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.     

A Comparison Between Contour Elevation Data Sources for DEM Creation and Soil Carbon Prediction, Coshocton, Ohio

A raster and vector GIS was created for the North Appalachian Experimental Watershed (NAEW) from legacy (1960) 1:2,400‐scale contour maps. The intent of the study was to use terrain data for the spatial modeling of soil organic carbon. It was hypothesized that DEMs derived from these data would be more accurate and therefore more useful for terrain‐based soil modeling than those from USGS 1:24,000‐scale contour data. Central tasks for this study were to digitally capture the 1:2,400‐scale maps, convert digital contour data sources to raster DEMs at multiple resolutions, and derive terrain attributes. A flexible approach was adopted, using software outside of mainstream GIS sources where scientifically or practically advantageous. Elevation contours and streamlines were converted to raster DEMs using ANUDEM. DEMs ranging in resolution from 0.5–30 m were tested for accuracy against precision carrier‐phase GPS data. The residual standard deviation was 1.68 meters for the USGS DEM and 0.36 meters for the NAEW DEM. The optimal horizontal resolution for the NAEW DEM was 5 m and for the USGS 10 m. Five and 10 m resolution DEMs from both data sources were tested for carbon prediction. Multiple terrain parameters were derived as proxies for surficial processes. Soil samples (n = 184) were collected on four zero‐order watersheds (conventional tillage, no‐till, hay and pasture). Multiple least squares regressions (m.l.s.) were used to predict mass C (kg m^?2, 30 cm depth) from topographic information. Model residuals were not spatially autocorrelated. Statistically significant topographic parameters were attained most consistently from the 5 m NAEW DEM. However, topography was not a strong predictor of carbon for these watersheds, with r² ranging from 0.23 to 0.58.     

Digital Elevation Model from the Best Results of Different Filtering of a LiDAR Point Cloud

The LiDAR point clouds captured with airborne laser scanning provide considerably more information about the terrain surface than most data sources in the past. This rich information is not simply accessed and convertible to a high quality digital elevation model (DEM) surface. The aim of the study is to generate a homogeneous and high quality DEM with the relevant resolution, as a 2.5D surface. The study is focused on extraction of terrain (bare earth) points from a point cloud, using a number of different filtering techniques accessible by selected freeware. The proposed methodology consists of: (1) assessing advantages/disadvantages of different filters across the study area, (2) regionalization of the area according to the most suitable filtering results, (3) data fusion considering differently filtered point clouds and regions, and (4) interpolation with a standard algorithm. The resulting DEM is interpolated from a point cloud fused from partial point clouds which were filtered with multiscale curvature classification (MCC), hierarchical robust interpolation (HRI), and the LAStools filtering. An important advantage of the proposed methodology is that the selected landscape and datasets properties have been more holistically studied, with applied expert knowledge and automated techniques. The resulting highly applicable DEM fulfils geometrical (numerical), geomorphological (shape), and semantic quality properties.     

Coupling land use allocation models with raster GIS

As geographic information systems (GIS) have moved from information storage and retrieval operations towards more decision support functions, there is a need for more integration of spatial analytical modules that can assist in locational decisions. This paper presents a methodology for coupling land use allocation models with a raster GIS. For raster systems, the integration of any decision module has been limited by the size of raster datasets that may contain hundreds of thousands of pixels. Therefore, decision heuristics have been used rather than exact methods such as mathematical programming models. For the problem of land use allocation, the special structure of the generalized assignment problem is used here to handle large scale datasets. The advantage of the mathematical programming approach is the additional information associated with the dual variables and opportunity costs that can be used in subsequent sensitivity analyses. Received: 7 April 1998/Accepted: 2 October 1998     

A Triangular Form‐based Multiple Flow Algorithm to Estimate Overland Flow Distribution and Accumulation on a Digital Elevation Model

In this study, we present a newly developed method for the estimation of surface flow paths on a digital elevation model (DEM). The objective is to use a form‐based algorithm, analyzing flow over single cells by dividing them into eight triangular facets and to estimate the surface flow paths on a raster DEM. For each cell on a gridded DEM, the triangular form‐based multiple flow algorithm (TFM) was used to distribute flow to one or more of the eight neighbor cells, which determined the flow paths over the DEM. Because each of the eight facets covering a cell has a constant slope and aspect, the estimations of – for example – flow direction and divergence/convergence are more intuitive and less complicated than many traditional raster‐based solutions. Experiments were undertaken by estimating the specific catchment area (SCA) over a number of mathematical surfaces, as well as on a real‐world DEM. Comparisons were made between the derived SCA by the TFM algorithm with eight other algorithms reported in the literature. The results show that the TFM algorithm produced the closest outcomes to the theoretical values of the SCA compared with other algorithms, derived more consistent outcomes, and was less influenced by surface shapes. The real‐world DEM test shows that the TFM was capable of modeling flow distribution without noticeable ‘artefacts’, and its ability to track flow paths makes it an appropriate platform for dynamic surface flow simulation.     

