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DEM分形特征的坡度尺度变换模型

利用DEM提取坡度具有明显的尺度依赖性,探求DEM在不同尺度下表现出的规律关系,建立多尺度变换模型,以实现不同尺度间的转换是地形分析研究的热点和难点。本文阐释了DEM表面与地表粗糙度分形维数值的地学意义及内在关系,并利用分形对象的自相似性原理,建立了一种基于DEM分形特征的坡度尺度变换模型。选取四川丘陵地区某小流域为研究区,进行坡度尺度变换实验和误差分析,结果表明该模型能有效实现坡度尺度变换:在非平坦地区(坡度1°)一般重采样方法变换得到的坡度误差为该方法的1.86倍;从信息熵理论分析,经该方法转换后的坡度信息得到了显著恢复。对于无1︰1万及以上精度地形数据的西南山区,利用该方法获取高精度坡度数据具有重要的理论价值和现实意义。     

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。     

数字地形分析的理论、方法与应用

数字高程模型自20世纪50年代首次被提出以来,就以其简洁的数据组织方式、对地形的直观表达、简单高效的地形因子解译方法而显示了其在地学领域应用的巨大潜力。本文在全面检索和分析前人相关研究成果的基础上,首先将数字地形分析 (Digital Terrain Analysis,简称DTA) 的各种分析方法总结为四类,即坡面地形因子分析、特征地形要素分析、地形统计分析以及基于DEM的地学模型分析,并简要总结了每种分析方法的主要内容;其次,探讨了数字地形分析的精度及尺度问题,指出尺度效应、最适宜尺度选择以及尺度转换是DEM地形分析中的基本尺度问题;然后,论文介绍了DTA在地貌、水文、土壤、地质灾害、农业等领域的应用现状;最后,提出了数字地形分析发展方向,指出数字地形分析的概念框架亟待完善、模型构建精度有待提高、地形分析方法需要扩展,尤其是实现DEM模型嵌入的一体化分析方法,以求得到与现实世界地理环境更为接近的模拟。     

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。     

DEM不同分辨率对地形因子提取的不确定性

地形因子的提取对水土流失、土地利用、土地资源评价、城市规划等方面的研究起着重要的作用,通过对地形因子计算和分析,为以上研究提供一定的参考。基于DEM(数字高程模型)的ASTER GDEM V2_30m数据,以云南省保山市隆阳区为研究区,提取该区的坡度与坡向等地形指标,分析不同分辨率(30 m、60 m、90m、120 m)下的地形因子的差异性。结果表明:随着分辨率降低,隆阳区坡度向中等级坡度集中,陡坡区域缩小,即坡度从集中在35°~45°区域向≤5°和15°~25°区域集中;不同空间分辨率对坡向提取也有不确定性的变化,但影响程度没有坡度大。因此在土壤侵蚀等模型中对地形因子进行估算时,需要充分考虑分辨率的影响。     

DEM采样间隔对地形描述精度的影响研究

数字高程模型(DEM)的精度包括采样点数据精度和地形描述精度两方面,前人对DEM精度的研究多集中在DEM采样点精度,而忽视了地形描述精度。该文提出基于窗口曲面拟合计算拟合曲面系列参数与"实际地形"曲面参数的标准差来衡量地形描述精度的方法,研究发现DEM地形描述精度随采样间隔的增大呈降低趋势;并利用坡度频率曲线和坡度累计频率曲线研究对DEM精度敏感的坡度因子与DEM采样间隔的关系,认为随DEM采样间隔增大,坡度衰减(变缓)的速率加快。     

黄土丘陵沟壑区坡度尺度效应空间分异分析

基于DEM提取的地形因子随分辨率变化问题(尺度效应)受到广泛关注,不同地貌类型区地形因子随分辨率变化规律存在差异,其差异的机理性原因还有待进一步探讨。本研究以黄土丘陵沟壑区五个副区为研究区,统计了不同地貌类型区坡度随分辨率变化规律,计算了高程变异函数,并引入独立结构变异函数模型(Independent Structures Model,ISM)拟合了高程表面不同空间频率层次,分析了地形空间频率层次在黄土丘陵沟壑区的空间分异规律,从而进一步分析坡度随分辨率变化规律与地形空间频率层次之间的关系。研究表明:平均坡度相近的地区坡度随分辨率变化规律并不相同,高频地形信息的存在与否及其所占比重,是决定一个地区坡度随分辨率变化衰减程度的重要因素,在坡度随分辨率变化衰减程度和坡度尺度变换研究及应用中应考虑研究区内地形空间频率组成情况,这对于丰富和完善数字地形分析理论体系具有重要意义。     

