数获取提供更准确可靠的活动构造定量参数,克服传统测量方法工作量大、效率低、受自然条件限制等缺点,可提供厘米级定位数据,从而显著提升图像元数据的绝对精度。利用大疆精灵4 RTK小型多旋翼高精度航测无人机,获取昆中断裂（巴隆-温泉段）在龙通村北的高精度DEM地貌数据,通过对微地貌的提取,初步确定断裂在该处的水平位错量为2.1～15.4 m。分析获取的8条陡坎剖面,认为其中5条陡坎形成后受到水流侵蚀作用较小,陡坎高度基本相似,断裂实际垂直位错量为0.6～0.9 m。研究结果表明,无人机航测技术是识别复杂地貌构造信息并提取相关活动构造参数的有效手段,可为断裂的定量研究提供可靠的数据基础。     

长距离RTK动态测量滑坡监测精度分析

短基线RTK技术的精度符合滑坡监测的要求,由于滑坡地带的特殊性,在利用RTK技术进行滑坡监测时,流动站与基准站构成长基线。长基线RTK观测精度是否符合滑坡监测精度要求未知。进行了模拟实验,设定一条长基线,利用RTK观测对固定不动的观测点进行动态测量,求出其观测坐标,将观测坐标与平均坐标相比,并利用求坐标中误差的方法解算出水平精度和高程精度,结果求得的水平精度和高程精度都达到了厘米级。结果显示:长基线RTK技术可以很好的用于滑坡监测,且监测精度达到厘米级。     

基于网络/基站RTK移动摄影测量数据的垂向精度分析

移动摄影测量技术SfM（Structure from Motion）的发展使活动构造研究中快速获得野外中小区域内高精度DEM数据更便捷,DEM数据精度是目前活动构造与测量领域较关注的问题。本文通过对比非RTK模式无人机摄影测量并结合地面控制点（GCPs）生成的SfM DEM数据与基于RTK移动摄影测量技术获取的RTK-SfM DEM数据差异,重点分析搭载RTK模块的移动摄影测量技术获取的DEM数据在垂向上的精度。数据采集、处理与对比结果表明:在添加地面控制点后的非RTK模式无人机摄影测量生成的DEM数据中,除测量区域边缘照片较少而产生畸变外,大部分地区畸变率较小;基于移动RTK技术摄影测量获取的高程数据畸变率更小,且与非RTK模式无人机摄影结合地面控制点生成的高程数据存在约0.85 m的系统高程误差,减去该误差后,点云对比结果表明二者95%以上的点垂向误差均＜0.05 m;搭载RTK模块的移动摄影测量技术获取的DEM数据在垂向上具有更高的精度,且节省了时间与人工成本。     

基于无人机摄影测量技术研究有无地面控制点的差异性在地震方面的应用

利用无人机摄影测量技术获取影像数据,在集成SfM算法的Photoscan软件上进行影像的处理,通过定量分析有无地面控制点生成的DEM精度,进一步明确了其在水平位置和垂直高程上的差异;对比两种情况下在数据获取、处理过程和结果精度的优缺点,探讨了两者在地震不同方面的应用前景.结果 表明:在无控制点的情况下,影像数据获取简易...     

高起伏区无人机摄影测量精度评估?以西秦岭光盖山-迭山断裂为例

经过近10年的迅速发展,无人机摄影测量已成为活动构造研究的常用方法之一。但对于无人机摄影测量的精度评估,尤其是高起伏地区的精度评估存在不足。为此,选择白龙江北岸光盖山-迭山断裂沿线的黑峪寺、化马村,开展无人机摄影测量,并构建正射影像（DOM）和数字地表模型（DSM）,配合差分GPS测绘进行校正和精度验证。通过对比实测控制点和图像提取点分析点精度,通过对比实测剖面与提取剖面分析剖面精度。研究结果表明,未经控制点校正的图像提取点与实测点存在较大误差,水平误差为5～8 m,垂直误差为几十米至上百米,但通过少数控制点校正后,点精度可达20 cm以内;6条实测剖面与提取剖面（提取自控制点校正后的图像）平均垂直精度总体为分米级,即0.16～0.65 m,标准差为0.13～0.69 m,略低于低起伏区的精度,对于测量条件恶劣的高起伏区,该精度是可接受的;异常高的垂直误差常出现在地形突变、低矮植被密集、行走困难等测量条件不理想位置。图像控制点中心点的准确识别、提取剖面线的修正准确性等因素也会影响精度评估的可靠性。     

