全数字摄影测量技术在莫高窟崖面保护中的应用

随着计算机技术和测绘技术的不断发展,摄影测量发展到了全数字摄影测量阶段。作为摄影测量学的一门分支学科--近景摄影测量在建筑物的变形观测,动态监测、文物保护等工作中起着很重要的作用。通过对敦煌莫高窟崖面进行数字近景摄影测量,着重介绍利用全数字近景摄影测量技术获取大范围复杂地貌崖面的高精度立面地理空间数据的方法及在文物的维护、修复中的应用。     

基于地表变形的摄影测量方法研究

开采矿山会破坏岩层内部的应力平衡状态,进而导致地表产生滑坡或移动等变形。因此,安全监视矿区可能产生的地表变形尤为重要。摄影测量技术是一种非接触的测量手段,利用该技术不仅能有效监测地形情况,还能随意定向,瞬间获取地表信息。就摄影测量技术在地表变形监测中的应用进行了分析,以供参考。     

利用近景摄影测量技术的滑坡监测新方法

将近景摄影测量技术应用于山体滑坡监测中,提出一种无需二次控制的、非接触的、快速的滑坡监测方法。方法采用旋转摄影或正射平行摄影的方式,对监测区域进行摄影,根据摄影测量原理获取目标监测区域的DEM模型。通过自动匹配控制点以及对两期DEM模型进行叠加分析,计算出山体在该时间段内的滑坡绝对位移量以及滑坡区域的局部变化量。利用模拟数据进行实验,结果表明该方法行之有效,能够方便地对滑坡体进行快速、准确的监测。     

数字孪生水下三维实景数据底板获取技术研究

为了获取高精度的水下三维模型细节纹理结构,满足数字孪生建设对水下三维实景数据底板获取的需求,实现对水下构筑物的实时可视化动态监测,基于GNSS技术、USBL技术研究构建了水陆一体化定位技术,融合水陆一体化定位技术、有缆ROV和水下摄影测量设备等研发了水下摄影测量系统,实现了数字孪生水下三维实景数据底板的获取,并采用多波束测深系统、水下三维全景成像声纳系统等对水下摄影测量系统获取的三维实景模型数据成果精度进行了验证,结果表明：水下摄影测量系统获取的三维实景模型精度满足规范要求,可用于数字孪生流域、工程等水下基础数据底板的建设,也可为水下高精度三维场景重构再现和水利工程水下构筑物实时动态监测提供技术支撑。     

基于数字近景立体摄影的三维表面模型构建

采用经过标定的数字近景立体摄影系统Z—System获取待建模对象的数字立体像对序列,探讨利用这些立体像对进行三维表面构建的方法。在构建三维目标表面模型时,首先根据数字近景立体摄影测量原理,提取目标表面的特征点和计算特征点的三维坐标;然后利用各立体像对内特征点的像平面坐标,按二维空间TINTIN（triangulated irregular network）构建方法得到离散特征点在三维空间中的拓扑连接关系,进而构建单像对内目标的局部表面TIN模型;最后再利用序列像对间的公共连接点,进行坐标转换,从而在三维空间中将各单立体像对的表面模型拼接成一个完整的三维表面模型。实验结果表明,该方法具有快速灵活的特点且行之有效。     

基于迁移学习的低空摄影测量滑坡方量估算方法

针对现有方法难以准确地估算山体滑坡体积的问题,引入人工智能算法,提出耦合迁移学习与微分算法的低空摄影测量山体滑坡方量估算方法。首先,利用SfM与SGM密集匹配等算法从低空无人机立体影像中解算出高精度三维密集点云,结合可见光植被指数和双边滤波算法从密集点云中剥离出目标区地面点云;然后,构建深度神经网络插值模型来表征二维坐标与高程之间的非线性映射关系,并基于参数共享的迁移学习来自适应优化深度神经网络以实现滑坡目标区高程值预测,进而重构滑坡区域的数字地表模型;最后,基于目标区滑坡前后数字地表模型高程差值和微分算法实现山体滑坡方量估算。实验结果表明,该方法平均相对误差为2.7%,相比常用的方法,显著提高了滑坡方量估计精度,并能适应不同地形条件下滑坡方量估算。     

