数字高程模型地形描述精度的研究

对数字高程模型(DEM)的地形描述误差(Et)与空间分辨率(R)和平均剖面曲率(V)的关系进行研究,得到地形描述误差的均方差值与R、V的函数关系公式:RMSEt=(0.006 1 V 0.002 7)R 0.001 0 V2-0.0649 V 0.569 5.进一步,还得到地形描述误差的均方差值与R、坡度W的函数关系公式:RMSEt=(0.000 1W2 0.003 1W 0.030 1)R 0.000 8W2-0.050 8W 0.355 9.分析结果表明,所得公式具有好的效果.     

数字高程模型格网间距对提取地形因子的影响研究

数字高程模型(DEM)作为地面高程信息的数字表示形式,在地学研究领域得到了广泛应用.本文通过对DEM基本原理及其现有表示形式进行分析,提出了数字等高线也是DEM表示形式的观点.随后通过选取4种不同地貌类型的规则格网DEM作为实验区,分析研究了DEM格网间距对坡度、坡面曲率、地表切割深度、地表粗糙度和沟谷密度等地形因子提取的影响,为人们根据地貌类型和应用需求合理选择DEM分辨率提供了参考.     

基于杨赤中插值法的DEM的可视化

数字高程模型(DEM)能有效描述地形结构,可视化技术是当今表达和分析复杂数据的有力工具。应用杨赤中插值法,将地形碎部点高程观测值看作一种包含规律性变化和随机性变化的复合变量,求其二项系数加权游动平均,建立估值数学模型,划分格网,求得各格网点高程估值。并阐述利用网格法来实现、分析和显示DEM数据的可视化原理和实例。     

雪线时空分布及与地形因子相关性分析

采用青海玉珠峰1998、2010、2013、2015年7月份四期SPOT5及QuickBird遥感影像(1998年为航片),解译冰雪范围线,对冰雪覆盖区域的时空变化特征进行分析。获取2013年雪线高程,利用30 m分辨率的SRTM-DEM提取坡度、地形曲率、地形起伏度等地形因子。在气温、降水条件基本相同的情况下,对不同的海拔范围采用回归分析推算雪线高程与地形因子的相关关系。结果表明,随着海拔的升高,雪线高程与地形因子的相关性有逐步增强的趋势。当海拔达到约5 500 m时,雪线高程与坡度、地形起伏度、剖面曲率、平面曲率的相关系数分别为0.509、0.517、0.141、0.221,地形起伏度与坡度是对雪线分布影响相对较大的地形因子。     

基于Coons曲面的规则格网DEM表面模型

内插是数字高程模型的核心问题。目前的内插模型主要是由离散的格网数据构建的连续曲面,直接以点推面,可能存在较大的地形误差。本文建立的Coons曲面DEM表面模型,首先利用离散的格网数据构造与格网边界相对应的地形剖面曲线的拟合曲线,再基于拟合曲线构建DEM表面模型。实验表明：Coons曲面DEM表面模型是一种高精度的DEM表面模型,其地形模拟误差比直接基于格网数据建立的双线性内插、样条函数内插和移动曲面拟合法的误差都小,实际地形模拟误差与双线性模型相比减少15％-28％,且精度随着构建边界拟合曲线所用格网点的增多而逐渐提高。     

DEM线性建模过程中的高程误差传播

在建立数字高程模型(DEM)时,基于规则格网数据和基于三角形网数据的线性建模是常用的方法。在建模过程中,结点的高程误差会随之传播。研究了DEM在基于规则格网数据和基于三角形网数据的线性建模过程中的高程误差传播问题,推导出了在结点高程误差相关情形下的高程误差传播公式,求出了在规则格网和不规则格网面上的平均高程传播误差。平均高程传播误差可以作为DEM线性插值过程中高程误差传播的度量指标。     

DEM线性建模过程中的高程误差传播

在建立数字高程模型(DEM)时,基于规则格网数据和基于三角形网数据的线性建模是常用的方法.在建模过程中,结点的高程误差会随之传播.研究了DEM在基于规则格网数据和基于三角形网数据的线性建模过程中的高程误差传播问题,推导出了在结点高程误差相关情形下的高程误差传播公式,求出了在规则格网和不规则格网面上的平均高程传播误差.平均高程传播误差可以作为DEM线性插值过程中高程误差传播的度量指标.     