北斗区域卫星导航系统基本导航定位性能初步评估

北斗区域卫星导航系统(也称北斗2代1期)于2012年12月27日正式开始运行,系统由14颗卫星组成,包括5颗地球静止轨道卫星、5颗倾斜地球同步轨道卫星和4颗中圆地球轨道卫星.本文初步评估了北斗区域卫星导航系统建成运行后的基本导航定位性能,包括卫星可见性、位置精度衰减因子、伪距和载波相位观测量精度、单点定位和差分定位精度以及模糊度解算性能等.通过实验分析可知:北斗伪距和载波相位测量精度已与GPS处在同一水平,伪距测量精度约为33 cm,载波测量精度约为2 mm;北斗伪距单点定位水平精度优于6 m,高程精度优于10 m,已满足设计要求;北斗区域卫星导航系统已具备独立的双频RTK定位能力,其单历元双频模糊度解算成功率几乎与GPS相当;北斗载波相位差分定位精度与GPS相位差分定位处在同一水平,超短基线情况下,定位精度优于1 cm,而在短基线情况下优于3 cm;北斗与GPS组合定位时,模糊度解算的固定率和可靠性均显著提高;在短基线情况下,北斗/GPS组合载波相位差分动态定位精度相对于单一的GPS定位的改善可达20%以上;北斗单频伪距差分定位精度优于2.5 m,与GPS相比仍存在较大差距,其主要原因可能为北斗GEO卫星伪距多路径误差较大.     

近几年地面重力调查工作方法技术的一些进展

近年来随着电子科技的进步,推动着物探仪器水平提高,促进了地面重力调查工作在方法技术上获得一些关键突破.包括GPS-RTK技术、CORS系统的引入,使得重力测点的平面位置与高程测量精度都有了显著提高;激光测距仪、RTK模式在近区地改实测地形中的应用,提高了近区地改的效率和精度.本文通过结合冀东铁矿外围覆盖区的高精度重力调查情况,阐述了在控制点测量、测点GPS高程转换、近区地改和中区地改方面的工作经验,总结了重力调查工作中一些方法技术的进展.     

控制点对区域流动重力测网平差精度的影响

为分析控制点对区域流动重力测网平差精度的影响,利用江苏测区的流动重力观测数据,从参与平差计算的控制点数量以及空间分布两个角度,分析控制点对平差后的重力测网精度的影响规律,并进一步分析了本区域测网的监测能力。结果显示：采用单个基准点进行平差计算,基准点应当选择尽量靠近测网几何中心或多个闭合环节点的位置;当采用在空间分布上较为均匀控制点平差计算时,控制点周边测点与测网中部测点的点值精度并没有明显的差别。结合江苏区域重力测网的空间分辨率和观测数据平差处理精度,认为江苏重力测网对5级以上地震具有较好的监测效果,同时对4～5级地震也具有一定的监测能力。结果可为重力数据处理中合理的采用基准点进行平差、提升资料处理精度提供参考依据。     

基于无人机摄影测量技术的地震地表破裂带定量参数提取 ——以1709年中卫南M7½地震为例

本文首先介绍了无人机摄影测量技术获取数字高程模型(digital elevation model,缩写为DEM)和地貌数据(正射影像)的作业流程,对比分析了三种不同质量密集点云生成的DEM在水平位置和高程上的差异;然后以1709年中卫南M7?大地震的主体地表破裂带为例,提取其上地震断层的垂直位错量和水平位移量.研究结果...     