基于WorldView-2制备大野口流域高分辨率DEM及精度分析

在全野外GPS地面控制点基础上,对WorldView-2影像自带RPC文件进行校正,利用数字摄影测量软件系统在立体模型上通过影像自动匹配技术快速提取黑河流域上游大野口子流域1∶5 000比例尺数字高程模型(DEM)。由于区域地形复杂、交通不便,研究区南部无地面控制点覆盖。基于立体模型交互式操作,匹配60个均匀分布高精度影像连接点,提高了DEM自动提取精度。并在对阴坡森林覆盖区、大野口水库等重点区域进行DEM编辑基础上,辅助地形特征点和线数据提高了成果精度。由15个外业控制点、12个模型保密点组成的检查点进行定量DEM验证,结果表明:两组高程中误差最大为1.9 m,达到该比例尺山地一级精度2.5 m的要求。
     

近景目标立体影像用于城市三维建模的空间定位

该文利用数字近景摄影测量的方法,对构成立体影像的近景目标序列影像进行数字摄影测量处理,以提取目标模型的三维空间坐标。给出了自由网模型的构建方法和大角度模型拼接的方法,解决了三维空间模型在没有控制点,仅有相对控制条件下,光束法自由网平差解算的空间基准问题。并给了三维网空间定位的实现过程和结论。     

2种灰色模型在矿区地表沉陷预计中的适用性

目前矿区地表单点沉陷动态预计方法主要基于传统的水准测量数据,监测方法单一,成本高,观测点易破坏,不能保证地表形变信息的实时性,且采用灰色模型进行地表沉陷预计时只针对单一模型的应用,没有结合模型自身特点分析其适用性。以袁店二矿7221工作面为试验区域,采用合成孔径雷达差分干涉测量技术监测矿区地表沉陷量,分别建立了描述沉陷量与时间关系的GM(1,1)与灰色Verhulst模型进行地表沉陷量预计,实现了矿区地表沉陷监测与动态预计一体化。通过比较、分析GM(1,1)与灰色Verhulst模型对地表沉陷量的拟合及预计结果,得出了2种灰色模型在矿区地表沉陷预计中的适用性:在矿区开采沉陷开始至活跃前期,若地表单点沉陷量曲线呈近似单峰型,则宜采用GM(1,1)进行短期预计;当矿区地表沉陷进入衰退阶段,单点沉陷量曲线呈平底饱和状态,则宜采用灰色Verhulst模型进行中长期预计。     

基于D-InSAR技术的淮南矿区地面沉陷监测

针对常规的通过大地水准测量、GPS测量监测矿区地面沉陷的技术存在监测周期长、成本高、无法全面监测等缺陷,提出了一种基于D-InSAR技术的矿区地面沉陷监测方法。以淮南矿区为试验区,采用两轨法D-InSAR技术,利用该地区2个时相的ALOS PALSAR数据获取了淮南矿区试验时间段内的地面形变图,分析了淮南矿区各矿的地面沉陷信息。结果表明,煤矿开采区存在5~25 cm不同程度的沉陷,与实际情况相符,因此,基于D-InSAR技术的监测方法可以作为一种获取矿区大范围的地表沉陷信息的有效方法。     

Dynamic monitoring of land subsidence in mining area from multi-source remote-sensing data – a case study at Yanzhou,China

Energy consumption in China is currently based on coal, but the exploitation of coal resources is accompanied by serious threats to the environment. In order to balance mine exploitation, land resource protection and land reclamation, there is an opportunity for monitoring land subsidence in mining area. This article examines a case study of Yanzhou mining area (YZMA) and proposes a new method for dynamic monitoring of land subsidence, which is a hybrid approach using a combination of multi-scale edge detection, relational model establishment and digital elevation model (DEM) difference analysis. A wavelet transform is used to extract the edges of water and marsh, which are buffered with the model to achieve the acquisition of the subsidence edge. DEM difference analysis is finally used to modify the results. The results indicate that this hybrid method improves subsidence monitoring performance by ±0.02 km² of the area accuracy. This method can be viewed as an effective approach to monitor a wide range of land subsidence in plain mining areas of China.     

Modelling glacier topography in Antarctica using unmanned aerial survey: assessment of opportunities

We discuss the application of unmanned aerial systems (UASs) and UAS-derived data to model glacier topography for detecting and analysing slow and rapid changes in glacier surfaces. The study was conducted in East Antarctica in the austral summer 2016/2017. The surveyed areas included an eastern part of the Larsemann Hills, an Airfield of the Progress Station, an initial section of a Sledge route from the Progress to Vostok Stations, and a north-western margin of the Dålk Glacier. We used a Geoscan 201 Geodesy, a professional-grade flying-wing UAS. For the photogrammetric processing, we utilized the Agisoft PhotoScan software. The direct georeferencing approach was applied. Several high-resolution, multitemporal digital elevation models (DEMs) for surveyed areas were produced. The DEM accuracy was estimated in the absence of ground control points and reference DEMs. We determined the ice flow velocity within the Airfield area and the Sledge route zone, where marked points were installed and moved together with the ice surface. We found that UAS imagery can be used for real-time monitoring of open and some snow-covered crevasses of various sizes. Wind-driven snow microforms are also well recognizable on UAS-derived aerial images. The 2017 Dålk Glacier catastrophic subsidence demonstrated that monitoring and studying such events in glaciers and ice sheets are almost impossible without UASs. Optimal meteorological conditions were empirically determined for conducting unmanned aerial survey to obtain images suitable for subsequent photogrammetric processing and DEM generation. Finally, we discuss adaptation of equipment and software to the Antarctic environment.     

