Creation of DTM with ASTER Data and Statistical Verification of the Accuracy of the Model (Western Peloponnese,Greece)

Abstract

In this paper we present the use of ASTER data for the creation of a Digital Terrain Model (DMT) of high accuracy. Using a stereo pair of ASTER satellite images with 15m resolution we created two DMTs: one with a 30m pixel size and another one with a 15m pixel size. Then we made a statistical verification of the two DTMs accuracy. We created another DTM with 30m pixel size from digitized contours of 1:50000 scale topographic maps. We first made an optical comparison of the two DTMs with 30m pixel size. Then we subtracted the two DTMs and we presented their difference. Finally, we verified the DTMs accuracy using 68 points of a well‐known elevation. All the results demonstrated that DTMs derived from ASTER data have very good accuracy.     

Semi-automatic Process for Hybrid DTM Generalization based on Structural Elements Multi-analysis

Abstract

The generalization of digital terrain models (DTMs) is a tool of great potential for simultaneous cartographic and photogrammetry generation processes at different scales, the main object of which is to feed different geographic information systems (GIS). These GIS enable multi-scale analysis and visualization through different data bases. This research proposes a semi-automatic DTM generalization process conditioned by a series of predefined parameters resulting in the generation of hybrid DTMs at different scales starting from a single cloud of points obtained through large-scale massive data acquisition processes. The generalization results obtained, applied on different areas of different relief, offer specific application ranks for each parameter with great precision, in contrast with DTMs obtained directly in each scale.     

利用GLAS激光测高数据评估DSM产品质量及精度优化

提出了一种利用卫星激光测高数据直接优化提升数字表面模型（DSM）产品精度的方法。选取境外中亚地区的资源三号DSM开展试验，通过采用多准则约束方法提取激光高程控制点，分别利用偏度、中值、线性、二次多项式等进行DSM误差修正，发现4种模型均能有效消除DSM系统误差，其中基于二次多项式的方法更适用于平地和丘陵地貌，线性模型更适用于高山地貌。试验验证了采用卫星激光测高数据优化境外DSM技术流程的可行性，最终可提高DSM的绝对高程精度。     

Accuracy assessment of digital elevation models by means of robust statistical methods

Measures for the accuracy assessment of Digital Elevation Models (DEMs) are discussed and characteristics of DEMs derived from laser scanning and automated photogrammetry are presented. Such DEMs are very dense and relatively accurate in open terrain. Built-up and wooded areas, however, need automated filtering and classification in order to generate terrain (bare earth) data when Digital Terrain Models (DTMs) have to be produced. Automated processing of the raw data is not always successful. Systematic errors and many outliers at both methods (laser scanning and digital photogrammetry) may therefore be present in the data sets. We discuss requirements for the reference data with respect to accuracy and propose robust statistical methods as accuracy measures. Their use is illustrated by application at four practical examples. It is concluded that measures such as median, normalized median absolute deviation, and sample quantiles should be used in the accuracy assessment of such DEMs. Furthermore, the question is discussed how large a sample size is needed in order to obtain sufficiently precise estimates of the new accuracy measures and relevant formulae are presented.     

Analogue, Analytical and Digital Photogrammetric Workstations: Practical Investigations of Peformance

Prospective customers often request information on the accuracy of digital photogrammetry. Suitable data have been scarce, so Leica has begun a programme of internal tests. These are neither comprehensive nor necessarily representative of other suppliers' equipment, but several experienced operators and sets of imagery are being used and the results do provide general guidelines. A selection of analogue, analytical and digital workstations is being tested, together with scanners giving different pixel sizes.
The early stages of the work are reported here. The tests include interior and exterior orientation of individual stereomodels followed by measurement of check points. Subsequent stages, covering DTMs, orthophotographs, mosaics and aerial triangulation, are planned.     

Digital Terrain Model Resolution and its Influence on Estimating the Extent of Rockfall Areas

As rockfall can cause a great deal of damage, it is essential to know its spatial propagation. Rockfall models are sensitive to the resolution of input data, i.e. the Digital Terrain Model (DTM) used. Nowadays, high resolution elevation data are available area‐wide from airborne laser scanning (ALS). However, rockfall models are designed for analysis on a certain scale, which means that high resolution input might not necessarily improve model results (e.g. for regional scale studies). Our aim is to estimate the reach of rockfall by analysing different input resolutions of an ALS DTM. The presented empirically–based model, implemented in Python 2.7, is a modified version of the zenital method including an iterative random walk trajectory model, which is designed for rockfall hazard assessment at the regional scale. Trajectories and rockfall probability maps are generated for selected DTM input resolutions. The comparison shows that high resolution DTMs do consider local topography better and thus lead to more realistic results than low resolution DTMs.     