基于DEM的对称13点局部窗口坡度算法分析

局部曲面拟合法是基于DEM的计算坡度的常用方法之一,采用不同的拟合曲面和局部移动窗口将得到不同精度的计算模型,探索不同的局部窗口类型可以丰富局部曲面拟合法在数字地形分析中的应用。本文考虑不同距离临近点的高程信息,基于3×3局部窗口提出了一种由两种不同倍率、与主轴(x轴、y轴)呈45°夹角的格网点构成的新窗口——对称13点局部窗口,推导了三阶曲面拟合该窗口的坡度计算公式,并利用典型数学曲面对该模型的计算精度进行了分析。研究分析认为,相对于现有的坡度计算模型,三阶曲面拟合对称13点窗口模型能显著地提高坡度计算精度,但对误差的平滑能力较差,适用于高精度DEM。本文的研究扩展了曲面拟合法在数字地形分析中的应用。     

论DEM地形分析中的尺度问题

DEM及其地形分析具有强烈的尺度依赖特征。本文以黄高原地区的研究为例,结合地学建模和地学模拟的需求,重点讨论DEM地形分析中的尺度问题。文中从DEM建立与应用出发,首先建立了DEM地形分析中的尺度概念体系,剖析了各类尺度之间的关系,其次讨论了尺度所引起的各种地形分析效应问题,最后探讨了DEM地形分析中的尺度转换类型和方法。     

地形湿度指数算法误差的定量评价

地形湿度指数(TWI)能够定量指示地形对土壤湿度空间分布的控制,是一种应用广泛的地形属性.目前基于栅格DEM的TWI计算方法结果各异,因此有必要对'TWI算法进行定量评价.对TWI算法通常是应用实际DEM数据进行评价.但实际DEM中存在的数据源误差会干扰对算法误差的评价.针对该问题,本文介绍了一种用不含数据源误差的人造...     

Terrain complexity and uncertainties in grid‐based digital terrain analysis

The objective of this research is to study the relationship between terrain complexity and terrain analysis results from grid‐based digital elevation models (DEMs). The impact of terrain complexity represented by terrain steepness and orientation on derived parameters such as slope and aspect has been analysed. Experiments have been conducted to quantify the uncertainties created by digital terrain analysis algorithms. The test results show that (a) the RMSE of derived slope and aspect is negatively correlated with slope steepness; (b) the RMSE of derived aspect is more sensitive to terrain complexity than that of derived slope; and (c) the uncertainties in derived slope and aspect tend to be found in flatter areas, and decrease with increasing terrain complexity. The study shows that although primary surface parameters can be well defined mathematically, the implementation of those mathematical models in a GIS environment may generate considerable uncertainties related to terrain complexity. In general, when terrain is rugged with steep slopes, the uncertainty of derived parameters is quite minimal. While in flatter areas, the DEM‐based derivatives, particularly the aspect, may contain a great amount of uncertainty, causing significant limitation in applying the analytical results.     

Pre-processing algorithms and landslide modelling on remotely sensed DEMs

Terrain analysis applications using remotely sensed Digital Elevation Models (DEMs), nowadays easily available, permit to quantify several river basin morphologic and hydrologic properties (e.g. slope, aspect, curvature, flow path lengths) and indirect hydrogeomorphic indices (e.g. specific upslope area, topographic wetness index) able to characterize the physical processes governing the landscape evolution (e.g. surface saturation, runoff, erosion, deposition). Such DEMs often contain artifacts and the automated hydrogeomorphic characterization of the watershed is influenced by terrain analysis procedures consisting in artificial depression (pit) and flat area treatment approaches combined with flow direction methods.In shallow landslide deterministic models, when applied using topographic dataset at medium scale (e.g. 30 m of resolution), the choice of the most suitable DEM-processing procedure is not trivial and can influence model results. This also affects the selection of most critical areas for further finer resolution studies or for the implementation of countermeasures aiming to landslide risk mitigation.In this paper such issue is investigated using as topographic input the ASTER DEMs and comparing two different combinations of DEM correction and flow routing schemes. The study areas comprise ten catchments in Italy for which hydrogeomorphic processes are significant. Aims of this paper are: 1) to introduce a parameter estimation procedure for the physically-based DEM correction method PEM4PIT (Physical Erosion Model for PIT removal); 2) to investigate the influence of different terrain analysis procedures on results of the slope stability model SHALSTAB (SHAllow Landsliding STABility) using remotely-sensed ASTER DEMs; 3) trying to assess which of terrain analysis methods is more appropriate for describing terrain instability.     