Validation and comparison of different techniques for the derivation of digital elevation models and volcanic monitoring (Vulcano Island,Italy)

High accurate digital elevation models (DEM) acquired periodically over a volcanic area can be used for monitoring crustal deformations. Airborne stereoscopic photography is a powerful tool for the derivation of high resolution DEM, especially when combined with Global Positioning System (GPS). We analyse data acquired on Vulcano Island (Italy) to assess the performance of two photogrammetry methods for DEM generation. The first method is based on automatic digital processing of scanned airborne stereo images from a film camera (Wild RC20). In the second method digital stereo data from the multi-spectral High Resolution Stereo Camera-Airborne (HRSC-A) are used. Accuracy assessment through comparison with kinematic GPS height profiles shows that both DEMs have accuracy on the order of few decimetres. Direct comparison of the two DEMs on the La Fossa volcanic cone provides a standard deviation of the residuals of 78 cm. Residuals greater than two metres between the two DEMs acquired at one year interval are locally evidenced in unstable areas with uneven morphology. The application of photogrammetric DEMs is also discussed within a SAR interferometry study carried out on Vulcano Island to evaluate the potentialities of such techniques for ground deformation monitoring. Although accuracy better than 1 m or 2 m is not required for satellite SAR interferometry, we show how the precise photogrammetric DEMs could still significantly improve SAR interferograms of Vulcano Island.     

Combining Structure from Motion and close-range stereo photogrammetry to obtain scaled gravel bar DEMs

ABSTRACT

Digital elevation models (DEMs) have been increasingly applied in topographic studies in areas such as physical geography and hydraulic engineering. Several methods have been proposed to reconstruct DEMs, including classic close-range stereo photogrammetry and the more novel Structure from Motion (SfM) methodology. Past published studies tend to apply SfM to large-scale environmental processes, whilst classic close-range stereophotogrammetry is focusing on detailed small-scale applications. However, SfM requires multiple ground control points (GCPs) to allow for proper DEM scaling. The larger the study area, the more GCPs are required, resulting in increased operational complexity and time-consuming application of SfM. As the accuracy of the DEM depends on the equipment used to measure GCPs, this can also result in a cost-expensive operation. In the present study, we introduce a combined SfM and close-range stereo photogrammetry application, with the close-range stereo photogrammetry results serving as a control for providing scale, thus eliminating the need for traditional GCPs. To validate our methodology, we studied a 40 m long gravel bar. We used GoPro Hero 3 cameras for SfM measurements and replaced GCPs by DEMs obtained through close-range stereo photogrammetry with a Nikon D5100 camera pair in stereo. In addition to using photo-mode frames, we also studied the quality of DEMs obtained with GoPro Hero 3 video-mode frames, and show how the DEM quality is reduced due to the smaller image format, hence coarser point cloud spacing, which eventually results in a convex curvature when image overlap was increased. Our results show that it is possible to collect high-quality topographic surface data by only using cameras, and alleviate the need for GCPs. The proposed workflow reduces the complexity, time, and resource demands associated with deploying GCPs and necessary independent geo-referencing, ensuring that digital photogrammetry will continue to gain popularity for field surveying.     

面向对象的高分辨率影像采煤塌陷地提取

煤炭开采引起了塌陷等一系列的地质环境问题,与常规监测方法相比,遥感技术可以实现大范围、高效率、周期性的动态监测。在遥感影像分类方法中,面向对象的遥感影像分类方法能更好地利用高分辨率遥感影像中丰富的纹理和几何结构信息。针对煤炭开采导致的地表塌陷地的特点,在归纳整理遥感影像中塌陷地判识准则的基础上,重点探讨了面向对象的遥感影像分类方法中塌陷地的自动提取规则。综合利用ERDAS IMAGINE9.2、ENVI4.7和ENVI4.4 ZOOM进行数据处理,以安徽省淮南矿务集团潘三矿区为实验区,用该方法利用SPOT５影像进行了塌陷地信息提取实验,结果证明,面向对象分类方法能有效地从高分辨率遥感影像中自动提取塌陷地相关信息。     