影响黄土高原集水面积阈值的地形因子主成分分析

以ASTER GDEM为信息源、22个典型小流域为样区,分析黄土高原集水面积阈值与沟谷密度的关系,利用均值变点法确定最佳阈值,探讨了影响阈值的数字高程模型（digital elevation model,DEM）地形因子主成分。结果表明,集水面积阈值由北向南、自东向西逐步增大,宏观上受黄土高原地貌类型制约,地形因子对其的影响成分归纳为坡面、起伏及高程变异因子。坡面因子的最大值与阈值正相关,坡度>粗糙度>地形曲率>平面曲率>剖面曲率。起伏因子的均值与阈值正相关,起伏度>切割深度。高程变异因子与阈值负相关。三者的主成分贡献率依次为58.754%、18.915%、11.388%,权重为0.527、0.229、-0.569。研究表明,坡面特征是影响黄土沟谷发育的重要因子。     

基于DEM的地形因子分析与岩性分类

地形因子作为对地形地貌特征进行数字表达的定量参数,对岩性识别精度的提高具有重要的意义。在对已知岩性类别区域的高程、坡度、剖面曲率、地表粗糙度和地表切割深度等10个地形因子的分类有效性和相关性进行评价的基础上,对地形因子进行筛选并将最佳尺度下的地形因子用于岩性的分类。结果表明,高程、剖面曲率、地表切割深度、地表粗糙度和平面曲率这5个地形因子的组合更具良好的分类效果,且都对应有识别性最好的岩性。在识别岩性类别时加入充分表达其地形特征的最佳地形因子组合有利于提高岩性的识别与分类能力。     

基于DEM地形因子的水土流失分析

研究地形因子对水土流失造成的影响,可为区域水土保持工作提供参考.本文以广西百色市、河池市、贺州市、防城港市为研究区域,以ArcGIS平台为技术支持,基于数字高程模型数据,选取坡度、剖面曲率、地表粗糙度、沟壑密度4个指标,进行空间叠加分析,得到研究区基于所选地形因子的水土流失强度分级图及水土流失面积,得出如下结论:1)基...     

采样数据密度及栅格尺寸对高程中误差的影响分析

利用全数字摄影测量得到的高精度点数据,获取不同密度的点数据,建立基于ANUDEM和TIN方法的两种DEM,比较两种DEM的高程中误差,分析数据密度、栅格尺寸与高程中误差的关系。研究结果表明,建立1∶100 00比例尺,具有高程中误差2m左右、栅格尺寸5m以下的ANUDEM,需要的点密度水平为大于7 000个/km2,而TINDEM则为8 500个/km2。同时,当栅格尺寸小于20m、数据密度介于7 000～9 400个/km2时,无论是ANUDEM还是TINDEM,高程中误差都处于一个较稳定的状态。     

The Effect of DEM Raster Resolution on First Order, Second Order and Compound Terrain Derivatives

It is well known that the grid cell size of a raster digital elevation model has significant effects on derived terrain variables such as slope, aspect, plan and profile curvature or the wetness index. In this paper the quality of DEMs derived from the interpolation of photogrammetrically derived elevation points in Alberta, Canada, is tested. DEMs with grid cell sizes ranging from 100 to 5 m were interpolated from 100 m regularly spaced elevation points and numerous surface‐specific point elevations using the ANUDEM interpolation method. In order to identify the grid resolution that matches the information content of the source data, three approaches were applied: density analysis of point elevations, an analysis of cumulative frequency distributions using the Kolmogorov‐Smirnov test and the root mean square slope measure. Results reveal that the optimum grid cell size is between 5 and 20 m, depending on terrain com‐plexity and terrain derivative. Terrain variables based on 100 m regularly sampled elevation points are compared to an independent high‐resolution DEM used as a benchmark. Subsequent correlation analysis reveals that only elevation and local slope have a strong positive relationship while all other terrain derivatives are not represented realistically when derived from a coarse DEM. Calculations of root mean square errors and relative root mean square errors further quantify the quality of terrain derivatives.     

DEM网格尺寸对地形因子精度的影响分析

本文以四川省为研究区,基于SRTM数据和GDEM数据,选取5种不同网格尺寸提取坡度、坡向、剖面曲率、平面曲率和地表粗糙度等地形因子,比较DEM网格尺寸变化对提取的地形因子计算结果的误差。研究表明,DEM网格尺寸的增大增加了DEM对地形信息的概括,提取的地形因子准确性降低;但是网格尺寸如果过小,会导致数据量快速增大,浪费大量时间和计算机资源。所以在生产实践中,应综合考虑多种因素选择适宜的网格尺寸。     

QUALITY CONTROL OF PHOTOGRAMMETRICALLY SAMPLED DIGITAL ELEVATION MODELS

The object of this paper is to study the geometric accuracy of photogrammetrically sampled digital elevation models (DEMs)obtained by using an on line graphical DEM editor. As a reference, DEMs obtained by regular grid measurements have been used. Three different test areas are used in the study, each representing different ground types and degrees of homogeneity. The DEMs have been evaluated with respect to their standard errors in elevation, slope and curvature. The results show that the standard errors are not improved by using the on line DEM editor. It is also demonstrated that an increased point density decreases the standard error in elevation while its effect on the standard error in slope is limited. The standard error in curvature is almost independent of the point density.     