Terrain complexity and reduction of topographic data

Digital terrain data are useful for a variety of applications in mapping and spatial analysis. Most available terrain data are organized in a raster format, among them being the most extensively-used Digital Elevation Models (DEM) of the U.S. Geological Survey. A common problem with DEM for spatial analysis at the landscape scale is that the raster encoding of topography is subject to data redundancy and, as such, data volumes may become prohibitively large. To improve efficiency in both data storage and information processing, the redundancy of the terrain data must be minimized by eliminating unnecessary elements. To what extent a set of terrain data can be reduced for improving storage and processing efficiency depends on the complexity of the terrain. In general, data elements for simpler, smoother surfaces can be substantially reduced without losing critical topographic information. For complex terrains, more data elements should be retained if the topography is to be adequately represented. In this paper, we present a measure of terrain complexity based on the behavior of selected data elements in representing the characteristics of a surface. The index of terrain complexity is derived from an estimated parameter which denotes the relationship between terrain representation (percentage surface representation) and relative data volume (percentage DEM elements). The index can be used to assess the required volume of topographic data and determine the appropriate level of data reduction. Two quadrangles of distinct topographic characteristics were examined to illustrate the efficacy of the developed methodology.     

栅格DEM的水平分辨率对地形信息的影响分析

数字高程模型（DEM）是当前用于地形分析的主要数据源,可以从DEM提取不同的地形因子得到地形信息为各种地学分析提供基础服务。对三峡库区应用6种不同网格分辨率进行地形因子数据的提取和分析。研究表明,DEM的水平分辨率对地形信息的精确性有影响,网格的增大增加了DEM对地形信息的概括．应根据不同的需要选择不同分辨率的DEM。     

多源DEM融合的高差拟合神经网络方法

本文侧重于介绍智能化摄影测量机器学习的高差拟合神经网络方法。观测手段和处理方式等限制导致全球高质量无缝DEM数据的缺乏,进而制约了它在水文、地质、气象及军事等领域的应用。本文提出了一种基于高差拟合神经网络的多源DEM融合方法,尝试融合全球DEM产品SRTM1、ASTER GDEM v2和激光雷达测高数据ICESat GLAS。首先,根据ICESat GLAS的相关参数及与DEM数据的高程差值,结合坡度自适应的思想设置高差阈值对ICESat GLAS进行滤波,剔除异常数据点。然后,以ICESat GLAS数据为控制点,利用神经网络模型拟合ASTER GDEM v2的误差分布。以地形坡度信息和经纬度坐标作为网络输入,ICESat GLAS和ASTER GDEM v2的高程差值作为目标输出,训练得到预测高差,将其与ASTER GDEM v2高程值相加即可获得校正结果。最后,引入TIN差分曲面的方法,利用校正后的ASTER GDEM v2高程值对SRTM1的数据空洞进行填充,融合生成空间无缝DEM。本文通过随机选取数据进行真实试验,对模型进行了精度验证,并给出了处理结果的定量评价和目视效果。结果表明,不论是空洞还是整体区域,本文方法相比其他DEM数据集和其他方法的处理结果都能够在RMSE上表现出优势,同时,本文提出的方法能够有效克服ASTER GDEM中异常值的影响,得到空间无缝DEM。     

A vector-based method for the extraction of catchment from grid DEMs

The methodology of catchment extraction especially from regular grid digital elevation models (DEMs) is briefly reviewed. Then an efficient algorithm, which combines vector process and traditional neighbourhood raster process, is designed for extracting the catchments and subcatchments from depressionless DEMs. The catchment area of each river in the grid DEM data is identified and delineated, then is divided into subcatchments as required. Compared to traditional processes, this method for identifying catchments focuses on the boundaries instead of the area inside the catchments and avoids the boundary intersection phenomena. Last, the algorithm is tested with a set of DEMs of different sizes, and the result proves that the computation efficiency and accuracy are better than existent methods.     