凹凸体位错非均匀性对断层引起地表位移的影响

在已有的凹凸体震源模型基础上考虑凹凸体位错非均匀性,提出改进的凹凸体位错模式.新的位错模式随机设置凹凸体上各子断层位错量,同时在凹凸体与背景区交界处设置位错平缓变化的区域.以1989年美国 LomaPrieta地震为例,计算不同断层位错模式下引起的地表位移,并与反演得到真实情况下地表的位移作对比,验证改进凹凸体位错模式的可靠性.结果显示,使用改进的渐变凹凸体非均匀位错模式计算时,与真实情况下竖向地表位移差大于8cm 的区域面积为 43km2,相较凹凸体均匀位错模式缩减25%;水平地表位移差大于8cm 区域面积为117km2,相较凹凸体均匀位错模式缩减达31%.利用改进的渐变凹凸体非均匀位错模式,计算1679年三河—平谷大地震在北京地区形成的地表位移场.北京市外,最大竖向地表位移大于4．8m,最大水平地表位移大于2．6m,均出现在三河附近;北京市内,通州区至平谷区一带地表位移最大,最大水平地表位移大于 2．6m,最大竖向地表位移大于1m.研究结果可为今后北京地区的抗震设防提供参考.     

THE APPLICATION OF MINIATURE UNMANNED AERIAL VEHICLE IN 25 NOVEMBER 2016 ARKETAO MW6.6 EARTHQUAKE

In order to complete the field investigation to the 25 November 2016 Arketao M_W6.6 earthquake, ultra-low altitude remote-sensing data were obtained from miniature unmanned aerial vehicle. The surface rupture surveying has important significance for earthquake research. This paper selects the macro-epicenter of Arketao as the study area. The pictures were obtained with DJI Phantom 3 professional input into the software, the Digital Elevation Model (DEM), Digital Orthophoto Map (DOM) were acquired based on photogrammetry method using the overlapped optical remote-sensing images of UAV. Using these data, we can identify surface ruptures that have vertical dislocation. We selected six feature points and drew the elevation profile. In the elevation profile map, we chose smooth part of the surface rupture sides and obtained the trend line. A stable point in the surface rupture was selected and the abscissa of the point was taken into the equation of two straight lines. Then subtracting the results of the two equations, we can get the vertical dislocation of the surface rupture. On this basis, we chose six feature points and determined their vertical dislocation, which are between 4.4cm and 10.4cm. What's more, taking Bulungkou Xiang in Xinjiang Uygur Autonomous Region for example, we speculated some surface ruptures that have vertical dislocation. It can provide a new method for identifying surface rupture in the field. In addition, we get DEM data of the Bulunkou area where ambient conditions are very poor, by using miniature unmanned aerial vehicle and taking 255 photos. Putting those photos into the EasyUAV software, we got the area digital elevation of 2cm resolution. Comparing these data with RTK data, we summarized some practical problems and solutions in the practical operation and evaluated the accuracy of miniature unmanned aerial vehicle data. The Pearson Correlation Coefficient is 0.996 6. In terms of absolute elevation, the average result of UAV and RTK differs by 156.96m. In terms of relative elevation, the average result of UAV and RTK differs by 9.74m. Compared with the previous test of Pishan County, there is a notable divergence in the results. It shows that the data accuracy will be affected to some extent in the cold weather in high elevations. The specific impact needs further exploration.     

Reducing systematic dome errors in digital elevation models through better UAV flight design

It is well established that digital elevation models (DEMs) derived from unmanned aerial vehicle (UAV) images and processed by structure from motion may contain important systematic vertical errors arising from limitations in camera geometry modelling. Even when significant, such ‘dome’-shaped errors can often remain unnoticed unless specific checks are conducted. Previous methods used to reduce these errors have involved: the addition of convergent images to supplement traditional vertical datasets, the usage of a higher number of ground control points, precise direct georeferencing techniques (RTK/PPK) or more refined camera pre-calibration. This study confirms that specific UAV flight designs can significantly reduce dome errors, particularly those that have a higher number of tie points connecting distant images, and hence contribute to a strengthened photogrammetric network. A total of 22 flight designs were tested, including vertical, convergent, point of interest (POI), multiscale and mixed imagery. Flights were carried out over a 300 × 70 m² flat test field area, where 143 ground points were accurately established. Three different UAVs and two commercial software packages were trialled, totalling 396 different tests. POI flight designs generated the smallest systematic errors. In contrast, vertical flight designs suffered from larger dome errors; unfortunately, a configuration that is ubiquitous and most often used. By using the POI flight design, the accuracy of DEMs will improve without the need to use more ground control or expensive RTK/PPK systems. Over flat terrain, the improvement is especially important in self-calibration projects without (or with just a few) ground control points. Some improvement will also be observed on those projects using camera pre-calibration or with stronger ground control. © 2020 John Wiley & Sons, Ltd.     

