基于规则格网DEM的地形特征提取算法

提出并实现了一种基于规则格网DEM的地形特征线提取算法,该算法在现有地表水流模拟方法的基础上将矢量操作与栅格操作结合起来对规则格网DEM中的洼地进行填平处理,采用邻域格网分组扫描方法确定平地水流方向,与以往算法相比在提取效率和结果准确性等方面都有了明显的改进,从而也使其更加适合于对大规模的DEM数据进行处理,采用各种尺度的DEM进行试验的结果验证了以上结论.     

Evaluation of vertical accuracy of open source Digital Elevation Model (DEM)

Digital Elevation Model (DEM) is a quantitative representation of terrain and is important for Earth science and hydrological applications. DEM can be generated using photogrammetry, interferometry, ground and laser surveying and other techniques. Some of the DEMs such as ASTER, SRTM, and GTOPO 30 are freely available open source products. Each DEM contains intrinsic errors due to primary data acquisition technology and processing methodology in relation with a particular terrain and land cover type. The accuracy of these datasets is often unknown and is non-uniform within each dataset. In this study we evaluate open source DEMs (ASTER and SRTM) and their derived attributes using high postings Cartosat DEM and Survey of India (SOI) height information. It was found that representation of terrain characteristics is affected in the coarse postings DEM. The overall vertical accuracy shows RMS error of 12.62 m and 17.76 m for ASTER and SRTM DEM respectively, when compared with Cartosat DEM. The slope and drainage network delineation are also violated. The terrain morphology strongly influences the DEM accuracy. These results can be highly useful for researchers using such products in various modeling exercises.     

Effect of Contour Intervals and Grid Cell Size on the Accuracy of DEMs and Slope Derivatives

Digital Elevation Models (DEMs) are indispensable tools in many environmental and natural resource applications. DEMs are frequently derived from contour lines. The accuracy of such DEMs depends on different factors. This research investigates the effect of sampling density used to derive contours, vertical interval between contours (spacing), grid cell size of the DEM (resolution), terrain complexity, and spatial filtering on the accuracy of the DEM and the slope derivative. The study indicated different alternatives to achieve an acceptable accuracy depending on the contour interval, the DEM resolution and the complexity of the terrain. The effect of these factors on the accuracy of the DEM and the slope derivative was quantified using models that determine the level of accuracy (RMSE). The implementation of the models will guide users to select the best combination to improve the results in areas with similar topography. For areas with variable terrain complexity, the suggestion is to generate DEMs and slope at a suitable resolution for each terrain separately and then to merge the results to produce one final layer for the whole area. This will provide accurate estimates of elevation and slope, and subsequently improve the analyses that rely on these digital derivatives.     

Vertical accuracy evaluation of freely available latest high-resolution (30 m) global digital elevation models over Cameroon (Central Africa) with GPS/leveling ground control points.

Digital Elevation Models (DEMs) contain topographic relief data that are vital for many geoscience applications. This study relies on the vertical accuracy of publicly available latest high-resolution (30?m) global DEMs over Cameroon. These models are (1) the ALOS World 3D-30?m (AW3D30), (2) the Shuttle Radar Topography Mission 1 Arc-Second C-Band Global DEM (SRTM 1) and (3) the Advanced Spaceborne Thermal Emission and Reflection Global DEM Version 2 (ASTER GDEM 2). After matching their coordinate systems and datums, the horizontal positional accuracy evaluation was carried out and it shows that geolocation errors significantly influence the vertical accuracy of global DEMs. After this, the three models are compared among them, in order to access random and systematic effects in the elevation data each of them contains. Further, heights from 555 GPS/leveling points distributed all over Cameroon are compared to each DEM, for their vertical accuracy determination. Traditional and robust statistical measures, normality test, outlier detection and removal were used to describe the vertical quality of the DEMs. The test of the normality rejected the hypothesis of normal distribution for all tested global DEMs. Overall vertical accuracies obtained for the three models after georeferencing and gross error removal in terms of Root Mean Square (RMS) and Normalized Median Absolute Deviation (NMAD) are: AW3D30 (13.06?m and 7.75?m), SRTM 1 (13.25?m and 7.41?m) and ASTER GDEM 2 (18.87?m and 13.30?m). Other accuracy measures (MED, 68.3% quantile, 95% quantile) supply some evidence of the good quality of AW3D30 over Cameroon. Further, the effect of land cover and slope on DEM vertical accuracy was also analyzed. All models have proved to be worse in the areas dominated by forests and shrubs areas. SRTM 1 and AW3D30 are more resilient to the effects of the scattering objects respectively in forests and cultivated areas. The dependency of DEMs accuracy on the terrain roughness is evident. In all slope intervals, AW3D30 is performing better than SRTM 1 and ASTER GDEM 2 over Cameroon. AW3D30 is more representative of the external topography over Cameroon in comparison with two others datasets and SRTM 1 can be a serious alternative to AW3D30 for a range of DEM applications in Cameroon.     