基于多分辨率方向预测的LIDAR点云滤波方法

为了快速提取LIDAR点云中的地面点,生成高精度的DTM,提出了一种基于多分辨率方向预测的LIDAR点云滤波方法。该方法首先构建多种分辨率数据集,然后基于方向预测法以分辨率由低到高的顺序逐层进行数据集的平滑处理,最后以最高分辨率数据集的平滑结果为基准标记原始LIDAR点云。本方法通过分析反距离权重插值模型的不足,利用改进的模型进行裸露地面点的插值,得到高精度的DTM。实验表明,本文方法能有效地滤除地物,并保持原有的地形特征,算法效率高,具有一定的实用价值。     

Processing of Laser Scanner Data and Extraction of Structure Lines Using Methods of the Image Processing

激光扫描数据提供了一种新的手段用于获取高精度的数字地形表面模型. 原始的航空激光扫描数据表达的是一些非规则分布的"点云", 这些非规则分布的点需要进行有效的事后处理. 这种事后处理有2个目的:一是将那些分布在地表面上的点(即地面点)与分布在非地表面上的点(譬如树木、房屋或汽车上的点, 即非地面点)进行有效的分离;二是从分离后的地面点中提取结构线, 用于建立高精度的数字地面模型. 作者发展了一系列的基于数字形态学理论和稳健参数估计理论的方法用于分离和探测地面点. 这里所介绍和开发的提取结构线的算法建立在数字图像处理和表面曲率理论的基础上. 这些算法同样可以扩展地用于其他领域. 所介绍的基于数字图像处理理论处理原始的航空激光扫瞄数据和提取结构线的方法取得了很好的结果. 这一结论可以在本文中通过一系列的插图得到有力的证明.     

Accuracy test of point-based and object-based urban building feature classification and extraction applying airborne LiDAR data

Point-based and object-based building extractions were conducted in airborne LiDAR data in a sample area of Buffalo, New York. First, the earth surface points were filtered from the entire laser scan data set using a new filtering algorithm, which combines the TIN slope modelling and statistical analysis. The off-ground points were extracted for buildings in the study area using both point cluster analysis and object-oriented classifications. The accuracies of both approaches were tested using the digitised ground truth. The outcomes of accuracy testing of the point-based method are correctness: 88.74%, completeness: 92.67% and quality: 83.50%. The results of the accuracy of object-based building extraction are correctness: 87.21%, completeness: 60.14%, and quality: 55.26%. Reconstructions of 3D building models based on the extracted building points were performed. This study contributes scientific and technological knowledge for researchers in developing more effective methods in converting the LiDAR survey to a 3D GIS database.     

Accuracy assessment of GDEM,SRTM, and DLR-SRTM in Northeastern China

This paper compares the accuracy of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM), Shuttle Radar Topography Mission (SRTM) C-band and German Aerospace Centre (DLR)-SRTM X-band digital elevation models (DEMs) with the Ziyuan 3 (ZY-3) stereoscopic DEM and ground control points (GCPs). To date, the horizontal error of these DEMs has received little attention in accuracy assessments. Using the ZY-3 DEM as reference, this study examines (1) the horizontal offset between the three DEMs and the reference DEM using the normalised cross-correlation method, (2) the vertical accuracy of those DEMs using kinematic GPS data and (3) the relationship between the three DEMs and the reference ZY-3 DEM. The results show that the SRTM and DLR-SRTM have greater vertical accuracy after applying horizontal offset correction, whereas the vertical accuracy of the ASTER GDEM is less than the other two DEMs. These methods and results can be useful for researchers who use DEMs for various applications.     

ICESat激光高程点辅助的天绘一号卫星影像立体区域网平差

无地面控制点（简称无控）区域网平差是实现卫星影像无控测图的一项重要技术,对于境外和外业测控困难区域的测图具有重要意义。然而,无控区域网平差的定位精度一般难以满足对应比例尺测图规范要求。利用公开、可稳定获取的公众地理信息数据辅助区域网平差,是提高卫星影像无控定位精度的有效途径,其中ICESat激光高程点便是一种良好的高程控制数据。为了提高天绘一号卫星影像无控定位精度,本文提出ICESat激光高程点辅助的卫星影像模型法立体区域网平差方法。首先,以30 m分辨率SRTM估算的地形坡度作为限制条件,结合激光高程点自身质量评价信息,自动提取高质量ICESat激光高程点;其次,利用自动匹配的连接点进行模型法自由网平差,实现卫星影像几何定位精度的相对一致性（内部一致性）;最后,将激光高程点自动量测至卫星影像作为控制点,其平面坐标根据自由网平差结果前方交会计算而得,高程坐标取自激光点高程,再次进行区域网平差精化定向参数,提高卫星影像的绝对高程精度。最后本文利用山东全省的天绘一号卫星影像进行试验,验证了本文方法的有效性和可行性。     

