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.     

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.     

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.     

数字高程模型内插方法的可视化对比研究

在生产或生活中应用数字高程模型内插时,最关键的问题就是怎样选取恰当的内插方法来满足高程数据建模的需求。不同的DEM内插方法随地貌地区和采样点方式的不同存在不同的误差。本文使用V isual Basic语言将数字高程模型内插方法编写成一套能够快捷方便的获取内插点高程的内插软件系统,可以使应用人员直接捕捉地面点高程,并获得地形的可视化信息,由此可以直观地观察到在同一地区相同采样点方式的条件下采用不同的内插方法引起的内插精度等质量方面的优劣区别,从而获取最优的内插方法,有效地满足DEM的生产、质量控制、精度评定和分析应用等各个环节。     

Efficient Priority-Flood depression filling in raster digital elevation models

Depressions in raster digital elevation models (DEM) present a challenge for extracting hydrological networks. They are commonly filled before subsequent algorithms are further applied. Among existing algorithms for filling depressions, the Priority-Flood algorithm runs the fastest. In this study, we propose an improved variant over the fastest existing sequential variant of the Priority-Flood algorithm for filling depressions in floating-point DEMs. The proposed variant introduces a series of improvements and greatly reduces the number of cells that need to be processed by the priority queue (PQ), the key data structure used in the algorithm. The proposed variant is evaluated based on statistics from 30 experiments. On average, our proposed variant reduces the number of cells processed by the PQ by around 70%. The speed-up ratios of our proposed variant over the existing fastest variant of the Priority-Flood algorithm range from 31% to 52%, with an average of 45%. The proposed variant can be used to fill depressions in large DEMs in much less time and in the parallel implementation of the Priority-Flood algorithm to further reduce the running time for processing huge DEMs that cannot be dealt with easily on single computers.     

GeoEye-1影像制作数字正射影像图的精度评定

GeoEye-1卫星传感器采用三线阵CCD扫描传感器,拥有空间分辨率高、单景影像地面成像面积大等诸多优点.本文以澳大利亚霍巴特市作为实验区,在ERDAS LPS平台下,结合国家航测规范,试验研究了不同地形和GCPs条件下应用GeoEye-1影像制作DOM的精度及误差分布情况.通过试验我们对应用GeoEye-1影像制作D...     

基于MapGIS的DEM质量检查与精度评定

介绍了DEM的NSDTF-DEM格式及Arc GIS明码Grid格式,后者的DEM格式应用更广泛并支持更多的GIS软件对其进行读取及处理,故本文通过自编程序实现了前者到后者的转换。     

DEM内插算法与精度评定研究

本文分析了DEM数据产品的误差源、内插算法的误差模型,简要介绍了目前DEM数据产品精度评定的指标与方法途径.通过介绍DEM引出了数字高程模型内插方法,比较了各种DEM内插方法,并且分析了模型精度.     

A total error-based multiquadric method for surface modeling of digital elevation models

Digital elevation model (DEM) source data are subject to both horizontal and vertical errors owing to improper instrument operation, physical limitations of sensors, and bad weather conditions. These factors may bring a negative effect on some DEM-based applications requiring low levels of positional errors. Although classical smoothing interpolation methods have the ability to handle vertical errors, they are prone to omit horizontal errors. Based on the statistical concept of the total least squares method, a total error-based multiquadric (MQ-T) method is proposed in this paper to reduce the effects of both horizontal and vertical errors in the context of DEM construction. In nature, the classical multiquadric (MQ) method is a vertical error regression procedure, whereas MQ-T is an orthogonal error regression model. Two examples, including a numerical test and a real-world example, are employed in a comparative performance analysis of MQ-T for surface modeling of DEMs. The numerical test indicates that MQ-T performs better than the classical MQ in terms of root mean square error. The real-world example of DEM construction with sample points derived from a total station instrument demonstrates that regardless of the sample interval and DEM resolution, MQ-T is more accurate than classical interpolation methods including inverse distance weighting, ordinary kriging, and Australian National University DEM. Therefore, MQ-T can be considered as an alternative interpolator for surface modeling with sample points subject to both horizontal and vertical errors.     

Levee crest elevation profiles derived from airborne lidar-based high resolution digital elevation models in south Louisiana

This study explores the feasibility of using airborne lidar surveys to construct high-resolution digital elevation models (DEMs) and develop an automated procedure to extract levee longitudinal elevation profiles for both federal levees in Atchafalaya Basin and local levees in Lafourche Parish, south Lousiana. This approach can successfully accommodate a high degree of levee sinuosity and abrupt changes in levee orientation (direction) in planar coordinates, variations in levee geometries, and differing DEM resolutions. The federal levees investigated in Atchafalaya Basin have crest elevations between 5.3 and 12 m while the local counterparts in Lafourche Parish are between 0.76 and 2.3 m. The vertical uncertainty in the elevation data is considered when assessing federal crest elevation against the U.S. Army Corps of Engineers minimum height requirements to withstand the 100-year flood. Only approximately 5% of the crest points of the two federal levees investigated in the Atchafalaya Basin region met this requirement.     

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.     