From consumer to enterprise grade: How the choice of four UAS impacts point cloud quality

Uncrewed aerial systems (UAS), combined with structure-from-motion photogrammetry, has already proven to be very powerful for a wide range of geoscience applications and different types of UAS are used for scientific and commercial purposes. However, the impact of the UAS used on the accuracy of the point clouds derived is not fully understood, especially for the quantitative analysis of geomorphic changes in complex terrain. Therefore, in this study, we aim to quantify the magnitude of systematic and random error in digital elevation models derived from four commonly used UAS (XR6/Sony α6000, Inspire 2/X4s, Phantom 4 Pro+, Mavic Pro) following different flight patterns. The vertical error of each elevation model is evaluated through comparison with 156 GNSS reference points and the normal distribution and spatial correlation of errors are analysed. Differences in mean errors (−0.4 to −1.8 cm) for the XR6, Inspire 2 and Phantom 4 Pro are significant but not relevant for most geomorphological applications. The Mavic Pro shows lower accuracies with mean errors up to 4.3 cm, thus showing a higher influence of random errors. QQ plots revealed a deviation of errors from a normal distribution in almost all data. All UAS data except Mavic Pro exhibit a pure nugget semivariogram, suggesting spatially uncorrelated errors. Compared to the other UAS, the Mavic Pro data show trends (i.e. differences increase with distance across the survey—doming) and the range of semivariances is 10 times greater. The lower accuracy of Mavic Pro can be attributed to the lower GSD at the same flight altitude and most likely, the rolling shutter sensor has an effect on the accuracy of the camera calibration. Overall, our study shows that accuracies depend highly on the chosen data sampling strategy and that the survey design used here is not suitable for calibrating all types of UAS camera equally.     

局部区域GNSS地壳形变监测系统设计与精度分析

为探索页岩气开采与地壳形变的关系、地表形变对页岩气压裂的响应等,布设一套GNSS跨断层形变监测系统。该系统综合使用静态和动态测量方法采集地表形变信息,结合多种GNSS定位方式增加监测区域地表动态位移信号探测的可靠性,并利用网络通讯与云服务器实现数据的自动化传输、设备的远程管理和站点的动态监测。考虑到测量误差与形变量之间的可区分度问题,文章从测量精度方面进行详细的分析。静态测量计算结果表明,单日基线解和PPP静态解精度在水平和垂直方向均可达到10 mm以内。四川泸定6.8级地震动态定位计算结果表明,RTK解、PPK解和PPP动态解时间序列中,瞬态地表位移信号的可识别程度也可达到10 mm以内。精度分析结果认为该系统可以较好地反映监测区域的部分长期和瞬态形变信息。     

A novel method for the quantitative assessment of the ionosphere effect on high accuracy GNSS applications,which require ambiguity resolution

Real time kinematic, or RTK, is a high-accuracy GPS relative positioning technique, which allows to measure positions in real time with an accuracy usually better than 1 decimeter. Ionospheric small-scale variability can strongly degrade RTK accuracy. In this paper, we present a method allowing to assess in a direct quantitative way the influence of the ionospheric activity on RTK accuracy. We apply this method to two different ionospheric situations: a day where strong travelling ionospheric disturbances (TIDs) were detected (December 24, 2004) and a day where a severe geomagnetic storm was observed (November 20, 2003). We show that on a 4 km baseline, strong TIDs have the same influence as the ionospheric variability induced by a geomagnetic storm on RTK accuracy: in both cases errors of more than 1.5 m are observed.     

