水平分辨率对DEM流域特征提取的影响

选取石质山地与黄土丘陵过渡区宛川河流域作为研究区,利用1∶5万、水平分辨率10~100 m栅格DEM提取流域特征参数进行分析。结果表明:DEM水平分辨率对数字河网的提取精度有影响,提取的流域面积差别很小,河流长度、河道总长、河道坡度以及河网密度有偏差,流域平均坡度变化明显,长度和坡度特征参数的变化导致流域汇流时间及滞时不一致。     

流域水系自动提取在西苕溪流域的应用

论述了如何基于栅格DEM自动提取流域自然水系的原理、方法和流程.以西苕溪中上游流域为例,根据DEM精度、上游集水区面积阈值和下垫面地形的不同,对所提取水系进行了比较.针对在平均地形坡度小于3°的平坦区域所提取水系与实际河网偏差较大的问题,提出了利用主干河道和平原水系数字化作为约束条件生成河网的新方法.     

基于神经网络的地面坡度与其他地形定量因子关联性分析--以黄土高原丘陵沟壑区实验为例

不同的地形因子从不同侧面反映地面的起伏特征或空间变异，各因子之间所存在的相互关联、相互制约、相互影响的程度与特征，在很大程度上揭示了地形发育与空间变异的内在本质，因而是地形学研究的重要内容。他以黄土高原丘陵沟壑区的16个样本地区为实验样区，以高分辨率、高精度的1：1万比例尺DEM为基准数据，应用BP神经网络模型，探讨地面坡度与其他地形因子之间的关联性特征。实验结果表明，利用神经网络分析方法可以有效评价地形因子对地面平均坡度的关联性。该研究方法为进行地貌多定量指标的的选择和多因子之间关联性的量化提供了一种新的方法。     

DEM结构特征对坡度坡向的影响分析

数字高程模型已严格定义为按规则格网阵列记录的地形高程数据,其固有的结构特征(如格网分辨率、格网方向、高程数据准确度等)直接影响DEM对地形表达和坡度、坡向的计算精度。该文通过理论和数据独立的DEM实验分析方法,研究了DEM结构特征对坡度、坡向的影响,得出如下结论:1)高分辨率的DEM并不一定能给出高精度的坡度、坡向计算结果;2)可通过g=bm/ms×180/π×cos2S来选择合适的DEM分辨率;3)三阶不带权差分算法的坡度、坡向计算结果对DEM方向有较强的依赖性。     

基于不同DEM数据源的数字河网提取对比分析——以韩江流域为例

基于HYDRO1K、SRTM3和ASTER GDEM三种DEM数据,利用BTOPMC地形子模型提取韩江流域河网,并作对比分析。结果表明:①SRTM3提取的河网精度最高,HYDRO1K相对最低。②DEM的垂直精度对提取的河网精度起控制作用。ASTER GDEM的水平分辨率较高,但垂直精度不如SRTM3,因而提取的河网精度不如SRTM3。③HYDRO1K提取大尺度流域河网具有一定的精度,但在地势平坦区域的效果较差,HY-DRO1K不宜用来提取小尺度流域河网。④由DEM提取的数字河网精度与当地的地面坡度以及处理DEM的填洼算法有关。     

DEM地面形态重构方法的精度差异特征研究

依据DEM地形建模过程,阐述了DEM地面形态重构概念,并以黄土丘陵1∶5万DEM数据为例,采用高程数值误差场和局地坡面形态误差场相结合的分析技术,实验分析了双线性、三次卷积、局部二次多项式、规则样条函数等常用插值方法在基于加密格网的DEM地面形态重构过程中的精度差异,以及DEM地面形态可重构的基本条件等问题。研究表明:在高程数值误差的极值大小、离散程度、空间分布等方面,规则样条函数插值法具有最好的地面形态重构精度,其次为局部二次多项式、三次卷积和双线性插值法;对于已确定综合尺度的地形,存在满足高保真地面形态描述要求的最佳DEM格网分辨率阈值,只有当实际DEM格网分辨率等于或高于该阈值时,才有可能无歧义、高精度地重构出DEM所描述的综合地形的地面形态。     