Noisy Data Smoothing in DEM Construction Using Least Squares Support Vector Machines

Since spatial datasets are subject to sampling errors, a smoothing interpolation method should be employed to remove noise during DEM construction. Although least squares support vector machines (LSSVM) have been widely accepted as a classifier, their effect on smoothing noisy data is almost unknown. In this article, the smoothness of LSSVM was explored, and its effect on smoothing noisy data in DEM construction was tested. In order to improve the ability to deal with large datasets, a local method of LSSVM has been developed, where only the neighboring sampling points around the one to be estimated are used for computation. A numerical test indicated that LSSVM is more accurate than the classical smoothing methods including TPS and kriging, and its error surfaces are more evenly distributed. The real‐world example of smoothing noise inherent in lidar‐derived DEMs also showed that LSSVM has a positive smoothing effect, which is approximately as accurate as TPS. In short, LSSVM with a high efficiency can be considered as an alternative smoothing method for smoothing noisy data in DEM construction.     

Drainage skeletonization from flow-accumulated area without the use of threshold

This study presents a method of automatic drainage skeletonization from flow-accumulated area without the use of threshold which conserves drainage geometry at chosen digital elevation model (DEM) scale. To get all possible drainage at the chosen scale, stream order raster is generated by incorporating flow accumulation and flow direction raster derived from corresponding DEM. This allows generation of drainage network without the use of threshold. Resultant stream order raster, termed as raw stream order raster (RSOR), is tested against threshold defined stream order raster to evaluate its efficiency. Use of RSOR allows extraction of stream heads to greater stream head extent. Again, DEM downscaling takes care of overestimation in number of streams. So, the proposed technique is effective in controlling two basic aspects of drainage characteristics – stream number and extent. In our case, drainage estimated from re-sampled medium-scale DEM has the closest matching with that of the reference topographical map.     

pRPL 2.0: Improving the Parallel Raster Processing Library

This article presents an improved p arallel R aster P rocessing L ibrary – pRPL version 2.0. Since the release of version 1.0, a series of modifications has been made in pRPL to improve its usability, flexibility, and performance. While retaining some of the key features of pRPL, the new version has gained several new features: (1) a new DataManager class has been added for integrated data management, and to facilitate data decomposition, assignment mapping, data distribution, Transition execution, and load‐balancing; (2) a GDAL‐based raster data I/O mechanism has been added to support various geospatial raster data formats, and provide centralized and pseudo parallel I/O modes; and (3) a static load‐balancing mode and a dynamic load‐balancing mode using the task‐farming technique are provided. A parallel zonal statistics tool and a parallel Cellular Automata model were developed to demonstrate the usability and performance of pRPL 2.0. The experiments using the California datasets showed that the performance altered when different pRPL options (i.e. load‐balancing mode, I/O mode and writer mode) were used for different algorithms, datasets, and varying numbers of processes.     

A vector-based method for the extraction of catchment from grid DEMs

The methodology of catchment extraction especially from regular grid digital elevation models (DEMs) is briefly reviewed. Then an efficient algorithm, which combines vector process and traditional neighbourhood raster process, is designed for extracting the catchments and subcatchments from depressionless DEMs. The catchment area of each river in the grid DEM data is identified and delineated, then is divided into subcatchments as required. Compared to traditional processes, this method for identifying catchments focuses on the boundaries instead of the area inside the catchments and avoids the boundary intersection phenomena. Last, the algorithm is tested with a set of DEMs of different sizes, and the result proves that the computation efficiency and accuracy are better than existent methods.     

Preparing The National Map for the 3D Elevation Program – products,process and research

The 3D Elevation Program (3DEP) is a collaborative effort among government entities, academia, and the private sector to collect high-resolution 3-dimensional data over the United States. The United States Geological Survey (USGS) is making preparations for managing, processing, and delivering petabytes of 3DEP elevation products for the Nation. In addition to the existing 1/3, 1, and 2 arc-second seamless elevation data layers of The National Map, new 3DEP products include lidar point cloud data; a standard 1-meter DEM layer; additional source datasets; and, in Alaska, 5-meter digital elevation models. A new product generation system improves the construction and publication of the seamless elevation datasets, prepares the additional 3DEP products for distribution, and automates the data management functions required to accommodate the high-volume 3DEP data collection. Major changes in geospatial data acquisition, such as high resolution lidar data, volunteered geographic information, data processing using parallel and grid computer systems, and user needs for semantic access to geospatial data and products, are driving USGS research associated with the 3DEP. To address the research requirements, a set of inter-related projects including spatiotemporal data models, data integration, geospatial semantics and ontology, high performance computing, multi-scale representation, and hydrological modeling using lidar and other 3DEP data has been developed.     