Digital Geologic Mapping of the Ferron Sandstone, Muddy Creek, Utah, with GPS and Reflectorless Laser Rangefinders

The traditional approach to geologic mapping consists of sketching, taking orientation and thickness measurements with compass and tape, and noting positions of features on topographic maps or photos. These methods are time consuming, often difficult to realize in rough terrain, and poorly constrain lateral variations in sedimentary facies in relatively flat lying strata. We describe a case study that captures the three-dimensional architecture of sandstone bodies and key geological surfaces such as stratigraphic boundaries and faults using digital capture techniques. The Ferron sandstone in Utah is a superbly exposed ancient delta deposit that provides an improtant outcrop analog to fluvio-deltaic subsurface reservoirs. It has been the focus of many traditional outcrop studies, but here we use a methodology (“cybermapping”) based on GPS with offsets from a continuous ranging mode reflectorless laser rangefinder (“laser sketch”) for collection and analysis of basic stratigraphic and structural data in a relatively remote area. We also show hos this data can be analyzed and visualized in three dimensions. The study area was mapped in two days, which included hiking several kilometers into the area. One-the-fly and rapid static post processing of GPS surveying was used for positioning the reflectorness laser rangefinders; 60,000 points were acquired mapping sedimentological and structural features, terrain, and control points. The resultant quantitative 3D model of the geology and terrain allowed robust geometric visualization and analyses. ? 2001 John Wiley & Sons, Inc.     

TERRA: Terrain Extraction from elevation Rasters through Repetitive Anisotropic filtering

Over the past decades, several filters have been developed to derive a Digital Terrain Model (DTM) from a Digital Surface Model (DSM), by means of filtering out aboveground objects such as vegetation. In this filtering process, however, one of the major challenges remains to precisely distinguish sharp terrain features, e.g. ridges, agricultural terraces or other anthropogenic geomorphology such as open-pit mines, riverbanks or road ramps. Hence, loss of elevation data around terrain edges (and consequent smoothing) is very common with existing algorithms. In terraced landscapes, the preservation of precise geomorphology is of key importance in digital terrain analyses, such as hydrologic and erosion modelling, or automatic feature recognition and inventorying. In this work, we propose a new filtering method called TERRA (Terrain Extraction from elevation Rasters through Repetitive Anisotropic filtering). The novelty of the algorithm lies within its usage of terrain aspect to guide the anisotropic filtering direction, therefore maximising the preservation of terrain edges. We derived six DTMs from DSMs using UAV Structure from Motion (SfM) photogrammetry, laser altimetry and satellite sources (grid resolutions ranging from 0.1–1.0 m). The results indicated a close agreement of DTMs filtered using the TERRA algorithm and reference DTMs, while terrace risers were well preserved even under thick canopies of vines and trees. Compared to existing filtering approaches, TERRA performed well in minimising Type I errors (false ground removal), while Type II errors occurred locally where vegetation was covering the terrace edges. Given the promising filtering performance, and supported by the minimal requirements of parameterisation and computation, the TERRA algorithm could be a useful tool in DTM preparation for digital terrain analysis of agricultural terraces and similar hillslopes characterised by a complex mosaic of sharp terrain and non-terrain features.     

How does co-registration affect geomorphic change estimates in multi-temporal surveys?