Satellite derived digital elevation model and terrain parameters — generation,accuracy assessment and validation

Digital Elevation Models (DEMs) and their derivatives are routinely exploited for a wide range of planning and engineering applications such as land reclamation, calculation of cut-and-fill requirements for earth works or to determine other relevant geomorphological landscape parameters. The advent of computer (digital) manipulation of elevation data has opened up great possibilities for studying the geometry of our land surface in relation to physical factors such as climate, vegetation, soils and geology. This paper is concerned with the generation, testing and validation of DEM and its derived terrain parameters viz., contours, drainage pattern etc. using IRS-1C stereo pair over a part of Alwar district, Rajasthan, India. In particular, it reports on the results achieved using indigenously developed stereo - processing software along with standard GIS and terrain analysis package to derive DEM and associated terrain parameters of the study area. The results are encouraging when compared with Survey of India topographical maps at 1:50,000 scale in terms of point to point accuracy of DEM, data quality evaluation of orthoimage and higher order drainage delineation.     

Accuracy assessment of airborne photogrammetrically derived high-resolution digital elevation models in a high mountain environment

High-resolution digital elevation models (DEMs) generated by airborne remote sensing are frequently used to analyze landform structures (monotemporal) and geomorphological processes (multitemporal) in remote areas or areas of extreme terrain. In order to assess and quantify such structures and processes it is necessary to know the absolute accuracy of the available DEMs. This study assesses the absolute vertical accuracy of DEMs generated by the High Resolution Stereo Camera-Airborne (HRSC-A), the Leica Airborne Digital Sensors 40/80 (ADS40 and ADS80) and the analogue camera system RC30. The study area is located in the Turtmann valley, Valais, Switzerland, a glacially and periglacially formed hanging valley stretching from 2400 m to 3300 m a.s.l. The photogrammetrically derived DEMs are evaluated against geodetic field measurements and an airborne laser scan (ALS). Traditional and robust global and local accuracy measurements are used to describe the vertical quality of the DEMs, which show a non Gaussian distribution of errors. The results show that all four sensor systems produce DEMs with similar accuracy despite their different setups and generations. The ADS40 and ADS80 (both with a ground sampling distance of 0.50 m) generate the most accurate DEMs in complex high mountain areas with a RMSE of 0.8 m and NMAD of 0.6 m They also show the highest accuracy relating to flying height (0.14‰). The pushbroom scanning system HRSC-A produces a RMSE of 1.03 m and a NMAD of 0.83 m (0.21‰ accuracy of the flying height and 10 times the ground sampling distance). The analogue camera system RC30 produces DEMs with a vertical accuracy of 1.30 m RMSE and 0.83 m NMAD (0.17‰ accuracy of the flying height and two times the ground sampling distance). It is also shown that the performance of the DEMs strongly depends on the inclination of the terrain. The RMSE of areas up to an inclination <40° is better than 1 m. In more inclined areas the error and outlier occurrence increase for all DEMs. This study shows the level of detail to which airborne stereoscopically derived DEMs can reliably be used in high mountain environments. All four sensor systems perform similarly in flat terrain.     

High Resolution DEM Generation in High‐Alpine Terrain Using Airborne Remote Sensing Techniques