Optimization of UAVs-SfM data collection in aeolian landform morphodynamics: a case study from the Gonghe Basin,China

UAVs-SfM (unmanned aerial vehicles-structure-from-motion) systems can generate high-resolution three-dimensional (3D) topographic models of aeolian landforms. To explore the optimization of UAVs-SfM for use in aeolian landform morphodynamics, this study tested flight parameters for two contrasting aeolian landform areas (free dune and blowout) to assess the 3D reconstruction accuracy of the UAV survey compared with field point measurements using differential RTK-GPS (real-time kinematic-global positioning system). The results reveal the optimum UAVs-SfM flight set-up at the free-dune site was: flying height = 74 m, camera tilt angle = −90°, photograph overlap ratio = 85%/70% (heading/sideways). The horizontal/vertical location error was around 0.028–0.055 m and 0.053–0.069 m, respectively, and a point cloud density of 463/m³ was found to generate a clear texture using these flying parameters. For the < 20 m deep blowout the optimum set-up with highest accuracy and the lowest cliff texture distortion was: flying height = 74 m combined camera tilt angle = −90° and −60°, photograph overlap ratio = 85%/70% (heading/sideways), and an evenly distributed GCPs (ground control points) density of 42/km² using these flying parameters. When the depth of the blowouts exceeded 40 m, the optimum flight/survey parameters changed slightly to account for more challenging cliff texture generation: flying height = 80 m (with −90° and −60°combined camera tilt angle), GCPs density = 63/km² to generate horizontal and vertical location error of 0.024 m and 0.050 m, respectively, and point cloud density of 2597.11/m³. The main external factors that affect the successful 3D reconstruction of aeolian landforms using UAVs-SfM are the weather conditions, manipulation errors, and instrument system errors. The UAVs-SfM topographic monitoring results demonstrate that UAVs provide a viable and robust means for aeolian landform morphodynamics monitoring. Importantly, the rapid and high precision 3D reconstruction processes were significantly advanced using the optimal flight parameters reported here. © 2020 John Wiley & Sons, Ltd.     

APPLICATION OF DEM GENERATION TECHNOLOGY FROM HIGH RESOLUTION SATELLITE IMAGE IN QUANTITATIVE ACTIVE TECTONICS STUDY: A CASE STUDY OF FAULT SCARPS IN THE SOUTHERN MARGIN OF KUMISHI BASIN

Traditional method to generate Digital Elevation Model (DEM)through topographic map and topographic measurement has weak points such as low efficiency, long operating time and small range. The emergence of DEM-generation technology from high resolution satellite image provides a new method for rapid acquisition of large terrain and geomorphic data, which greatly improves the efficiency of data acquisition. This method costs lower compared with LiDAR (Light Detection and Ranging), has large coverage compared with SfM (Structure from Motion). However, there is still lack of report on whether the accuracy of DEM generated from stereo-imagery satisfies the quantitative research of active tectonics. This research is based on LPS (Leica Photogrammetry Suit)software platform, using Worldview-2 panchromatic stereo-imagery as data source, selecting Kumishi Basin in eastern Tianshan Mountains with little vegetation as study area. We generated 0.5m resolution DEM of 5-km swath along the newly discovered rupture zone at the south of Kumishi Basin, measured the height of fault scarps on different levels of alluvial fans based on the DEM, then compared with the scarp height measured by differential GPS survey in the field to analyze the accuracy of the extracted DEM. The results show that the elevation difference between the topographic profiles derived from the extracted DEM and surveyed by differential GPS ranges from -2.82 to 4.87m. The shape of the fault scarp can be finely depicted and the deviation is 0.30m after elevation correction. The accuracy of measuring the height of fault scarps can reach 0.22m, which meets the need of high-precision quantitative research of active tectonics. It provides great convenience for rapidly obtaining fine geometry, profiles morphology, vertical dislocations of fault and important reference for sites selection for trench excavation, slip rate, and samples. This method has broad prospects in the study of active tectonics.