ABSTRACT

High-Resolution Topography (HRT) data sets are becoming increasingly available, improving our ability and opportunities to monitor geomorphic changes through multi-temporal Digital Terrain Models (DTMs). The use of repeated topographic surveys enables inferring the sediment dynamics of hazardous geomorphic processes such as floods, debris flows, and landslides, and allows us to derive important information on the risks often associated with these processes. The topographic surveying platforms, georeferencing systems, and processing tools have seen important developments in the last two decades, in particular Light Detection And Ranging (LiDAR) technology used in Airborne Laser Scanning (ALS) and Terrestrial Laser Scanning (TLS). Moreover, HRT data, produced through these techniques, changed a lot in terms of point cloud density, accuracy and precision over time. Therefore, old “legacy” data sets and recent surveys can often show comparison problems, especially when multi-temporal data are not homogeneous in terms of quality and uncertainties. In this context, data co-registration should be used to guarantee the coherence among multi-temporal surveys, minimizing, on stable areas, the distance between corresponding points acquired at different epochs. Although several studies highlight that this process is fundamental to properly compare multi-temporal DTMs, it is often not addressed in LiDAR post-processing workflows. In this paper we focus on the alignment of multi-temporal surveys in a topographically complex and rugged environment as the Moscardo debris-flow catchment (Eastern Italian Alps), testing various co-registration methods to align multi-temporal ALS point clouds (i.e. years 2003, 2009 and 2013) and the derived DTMs. In particular, we tested the pairwise registration with manual correspondences, the Iterative Closest Point (ICP) algorithm and a mathematical model that allows aligning simultaneously a generic number of point clouds, the so-called Generalized Procrustes Analysis (GPA), also in its GPA-ICP variant. Then, to correct the possible small inaccuracies generated from the gridding interpolation process, a custom-developed DTM co-registration tool (GRD-CoReg) was used to align gridded data. Both alignment phases (i.e. at point cloud and DTM level) proved to be fundamental and allowed us to obtain proper and reliable DTMs of Difference (DoDs), useful to quantify the debris mobilized and to detect the spatial and temporal patterns of catchment-scale erosion and deposition. The consistency of DoDs data was verified through the comparison between the erosion estimate of DoDs and the volumes of debris-flow events measured by the monitoring station close to the Moscardo torrent catchment outlet. The GPA-ICP algorithm followed by the GRD-CoReg tool proved to be the most effective solution for improving DoDs results with a decrease of systematic trend due to vertical and horizontal uncertainties between surveys, especially at steep slopes. The net volume difference (i.e. the sediment output from the catchment) of the 2003–2013 period changed from 3,237,896 m³ to 135,902 m³ in DoDs obtained from not co-registered and co-registered DTMs. The volume of debris flows measured at the catchment outlet during the same time interval amounts to 169,660 m³. The comparison with debris-flow volume measures at the monitoring station shows, therefore, that the DTMs obtained from the co-registration processes generate more reliable DoDs than those obtained from the raw DTMs (without the alignment).     

DTM法土方量计算的工区边缘高程点选取问题与精度分析

DTM法土方量计算是工程施工中较为常用的一种方法,选取不同的高程点将获得不同的DTM,进而会影响到工区内土方量计算的精度。本文对不同工区的多种高程点选取方式进行了实验及分析,从中总结了一种较为有效的并兼顾精度的工区边缘高程点选取方法。     

SPOT卫星影象严密数字几何校正的直接法

由于SPOT卫星影象的行中心投影成象方式和外方位元素时序变化特点,在实施严密数字几何校正的过程中,直接法的应用显示了很大的优越性。为此,本文提出了应用直接法的原理和方法,指出了技术关键和确保锚点坐标解算精度和可靠性的方法。由于直接法可较精确地确定锚点所在行的外方位元素,不需要迭代计算,因而不仅计算速度快,而且从实验结果包括锚点坐标计算精度,锚点网格内插精度估计和几何校正结果之正射影象精度的分析都表明直接法优于间接法,证实了所提出的原理方法的合理性和正确性。     

最邻近曲面约束的近景光学影像与地面激光点云几何配准

提出一种以最邻近曲面为约束的近景光学影像与地面激光点云高精度配准方法。根据光学影像生成三维稀疏点云,以影像三维稀疏点邻近的激光点拟合的曲面为约束,结合共线条件方程建立影像三维稀疏点云与三维激光点云间变换模型,通过平差迭代解算实现光学影像与激光点云的高精度几何配准。该方法只需提供初始配准参数,无需对激光点云数据进行特征提取和分割,并且基于曲面约束有效地解决了两个点集之间难以精确确定同名点的问题。通过实际数据试验表明该方法能获得很好的配准精度。     

三维激光扫描数据获取高分辨率DTM试验研究

三维激光扫描技术能够提供实体表面点云数据,可用于获取高精度高分辨率数字地形模型。本文以重庆万州区付家岩滑坡体为例探讨了采用三维激光扫描监测技术获取数字地形模型的方法,着重讨论了相关点云数据处理流程和关键技术问题。通过结合差分GPS技术进行激光数据的相对定位和绝对定位、去噪、拼接等方法,获得了该区域地表高精度地形数据,并生成了相应的数字高程模型。试验结果初步说明该技术可用于获取小尺度高精度高分辨率数字地形模型,具有一定的应用前景。     

低空UAV激光点云和序列影像的自动配准方法

提出了一种低空无人机(unmanned aerial vehicle,UAV)序列影像与激光点云自动配准的方法。首先分别基于多标记点过程与局部显著区域检测对激光点云和序列影像的建筑物顶部轮廓进行提取,并依据反投影临近性匹配提取的顶面特征。然后利用匹配的建筑物角点对,线性解算序列影像外方位元素,再使用建筑物边线对的共面条件进行条件平差获得优化解。最后,为消除错误提取与匹配特征对整体配准结果的影响,使用多视立体密集匹配点集与激光点集进行带相对运动阈值约束的ICP(迭代最临近点)计算,整体优化序列影像外方位元素解。试验结果表明本文方法能实现低空序列影像与激光点云像素级精度的自动配准,联合制作DOM精度满足现行无人机产品1∶500比例尺标准。