Up‐to‐date and accurate digital elevation models (DEMs) are essential for many applications such as numerical modeling of mass movements or mapping of terrain changes. Today the Federal Department of Topography, swisstopo, provides Digital Terrain Models (DTMs) and Digital Surface Models (DSMs) derived from airborne LiDAR data with a high spatial resolution of 2 m covering the entire area of Switzerland below an elevation of 2000 m a.s.l.. However, above an elevation of 2000 m a.s.l., which is typical for high‐alpine terrain, the best product available is the a DTM with a spatial resolution of 25 m. This spatial resolution is insufficient for many applications in complex terrain. In this study, we investigate the quality of DSMs derived from opto‐electronic scanner data (ADS80; acquired in autumn 2010) using photogrammetric image correlation techniques based on the multispectral nadir and backward looking sensor data. As reference, we take a high precision airborne LiDAR data set with a spatial resolution of ca. 0.5 m, acquired in late summer 2010, covering the Grabengufer/Dorfbach catchment near Randa, VS. We find the deviations between the two datasets are surprisingly low. In terrain with inclination angles of less than 30° the RMSE is below 0.5 m. In extremely steep terrain of more than 50° the RMSE goes up to 2 m and outliers increase significantly. We also find dependencies of the deviations on illumination conditions and ground cover classes. Finally we discuss advantages and disadvantages of the different data acquisition methods.     

Uncertainty analysis of soil erosion modelling using different resolution of open-source DEMs

The Digital Elevation Model (DEM) is one of the important parameters of soil erosion assessment and notable uncertainties are found in using different resolutions of the DEM. Revised Universal Soil Loss Equation model has been applied to analyze the effect of open-source DEMs with different resolution and accuracy on the uncertainties of soil erosion modelling in a part of the Narmada river basin in Madhya Pradesh in central India. Selected open-source DEMs are GTOPO30 (1 km), SRTM (30 and 90 m), CARTOSAT (30 m) and ASTER (30 m), used for estimating erosion rate. Results with better accuracy are achieved with the high-resolution DEMs (30 m) with higher vertical accuracy than the coarse resolution DEMs with lower accuracy. This study has presented potential uncertainties introduced by the open-source DEMs in soil erosion modelling for better understanding of appropriate selection and acceptable errors for researchers.     

基于星载激光雷达和雷达高度计数据的南极冰盖表面高程制图

南极数字高程模型DEMs(Digital Elevation Models)是研究极区大气环流模式,南极冰盖动态变化和南极科学考察非常重要的基础数据。目前,科学家已经发布了五种不同的南极数字表面高程模型。这些数据都是由卫星雷达高度计,激光雷达和部分地面实测数据等制作而成。尽管如此,由于海洋与冰盖交接的南极冰盖边缘区随时间的快速变化,有必要根据新的卫星数据及时更新南极冰盖表面高程数据。因此,我们利用雷达高度计数据(Envisat RA-2)和激光雷达数据(ICESat/GLAS)制作了最新的南极冰盖高程数据。为提高ICESat/GLAS数据的精度,本文采用了五种不同的质量控制指标对GLAS数据进行处理,滤除了8.36%的不合格数据。这五种质量控制指标分别针对卫星定位误差、大气前向散射、饱和度及云的影响。同时,对Envisat RA-2数据进行干湿对流层纠正、电离层纠正、固体潮汐纠正和极潮纠正。针对两种不同的测高数据,提出了一种基于Envisat RA-2和GLAS数据光斑脚印几何相交的高程相对纠正方法,即通过分析GLAS脚印点与Envisat RA-2数据中心点重叠的点对,建立这些相交点对的高度差(GLAS-RA-2)与表征地形起伏的粗糙度之间的相关关系,对具有稳定相关关系的点对进行Envisat RA-2数据的相对纠正。通过分析南极冰盖不同区域的测高点密度,确定最终DEM的分辨率为1000 m。考虑到南极普里兹湾和内陆地区的差异性,将南极冰盖分为16个区,利用半方差分析确定最佳插值模型和参数,采用克吕金插值方法生成了1000 m分辨率的南极冰盖高程数据。利用两种机载激光雷达数据和我国多次南极科考实测的GPS数据对新的南极DEM进行了验证。结果显示,新的DEM与实测数据的差值范围为3.21—27.84 m,其误差分布与坡度密切关系。与国际上发布的南极DEM数据相比,新的DEM在坡度较大地区和快速变化的冰盖边缘地区精度有较大改进。     

从规则格网DEM自动提取汇水区域及其子区域的方法

从DEM自动提取的汇水区域及其子区域信息对进一步的水文分析有着重要的辅助作用.在经过洼地处理的DEM及得到水流方向矩阵的基础上,本文提出并实现了一种汇水区域及其子区域的提取算法.该算法首先提取整个DEM区域内每条河流的汇水区域,然后按照不同的要求划分子区域.经过试验,与现有的方法相比,该算法在提取效率和结果准确性方面都有明显提高.     