LIDAR点云支持的CCD影像地理编码

针对传统航空摄影测量生成有地理编码的正射影像需要一定的地面控制点、密集的同名点匹配和繁琐的DEM人工编辑,本文将LIDAR点云作为控制基准,采用共线、共面等几何约束条件,联合平差求出CCD影像的外方位元素,并采用LIDAR点云滤波后的DEM,对CCD影像进行正射纠正,生成具有地理编码的影像数据,可有效地提高工作效率,节省大量时间和人工成本,试验结果证实了这种思路和算法的可行性。     

A semi-automated method to create a lidar-based hydro-flattened DEM

The response of water surfaces to light detection and ranging (lidar) pulses is unpredictable, which results in sparse lidar point density with varying intensity values. Due to the sparseness of the point cloud and lack of natural breaklines, lidar-derived digital elevation model (DEM) can produce unnatural surface over waterbodies. Such surfaces are not cartographically pleasing and can cause issues in the hydrologic and hydraulic modelling of a river. Hydro-flattening is the process of creating a lidar-derived DEM in which water surfaces appear and behave as they would in traditional topographic DEMs generated from photogrammetric digital terrain models. Hydro-flattened DEMs, created using lidar data, exclude the lidar points over waterbodies and include three-dimensional (3D) bank shorelines. In this article, a semi-automated method is presented for extracting bank shorelines for the purpose of creating lidar-derived hydro-flatten DEMs. Lidar point cloud and an approximate stream centreline are the primary data for this process. In the first step, a continuous bare ground surface (CBGS) is created by eliminating non-ground lidar points and by adding artificial underwater points. In the second step, the lowest elevation from the lidar point cloud within a radius distance from the river centreline is used to create a virtual water surface (VWS). This VWS is revised to consider water surface undulations such as ripples or waves, protruding underwater objects, etc. The revised VWS is then intersected with the CBGS to locate the two-dimensional (2D) bank shorelines. The 2D shorelines are assigned the elevations of the VWS and are used to produce a hydro-flattened DEM. The planimetric absolute mean separation of 0.94, 0.69, and 0.63 m for the three water surfaces is observed between the bank shoreline extracted using raw lidar points and a GPS (global positioning system) survey. The mean separation using vendor classified lidar points is 0.74, 0.67, and 0.64 m which are very similar to those using raw lidar.     

Monitoring of large-scale deformation in mining areas using sub-band InSAR and the probability integral fusion method

The large-scale and rapid land subsidence that occurs in mining areas often leads to problems, such as densely spaced interference fringes and the temporal decorrelation of interferometric synthetic aperture radar (InSAR) interferograms. To solve these problems, sub-band InSAR is applied to monitor the large-scale deformation that occurs in mining areas. First of all, four different bandwidth images with three sub-band bandwidth parameters are used to extract simulated mining-induced subsidence with seven different deformation magnitudes. The results of the simulation experiment suggest the following conclusions. In monitoring subsidence with different deformation magnitudes using images with different bandwidths, an optimal monitoring value exists; wider image bandwidths lead to smaller optimal monitoring values and higher monitoring accuracies. Therefore, an appropriate sub-band bandwidth should be selected that depends upon the image bandwidth and the subsidence level to achieve optimal monitoring. The optimal sub-band bandwidth for monitoring subsidence of different magnitudes in mining areas is determined through simulation experiments, and these conclusions can provide a technical basis for selecting the appropriate sub-band bandwidth for the monitoring of subsidence in mining areas. Although sub-band InSAR can reduce the number of interference fringes and the difficulty of unwrapping, the simultaneous introduction of large amounts of noise leads to reduced monitoring precision, and the application of the probability integral method in the prediction of mine subsidence is more mature. Therefore, the combined use of sub-band InSAR and the probability integral fusion method to monitor mining-induced deformation is proposed in this paper. The probability integral method is used to perform noise peeling on the interferometric phases of the sub-bands to improve the monitoring accuracy of sub-band interferometry. Then, according to the results of the simulation experiment, the fusion method with the appropriate sub-band bandwidth parameters is applied to monitor the surface deformation associated with working face 52,304 from 2 December 2012 to 13 December 2012. Finally, the monitoring results are compared with the results of monitoring using conventional differential interferometric synthetic aperture radar (D-InSAR) and global positioning system (GPS) field survey data. The results show that the reliability and accuracy of the fusion method are much better than those of conventional D-InSAR in monitoring the large-scale deformation that occurs at the edges of subsidence basins.