Evaluation of NDWI and MNDWI for assessment of waterlogging by integrating digital elevation model and groundwater level

Accurate information on the extent of waterlogging is required for flood prediction, monitoring, relief and preventive measures. The rule-based classification algorithms were used for differentiating waterlogged areas from other ground features using Resourcesat-2 AWiFS satellite imagery (Indian Remote Sensing Satellite with spatial resolution of 56 m). Two spectral indices normalized difference water index (NDWI) and modified normalized difference water index (MNDWI) were used for extracting waterlogged areas in Sri Muktsar Sahib district of Punjab, India. These indices extracted the waterlogged areas (cropped areas inundated with water) but the water features were less enhanced in the NDWI-derived image (when compared with MNDWI-derived image) due to negative values of NDWI and, mixing of water with built up features. The water features were more enhanced with MNDWI and the values of MNDWI were positive for water features mixed with vegetation. The overall accuracy of waterlogged areas extracted from the MNDWI image was 96.9% with the Kappa coefficient of 0.89. The digital elevation model (DEM) was extracted from ASTER-GDEM. The relationships among depth to the water table recorded before the incessant rain in the region, DEM and classified MNDWI images explained the differences in the extent of waterlogging in various directions of the study area. These results suggest that MNDWI can be used to better delineate water features mixed with vegetation compared to NDWI.     

基于DEM的新疆地势起伏度分析

地势起伏度的提取为获取地表信息、进行地形定量化分析提供有效手段。本研究以新疆1:25万DEM数据为基础,并借鉴前人研究方法,在GIS系统的支持下,利用邻域分析方法,运用均值变点分析法对其进行了最佳统计单元的计算,最后得出基于1:25万DEM的新疆地势起伏度计算的最佳统计单元为8×8的网格大小(2.56km2),并完成了新疆地势起伏度分级图的绘制,通过分级图认真分析新疆基本地貌特征(戈壁、沙漠、丘陵、高山等),从地势上看,新疆地势局部起伏较大,总体较平缓。     

Accuracy assessment of QuickBird stereo imagery

The Geographical Survey Institute of Japan has recently carried out an evaluation of the metric performance of QuickBird stereo satellite imagery. This paper describes the accuracy assessment of the sensor orientation and geopositioning phases of the study, the aim of which was twofold. First, it was desired to confirm the metric potential of QuickBird imagery for 1:25 000 scale topographic mapping. Second, a determination was to be made of the accuracy attainable from the Basic image product. The techniques of rational functions and affine bundle adjustment were employed, the former with bias compensation. The results obtained both reassert the high precision of the rational functions approach and cast doubt upon the applicability of the 3D affine model for accurate geopositioning from QuickBird imagery.     

A novel method for automating the checking and correction of digital elevation models using orthophotographs

This article presents a complete mathematical model, which translates discrepancies between two orthophotographs created from different photographs, into precise corrections of the Digital Elevation Model (DEM). These corrections are the differences from the real surface and, if applied over the existing DEM, can produce a more accurate one. The mathematical model is straightforward, and is not approximate, and therefore there is no need for iterations.
Possible applications include checking of automatically created DEMs, refinement of existing DEMs using aerial photographs and update of orthophotographs based on the previous DEM and new imagery.     

Galileo IOV卫星广播星历精度评估

介绍广播星历精度评估的基本原理与方法,在此基础上利用长达两年的广播星历数据分析比较Galileo现有IOV卫星的广播轨道精度、钟差精度以及整体精度SISRE的长期和短期变化趋势,结果表明,目前Galileo IOV卫星径向轨道精度优于0.5m,切向精度优于1.8m,法向精度优于1.5m,略优于切向,钟差精度优于5ns,SISRE优于1.3m。从星历精度的长期变化趋势来看,Galileo广播星历精度随系统发展有一定的改善。     

Evaluation of digital elevation models for delineation of hydrological response units in a Himalayan watershed

This study reports results from evaluation of the quality of digital elevation model (DEM) from four sources viz. topographic map (1:50,000), Shuttle Radar Topographic Mission (SRTM) (90 m), optical stereo pair from ASTER (15 m) and CARTOSAT (2.5 m) and their use in derivation of hydrological response units (HRUs) in Sitla Rao watershed (North India). The HRUs were derived using water storage capacity and slope to produce surface runoff zones. The DEMs were evaluated on elevation accuracy and representation of morphometric features. The DEM derived from optical stereo pairs (ASTER and CARTOSAT) provided higher vertical accuracies than the SRTM and topographic map-based DEM. The SRTM with a coarse resolution of 90 m provided vertical accuracy but better morphometry compared to topographic map. The HRU maps derived from the fine resolution DEM (ASTER and CARTOSAT) were more detailed but did not provide much advantage for hydrological studies at the scale of Sitla Rao watershed (5800 ha).     

Facets of uncertainty in digital elevation and slope modeling

IntroductionWith sophistication of information technologysuch as global positioning system and remotesensing,anincreasing quantity of digital terraindata is produced fromvarious sources ,contribu-tingto accurate mapping and dynamic monitoringof the natural and built landscapes[1-3]. The val-ue of spatial information, however , dependsheavily on a good understanding and proper han-dling of uncertainty , which occurs due to the in-ability of any information systems to representthe real world as …