基于多方位DEM地形晕渲的黄土地貌正负地形提取

以陕北绥德县韭园沟流域5 m分辨率DEM数据为基础,在数字地形分析、多元统计和数据挖掘方法的基础上,提出利用多方位DEM地形晕渲、坡度等多元指标,以主成分分析消除多重共线性和约减维数,并以Logis-tic回归模型提取黄土高原正、负地形的方法。研究结果表明:模型提取精度为82.1%,Kappa统计量为0.629;模型在6个不同流域测试样本上正、负地形的平均精度分别为77.6%,84.9%,加权平均精度为81.3%,模型具有较好的一致性和泛化能力,正、负地形提取效果良好。     

基于DEM的四川省低山丘陵区坡度提取不确定性分析

针对四川省低山丘陵区,以GIS为技术支撑,深入分析研究区坡度提取的不确定性.以平均坡度代表区域坡度的一般水平,采用6种地貌类型的12组不同分辨率的DEM数据,研究平均坡度与DEM空间分辨率、区域地貌特征的关系,定量分析基于DEM提取坡度的不确定性.结果表明,研究区不同地貌单元内,平均坡度随着DEM分辨率的减小而减小,呈现出很强的线性变化规律,其衰减速率基本不变;其回归方程的常数项与所在地貌单元的沟壑密度呈显著的二次曲线变化特征;坡度提取的精度与DEM的空间分辨率成正相关关系.     

基于高分辨率DEM的黄土地貌正负地形自动分割技术研究

黄土地貌正负地形自动分割是构建地表空间分布式机理-过程模型的基础。在分析黄土高原地区典型地貌坡面形态及汇流过程特征的基础上,提出了基于5m分辨率栅格DEM自动分割黄土正、负地形的技术方案。该方案首先利用坡面上下游栅格点的坡度对比识别沟沿线点,然后利用汇水模型提取沟沿线点约束的上游汇水区域,从而实现正、负地形的自动分割。在黄土塬区及丘陵沟壑区的实验结果表明,该方法的优点是提取精度高,人工干预少,在不同地貌类型区域内有很好的应用适宜性。     

SRTM DEM高程精度评价

为了全面认识SRTM DEM数据精度特征并完善SRTM DEM数据精度评定方法,该文以我国1∶5万比例尺DEM为参考数据,以具有多种地貌类型的陕西省为实验样区,利用高程中误差模型及空间插值方法对SRTMDEM进行高程精度分析。结果表明:陕西省的SRTM DEM高程中误差在3.5~60.7 m,呈现出较为显著的空间分异特征;并且高程中误差与实验样区平均坡度有较强的指数相关性,拟合的指数函数具有较高的模拟精度。     

不同分辨率DEM提取地面坡度的不确定性模拟:以在黄土高原的试验为例

Slope is one of the crucial terrain variables in spatial analysis and land use planning,especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas,but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as (0.0015S2+0.031S-0.0325)X-0.0045S2-0.155S+0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation.     

Simulation on slope uncertainty derived from DEMs at different resolution levels: a case study in the Loess Plateau

Slope is one of the crucial terrain variables in spatial analysis and land use planning, especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas, but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as (0.0015S2+0.031S-0.0325)X-0.0045S2-0.155S+0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation.     

Simulation on slope uncertainty derived from DEMs at different resolution levels： a case study in the Loess Plateau

Slope is one of the crucial terrain variables in spatial analysis and land use planning, especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas, but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as(0.0015S2 0.031S-0.0325)X-0.0045S2-0.155S 0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation.     

Resolution and accuracy of terrain representation by grid DEMs at a micro-scale

This paper examines the impact of DEM resolution on the accuracy of terrain representation and of the gradient determined. The DEMs of three terrain types with diverse complexities were constructed from digitizing contours and then kriging. The accuracy (RMSE) of the DEMs was regressed against contour density (D) and DEM resolution (S) at six resolution levels. It is found that RMSE may be expressed as (7.274 1.666S)D/1000 with an R value of 0.9659. The representation accuracy decreases moderately at an intermediate resolution, but sharply at coarse resolutions for all three terrain types. Resolution reduction profoundly affects the gradient determined from the DEM. While exerting little influence on mean gradient, resolution significantly affects the standard deviation of gradient, especially for a simple terrain. The results obtained in this study may be used to determine the DEM resolution that is appropriate to the accuracy requirements of a particular user.     