Advanced analysis of differences between C and X bands using SRTM data for mountainous topography

By Interferometric Synthectic Aperture Radar (InSAR), during the Shuttle Radar Topography Mission (SRTM) height models have been generated, covering the earth surface from 56° south to 60.25° north. With the exception of small gaps in steep parts, dry sand deserts and water surfaces, the free available US C-band data cover the earth surface from 56° south to 60.25° north completely while the X-band data, distributed by the DLR (German Aerospace Center), cover it only partially. The C-band and X-band radar cannot penetrate the vegetation because of the short wavelength. Therefore, the height models are not Digital Elevation Models (DEM) representing bare Earth surface without any details, they are Digital Surface Models (DSM) representing the visible surface including vegetation and buildings. In the area of Zonguldak, Turkey, C-band and X-band DSMs are available and have been analysed in cooperation between Zonguldak Karaelmas University (ZKU) and Leibniz University of Hannover. The digitized contour lines from the 1:25,000 scale topographic maps and also a more precise height model derived directly from large scale photogrammetric mapping are used as reference height models. The terrain inclination influences the accuracy strongly, but also the directions of the inclination in relation to the radar view direction, the aspects, are important. Independent from the aspects, the analysed results do have root mean square differences against the reference data fitting very well to the Koppe formula SZ=a+b*tan α. The analyses are made separately for open and forest areas, with clear accuracy differences between both. Also, the analysis of X-band separately for three sub-areas is done and the positive effect of double observation to the accuracy has been clearly determined. The C-band data are only available with a spacing of 3 arcsec, corresponding to 92m × 70m, while the X-band data do have a spacing of 1 arcsec. This is important for the interpolation in the mountainous test area. The accuracy of the height points is approximately the same for the C- and the X-band data. But the C-band data which have three times larger spacing than Xband data, do not include the same morphological information. While C-band data contain very generalised contour lines X-band data have quite more details depending on 1 arcsec point spacing. The differential DEMs have been generated, separately, for displaying the differences between SRTM height models and reference DEMs of the test field.     

多源点云数据融合的建筑物精细化建模

三维建模技术能够实现建筑物的数字化存档，在古建筑保护与修复和现代建筑规划与改造中具有不可替代的作用。针对倾斜摄影测量和三维激光扫描建模技术中建筑物模型存在的问题，本文提出了一种倾斜摄影测量和三维激光扫描生成三维点云模型相融合的建筑物精细化建模方法。选用无人机和三维激光扫描仪作为试验设备，利用ContextCapture、SCENE软件完成点云拼接、生产和编辑，通过ICP算法完成点云精细匹配，实现多源点云数据融合建模；对比单一建模方法模型，从纹理结构和模型精度两方面对融合建模模型进行质量评价。结果表明，融合建模模型纹理清晰，几何结构完整，模型距离中误差和高差中误差的均值均低于倾斜摄影测量模型的值，接近三维激光扫描模型。     

Digital Elevation Models By Laser Scanning

The TopoSys laser scanner system is designed to produce digital elevation models (DEMs) at a maximum accuracy of 0.5 m in x and y and 0.1 m in z. The regular scan pattern and the measurement frequency of 80 000 measurements per second (on average 5 measurements per m2) form the basis for high quality DEMs.
The mainly automated data processing makes it possible to generate DEMs of large areas in a short production time. The DEMs produced come into common use as basic data for different applications, some of which are water resources management, shoreline control, planning of utility lines and urban planning (simulation of noise and pollution distributions). The performance of the system is illustrated with the help of DEM sections produced with the TopoSys system.     

激光扫描技术在土方量计算中的应用及精度分析

土方量计算的方法有方格网法、断面法、等高线法、数字高程模型(DEM)方法等,本文提出一种利用激光扫描获取海量数据生成不规则三角网(TIN)来计算土方量的方法,介绍其作业方法、地形数据提取、土方量计算等。在实际工程中,用不同方法计算出来的土方量会存在差别,哪种计算方法的精度更高,通过精度分析得出相应结论。     

Vertical accuracy assessment of freely available digital elevation models over low-lying coastal plains