EarthEnv-DEM90: A nearly-global,void-free,multi-scale smoothed, 90m digital elevation model from fused ASTER and SRTM data

A variety of DEM products are available to the public at no cost, though all are characterized by trade-offs in spatial coverage, data resolution, and quality. The absence of a high-resolution, high-quality, well-described and vetted, free, global consensus product was the impetus for the creation of a new DEM product described here, ‘EarthEnv-DEM90’. This new DEM is a compilation dataset constructed via rigorous techniques by which ASTER GDEM2 and CGIAR-CSI v4.1 products were fused into a quality-enhanced, consistent grid of elevation estimates that spans ∼91% of the globe. EarthEnv-DEM90 was assembled using methods for seamlessly merging input datasets, thoroughly filling voids, and smoothing data irregularities (e.g. those caused by DEM noise) from the approximated surface. The result is a DEM product in which elevational artifacts are strongly mitigated from the input data fusion zone, substantial voids are filled in the northern-most regions of the globe, and the entire DEM exhibits reduced terrain noise. As important as the final product is a well defined methodology, along with new processing techniques and careful attention to final outputs, that extends the value and usability of the work beyond just this single product. Finally, we outline EarthEnv-DEM90 acquisition instructions and metadata availability, so that researchers can obtain this high-resolution, high-quality, nearly-global new DEM product for the study of wide-ranging global phenomena.     

Comparison of basin morphometry derived from topographic maps,ASTER and SRTM DEMs: an example from Kerala,India

The drainage network of a sixth-order tropical river basin, viz. Ithikkara river basin, was extracted from different sources such as Survey of India topographic maps (1: 50,000; TOPO) and digital elevation data of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) (30 m) and Shuttle Radar Topography Mapping Mission (SRTM) (90 m). Basin morphometric attributes were estimated to evaluate the accuracy of the digital elevation model (DEM)-derived drainage networks for hydrologic applications as well as terrain characterization. The stream networks derived from ASTER and SRTM DEMs show significant agreement (with slight overestimation of lower order streams) with that of TOPO. The study suggests that SRTM (despite the coarser spatial resolution) provides better results, in drainage delineation and basin morphometry, compared to ASTER. Further, the variability of basin morphometry among the data sources might be attributed to spatial variation of elevation, raster grid size and vertical accuracy of the DEMs as well as incapability of the surface hydrologic analysis functions in the GIS platform.     

Accuracy Assessment of Digital Elevation Model Generated by SAR Stereoscopic Technique Using COSMO-Skymed Data

Radargrammetry technique using the stereoscopic synthetic aperture radar (SAR) images is used for the generation of a digital elevation model (DEM) of a region requires only the amplitude images. SAR stereoscopic technique is analogous to the stereo-photogrammetric technique where the optical stereoscopic images are used for DEM generation. While the advantages of the SAR images are their indifference to atmospheric transparency and solar illumination conditions, the side-looking geometry of the SAR increases the complexity in the SAR stereo analysis. The availability of high spatial and temporal resolution SAR data in recent years has facilitated generation of high-resolution DEM with greater vertical accuracy using radargrammetric technique. In the present study, attempt has been made to generate the DEM of Dehra Dun region, India, from the COSMO-Skymed X-band SAR data-pair acquired at 8 days interval through the radargrammetry technique. Here, radargrammetric orientation approach has been adopted to generate the DEM and various issues and processing steps with the radargrammetry technique have been discussed. The DEM was validated with ground measured elevation values using a differential global positioning system and the root-mean-square error of the DEM was found as 7.3 m. The DEM was compared with the reference DEM of the study area generated from the Cartosat-1 stereo data with a model accuracy of 4 m.     

基于多协议的地理信息服务集成

设计了多协议地理信息服务集成框架,探讨解决了其中的关键问题,实现了从不同地理信息服务获取的影像数据、矢量数据和DEM数据的无缝集成。     

Sketch-based Identification of Bench and Terrace Slope Breaks in the Laramie Basin, Wyoming

This study presents a semi‐automated approach to support the identification of fluvial landform slope breaks in the Laramie Basin, southeastern Wyoming. The landforms in question form the edges of terraces and benches and tend to be subtle and varied depending on where they appear in the landscape. Because of this variation combined with DEM error, conventional raster filtering methods were unable to readily identify the benches with any consistency. In an effort to automate the collection of benches, a two stage, sketch‐based algorithm was designed to detect bench edges on a semi‐automated basis and was integrated into a commercial GIS environment for testing and execution. The approach of tailoring an algorithm to detect a particular feature proved viable and, in fact, more consistent in many cases than heads‐up digitizing. However, feature complexity appears to be a significant driver in the accuracy of the algorithmic approach with the unlikely finding that more complex features are more accurately identified than less complex features. This research demonstrates that user cognition, DEM resolution, algorithm functionality and landform characteristics are thus all important and interrelated factors requiring consideration when implementing approaches to topographic feature identification.     

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。