The impact of resolution on the accuracy of hydrologic data derived from DEMs

Hydrologic data derived from digital elevation models (DEM) has been regarded as an effective method in the spatial analysis of geographical information systems (GIS). However, both DEM resolution and terrain complexity has impacts on the accuracy of hydrologic derivatives. In this study, a multi-resolution and multi-relief comparative approach was used as a major methodology to investigate the accuracy of hydrologic data derived from DEMs. The experiment reveals that DEM terrain representation error affects the accuracy of DEM hydrological derivatives (drainage networks and watershed etc.). Coarser DEM resolutions can usually cause worse results. However, uncertain result commonly exists in this calculation. The derivative errors can be found closely related with DEM vertical resolution and terrain roughness. DEM vertical resolution can be found closely related with the accuracy of DEM hydrological derivatives, especially in the smooth plain area. If the mean slope is less than 4 degrees, the derived hydrologic data are usually unreliable. This result may be helpful in estimating the accuracy of the hydrologic derivatives and determining the DEM resolution that is appropriate to the accuracy requirement of a particular user. By applying a threshold value to subset the cells of a higher accumulation flow, a stream network of a specific network density can be extracted. Some very important geomorphologic characteristics, e.g., shallow and deep gullies, can be separately extracted by means of adjusting the threshold value. However, such a flow accumulationbased processing method can not correctly derive those streams that pass through the working area because it is hard to accumulate enough flow direction values to express the stream channels at the stream's entrance area. Consequently, errors will definitely occur at the stream’s entrance area. In addition, erroneous derivatives can also be found in deriving some particular rivers, e.g., perched (hanging up) rivers, anastomosing rivers and braided rivers. Therefore, more work should be done to develop and perfect the algorithms.     

The impact of resolution on the accuracy of hydrologic data derived from DEMs

1 Introduction Automated extraction of drainage features from DEMs is an effective alternative to the tedious manual mapping from topographic maps. The derived hydrologic characteristics include stream-channel networks, delineation of catchment boundaries, catchment area, catchment length, stream-channel long profiles and stream order etc. Other important characteristics of river catchments, such as the stream-channel density, stream-channel bifurcation ratios, stream-channel order, number…     

Effects of lidar post‐spacing and DEM resolution to mean slope estimation

This paper examines the effect of scale (exhibited by spatial sampling) in modeling mean slope from lidar data using two representations of scale: lidar posting density (i.e. post‐spacing) and DEM resolution (i.e. cell size). The study areas selected include six small (i.e. approximately 3 km²) urban drainage basins in Richland County, SC, USA, which share similar hydrologic characteristics. This research spatially sampled an airborne lidar dataset collected in 2000 at a 2 m nominal posting density to simulate lidar posting density at various post‐spacings, from 2 m through 10 m. DEMs were created from the lidar observations at a corresponding cell size using spatial interpolation. Finally, using these DEMs, a sensitivity analysis between modeled terrain slope and lidar post‐spacing was conducted. Results of the sensitivity analyses showed that the deviation between mean slope and modeled mean slope decreases with finer posting density and DEM resolution. The relationship of mean slope with varying cell sizes and post‐spacing suggests a linear and a logarithmic function, respectively, for all study areas. More importantly, cell size has a greater effect on mean slope than lidar posting density. Implications of these results for lumped hydrologic modeling are then postulated.     

坡谱提取与应用的基本地域条件

阐述坡谱提取原理,借鉴地理空间数据不确定性处理中的"ε-带"模型概念,构建坡谱稳定的判定模型,最后以陕北黄土高原和秦岭山区的典型地貌类型区为实验区,以1:10000 DEM为信息源,分析研究不同地貌类型区坡谱的变异特征,揭示坡谱提取与应用的基本条件:地貌形态的相似性与渐变性、研究尺度的合理性以及地貌类型的完整性。该研究为坡谱的进一步深入研究与应用奠定良好的理论基础,也为地理学研究中如何确定基本地域单元等重要的理论问题提供了借鉴思路。     

DEM地形信息量计算的不确定性研究

DEM地形信息量的准确度量是判定DEM数据应用适宜性与限制性关键。以黄土丘陵沟壑区DEM及其派生的坡度、坡向DTM为例进行实验,研究子集划分与分级数对DEM信息量估算精度的影响。结果表明,DEM地形信息量是实际地形信息和子集划分策略共同作用的结果,现有DEM信息量计算存在不确定性,DEM子集划分算法和分级数的选择直接影响DEM信息量的计算结果。文章借助最大熵定理的基本思路构建DEM地形信息量分级判定模型,可客观获得连续型栅格地形数据在信息量计算上最优分级,为有效估算DEM地形信息量提供科学依据。