The frequency of coastal flood damages is expected to increase significantly during the twenty-first century as sea level rises in the coastal floodplain. Coastal digital elevation model (DEM) data describing coastal topography are essential for assessing future flood-related damages and understanding the impacts of sea-level rise. The Shuttle Radar Topography Mission (SRTM) and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) are currently the most accurate and freely available DEM data. However, an accuracy assessment specifically targeted at DEMs over low elevation coastal plains is lacking. The present study focuses on these areas to assess the vertical accuracy of SRTM and ASTER GDEM using Ice, Cloud, and land Elevation Satellite, Geoscience Laser Altimeter System (ICESat/GLAS) and Real Time Kinematic (RTK) Global Positioning System (GPS) field survey data. The findings show that DEM accuracy is much better than the mission specifications over coastal plains. In addition, optical remote sensing image analysis further reveals the relationship between DEM vertical accuracy and land cover in these areas. This study provides a systematic approach to assess the accuracy of DEMs in coastal zones, and the results highlight the limitations and potential of these DEMs in coastal applications.     

Measuring the accuracy of contour interpolated digital elevation models

Digital elevation models (DEM) are becoming increasingly important as tools in hydrological research and water resources management. Since error and uncertainty are inherently associated with spatial data, a complete evaluation of a DEM is of utmost importance before it is put into subsequent analysis. The present paper offers an innovative approach for quality assessment of contour interpolated DEMs of different resolutions. Five most frequently cited interpolation methods viz., TIN with linear interpolation, Inverse Distance Weighing, Thin Plate Spline, Ordinary Kriging and TOPOGRID were selected for gridding of contours at five different resolutions i.e., 30m, 45m, 60m, 75m and 90m. In order to compare the quality of interpolated DEMs, a qualitative and quantitative evaluation of inter-polated DEMs for their vertical, horizontal and shape accuracy were carried out. It was found that different interpolation methods produced DEMs with different levels of artifacts. The analyses of vertical accuracy suggested that the variations were not pronounced in nature. However, the quantitative comparisons for horizontal and shape accuracy showed that there was a high level of disparity with significant differences among the interpolated DEMs.     

Laser scanning—surveying and mapping agencies are using a new technique for the derivation of digital terrain models

A user group of the Surveying and Mapping Agencies (SMA) of the Federal States of Germany tested several datasets for the derivation of high-quality Digital Terrain Models (DTM) which were collected by laser scanning. Since the results were very promising, a standard procedure for verification and handling of the data was proposed. Because the ground points that are delivered by the contractor are the result of an automated filtering process, final editing is necessary to correct remaining misclassifications. This can be carried out using photogrammetric stereo models or through comparison of the results with large scale topographic maps. Both approaches lead to a high-quality DTM with much shorter production time and less costs as compared to the photogrammetric methods used up to now.     

A comparison between analytical aerial photogrammetry,laser scanning,total station and global positioning system surveys for generation of digital terrain model

The present paper compares between four data sources for creating digital terrain models (DTMs), based on analytical aerial photogrammetry, laser scanning, total station (TS) and global positioning system surveys. The case study presents the comparative results obtained using the methods listed above. After obtaining the ground coordinates of points using each method, DTMs were created using Surfer Software to establish comparison consistency. To check accuracy of each method used, a series of 100 independent points were collected at random positions over the case study area using the TS for horizontal position and a digital level for elevation. The comparison of the results of the methods was performed based on accuracy and efficiency aspects. The results have shown that TS and terrestrial laser scanners (TLSs) could represent precise, effective and rapid solutions to produce economical and accurate DTMs. Also, using TLSs allow more various possibilities of data representation.     

Artificial Neural Networks as a Method of Spatial Interpolation for Digital Elevation Models

This paper examines the performance of artificial neural networks (ANNs) as a method of spatial interpolation, when presented with irregular and regular samples of elevation data. The results of the ANN interpolation are compared with results obtained by kriging. Tests of spatial bias in the systematic errors contained in each of the neural network-derived DEMs were conducted using four attributes: slope, aspect, average direction and average distance from the nearest sampled value. Based on RMS and other evaluation measures, the accuracy of estimated DEMs from regular and irregular sample distributions using neural networks is lower than the accuracy level derived from kriging. The accuracy level of the ANN interpolators also decreases as the range of elevation values in DEMs increases. As reported in the literature, ANNs are approximate interpolators, and the pattern of under-prediction and over-prediction of elevation values in this study revealed that all estimated values fell within the range of sample elevations. Neural networks cannot predict values outside the range of elevation values contained in the sample, a property shared by other interpolators such as inverse weighted distance.