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.     

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.     

坡位渐变信息的模糊推理

坡位的空间变化通常是渐变的,定量的坡位空间渐变信息对于精细尺度上的坡面土壤侵蚀、预测性土壤制图等应用具有重要意义。现有基于栅格DEM的坡位模糊识别方法,或是仅在属性域内模糊聚类,忽略了空间信息;或是需要繁琐的规则进行模糊分类,实用性受限。本文建立了一种基于相似度的模糊推理方法,根据各类坡位在空间上的典型位置,计算其他位置与典型位置间的相似度,从而对坡位空间渐变信息进行系统、定量的描述。应用表明本方法能够合理地描述山脊、坡肩、背坡、坡脚、沟谷等重要坡位类型的渐变信息,所获得的坡位渐变信息也能够合理地解释土壤样点的A层土壤含砂量随坡位渐变的变化趋势。     

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.     

DEM提取黄土高原地面坡度的不确定性

选择陕北黄土高原6个典型地貌类型区为试验样区,采用野外实测及高精度的1:1万比例尺DEM为基准数据,研究栅格分辨率及地形粗糙度对DEM所提取地面平均坡度精度的影响。结果显示,对于1:1万比例尺DEM,5 m是保证该地区地形描述精度的理想分辨率尺度;多要素逐步回归模拟的方法进一步揭示了DEM所提取的地面平均坡度误差E与栅格分辨率X以及地形起伏的代表性因子-沟壑密度S之间存在的量化关系为E = (0.0015S2+0.031S-0.0325)X-0.0045S2-0.155S+0.1625,该结果也为确定适用的DEM分辨率提供了理论依据。     

贵州高原复杂地形下太阳总辐射精细空间分布

海拔、坡度、坡向以及周围地形遮蔽作用,造成山区各部位接受到的太阳辐射能有很大差异. 在前人研究的基础上,对以前的模型进行了一些改进,考虑了坡度、坡向和地形相互遮蔽作用对复杂地形下天文辐射的影响,基于数字高程模型(DEM)数据,研制了以复杂地形下天文辐射为起始数据的复杂地形下太阳总辐射的分布式模型,在模型中还考虑了散射辐射的各向异性及坡地反射辐射对复杂地形下太阳总辐射的影响.应用100 m×100 m分辨率的DEM数据及气象站常规观测气象资料,计算了贵州高原复杂地形下100 m×100 m分辨率的复杂地形下太阳总辐射.结果表明:(1) 局地地形因子如坡度、坡向、地形遮蔽等对太阳总辐射影响显著,地形对复杂地形下太阳总辐射的影响是不容忽视的.(2)在缺乏复杂地形下坡面考察资料的情况下,建立以常规气象站观测资料为主的物理经验统计模型是实现细网格辐射资源计算的可行途径.     

Terrain Pattern Recognition and Spatial Decision Making for Regional Slope Stability Studies

A terrain partition scheme is presented that allows the identification of regions with high landslide risk in natural terrain zones on the basis of geomorphometric criteria from moderate resolution DEMs. The key factor being the terrain segmentation to aspect regions (regions formed by points preserving the same aspect direction) instead of using an artificial regular-grid terrain partition scheme. The study area is in western Greece (NW Peloponnesus) whereas a moderate resolution digital elevation model with spacing 75 m is used. Landslide inventory analysis and knowledge conceptualization identified that the landslide susceptibility of a particular aspect region is high, if the mean elevation is low and the mean gradient is high. Each aspect region was parametrically represented on the basis of its mean gradient and elevation. The domain of each parameter was divided to seven slices (classes) on the basis of the observed density. Subsequent knowledge based mapping identified aspect regions with high landslide susceptibility for the following spatial rule: (a) “mean slope in class 6 or 7” and (b) “mean elevation in class 1 to 5”. Alternatively the rule is expressed as mean slope to be equal or greater than 15^∘ whereas mean elevation to be in the range 0 to 750 m. These identified zones correspond to regions where historical landslides occurred (populated coastal areas in the North) as well as to south regions (natural terrain zone) where no landslide record is available, because of the limitations posed by the natural terrain landslide mapping program in Greece. The presented terrain segmentation technique combined to the spatial decision-making process, provided both an object framework for integrating geomorphometric parameters and a method for landslide risk analysis in natural terrain zones.