机载LiDAR点云密度对DEM精度的影响

机载激光雷达技术(LiDAR)作为一项先进的遥感技术,是植被覆盖区DEM获取的重要手段之一,而不同地形坡度条件及点云密度对DEM产品质量有重要影响。本文以辽宁省某市的机载LiDAR数据为基础,选取5种不同地形坡度的点云数据,通过随机、等间距及基于曲率3种不同的点云抽稀方法,按照点云保留率为80%、60%、40%、20%和10%共5个不同梯度的抽稀倍数对原始点云进行抽稀简化处理,生成与之对应的DEM并对其进行精度评价,以此研究地形坡度、点云抽稀方法、抽稀倍数对DEM精度的影响。结果表明,DEM精度与地形坡度呈负相关关系,即RMSE随地形坡度升高不断增加;基于曲率的抽稀方法在地形坡度＞30°时,相较于其他两种方法RMSE较小,具有明显优势;40%的点云保留率是平衡DEM精度与数据存储效率的一个节点,当点云保留率<40%时,DEM的高程RMSE会迅速增大。该研究对于利用机载LiDAR进行大范围DEM生产具有一定的指导和借鉴意义。     

Evaluation and Comparison of Multi Resolution DEM Derived Through Cartosat-1 Stereo Pair – A Case Study of Damanganga Basin

The study evaluates and compares Digital Elevation Model (DEM) data of various grid spacing derived using high resolution Cartosat 1 stereo data for hydrologic applications. DEM is essential in modeling different environmental processes which depend on surface elevation. The accuracy of derived DEM varies with grid spacing and source. The CartoDEM is the photogrammetric DEM derived from stereo pairs. Damanganga basin lying in the Western Ghats was analysed using 11 Carto stereo pairs. The process of triangulation resulted in RMSE of 0.42. DEM was extracted at 10 m, 20 m, 30 m, 40 m, 50 m and 90 m grid spacing and compared with ASTER GDEM (30 m) and SRTM DEM (90 m). DEM accuracy was checked with Root Mean Square Error (RMSE) statistic for random points generated in different elevation zones. Extracted stream networks were compared based on Correctness Index and Figure of Merit index, calculated for all the Digital Elevation Models at varying cell sizes. In order to further evaluate the DEM’s, a simple flood simulation with no water movement and no consideration of real time precipitation data was carried out and relationship between heights of flood stage and inundation area for each Digital Elevation Model was also established.     

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.     

Comparative evaluation of horizontal accuracy of elevations of selected ground control points from ASTER and SRTM DEM with respect to CARTOSAT-1 DEM: a case study of Shahjahanpur district,Uttar Pradesh,India

Digital elevation model (DEM) data of Shuttle Radar Topography Mission (SRTM) are distributed at a horizontal resolution of 90 m (30 m only for US) for the world, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM data provide 30 m horizontal resolution, while CARTOSAT-1 (IRS-P5) gives 2.6 m horizontal resolution for global coverage. SRTM and ASTER data are available freely but 2.6 m CARTOSAT-1 data are costly. Hence, through this study, we found out a horizontal accuracy for selected ground control points (GCPs) from SRTM and ASTER with respect to CARTOSAT-1 DEM to implement this result (observed from horizontal accuracy) for those areas where the 2.6-m horizontal resolution data are not available. In addition to this, the present study helps in providing a benchmark against which the future DEM products (with horizontal resolution less than CARTOSAT-1) with respect to CARTOSAT-1 DEM can be evaluated. The original SRTM image contained voids that were represented digitally as ?140; such voids were initially filled using the measured values of elevation for obtaining accurate DEM. Horizontal accuracy analysis between SRTM- and ASTER-derived DEMs with respect to CARTOSAT-1 (IRS-P5) DEM allowed a qualitative assessment of the horizontal component of the error, and the appropriable statistical measures were used to estimate their horizontal accuracies. The horizontal accuracy for ASTER and SRTM DEM with respect to CARTOSAT-1 were evaluated using the root mean square error (RMSE) and relative root mean square error (R-RMSE). The results from this study revealed that the average RMSE of 20 selected GCPs was 2.17 for SRTM and 2.817 for ASTER, which are also validated using R-RMSE test which proves that SRTM data have good horizontal accuracy than ASTER with respect to CARTOSAT-1 because the average R-RMSE of 20 GCPs was 3.7 × 10^?4 and 5.3 × 10^?4 for SRTM and ASTER, respectively.