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。     

地形特征与山地气候变化空间关联规则数据挖掘研究

以四川省的地形、气候为研究对象,针对山地地形特征与气候变化研究中,传统的统计分析、非线性拟合等方法缺乏分析处理海量数据和提取隐含信息能力的问题,提出将关联规则数据挖掘与栅格图像处理、地形分析相结合的研究方法。该方法利用栅格图像处理和地形分析技术,对地形和气候栅格图像进行坐标转换、裁剪、分类、因子提取、离散化等预处理,再用Apriori算法对提取的地形特征因子和气候因子进行分析,得到反映两者之间相关性的强关联规则。通过对60余万组数据的分析,得到22条满足最小支持度和置信度的关联规则,并由此综合分析得到6条复合关联规则。实验证明,这些反映地形特征与气候变化幅度之间关联性的关联规则可信度较高。     

黄土地貌地形特征点格局研究

地形特征点广泛分布于地球表面,是反映地貌空间形态的重要点位。通过对不同地形特征点空间分布格局的研究,能够较好地探讨地形特征点群间的空间结构关系及其关联模式,并进一步映射地貌演变过程与发育机理。该文以黄土高原为研究区域,提取山顶点、鞍部点与径流节点作为地形特征点,运用点格局分析方法研究地形特征点间的空间结构特征。结果表明:1)地形特征点的空间分布规律与其地貌类型有显著相关性,而与其等级无明显相关;2)不同特征点存在较为固定的空间关联尺度,这种尺度对地貌类型不存在依赖性;3)在地貌演变的多个时期,不同特征点间的空间格局指标变化趋势具有相似性,而空间分布类型由于受地貌影响存在差异性。运用点格局研究中的相关方法,探索了地形特征点单点及多点间的格局特征,对地形特征结构及其模式研究具有参考意义。     

遥感与神经网络相结合的潮滩地形模拟方法

潮滩地形资料的获取是开发利用潮间带资源的第一步。以纳潮盆地为实验对象,从遥感影像面状信息入手,提取并组合影像中的信息,采用遥感与BP人工神经网络相结合的方法,构建遥感光谱信息、地貌特征与潮滩高程信息之间的关系模型。结果表明:在遥感光谱信息基础上,引入纳潮盆地纵、横剖面地貌特征因子的神经网络模拟效果更好;将潮滩滩面与潮水沟分别进行网络建模,生成地形,平均绝对误差达0.299m,这说明,神经网络在模拟高程起伏较大的区域时精度较低,适当降低神经网络输入数据的复杂度有利于改善网络的模拟精度。     

黄土高原数字地形分析研究进展

黄土高原数字地形分析以我国黄土高原为研究对象,基于该区域不同尺度DEM数据提取各类坡面地形因子及特征地形要素,并通过对各种地形因子和特征要素的自身特点、空间分异规律及各因子与要素之间的相互关系建立地学统计模型,从更深层次探讨黄土地貌演化及其空间分异规律,深化对黄土高原的认识。该文总结了黄土高原数字地形分析的基本理论与分析方法,从该区域的DEM数据模型、地形特征要素、地形信息图谱、地形纹理、沟壑信息图谱和地貌发育演化机理等方面对黄土高原数字地形分析的研究成果进行较全面地梳理与分析。可以看出,黄土高原数字地形分析已成为数字地形分析领域独具特色的研究方向,其中很多方法均已成为地貌计量学的重要研究手段。     

横断山区泥石流空间格局和激发雨量分异性研究

地形、降雨等环境因子决定了泥石流的时空分布特征,理解泥石流与这些因子的关系有助于区域泥石流灾害风险评估与防灾减灾工作。以横断山区为研究区域,选取降水、气候、地貌、地质、土地覆盖、土壤厚度、高差势能以及湿度指数等因子,利用地理探测器和灰度关联分析等方法,探讨了环境因子与泥石流沟空间分布的关系以及降水特征与泥石流灾害的时间关联性。结果表明,湿度指数是决定泥石流沟空间格局的最主要因子,其次是高差势能和土壤厚度,多年平均分布的降水特征对泥石流沟分布的影响较小。泥石流灾害事件与降水特征的时间关联具有较大的区域异质性。泥石流发生地的激发雨量、湿度指数、高差及土壤厚度的统计分布在不同地貌、地质和气候单元中有明显差异。这表明泥石流预警不仅需要考虑雨量等激发因子,还必须考虑其他影响因素的空间差异性。     

基于ANN-CA模型的黄土小流域正负地形演化模拟

黄土高原正负地形的不同组合特征反映了黄土地貌的发育程度,黄土小流域正负地形的演化则是黄土高原地貌形态发育的缩影。该文采用地理元胞自动机的建模方法,对室内黄土小流域正负地形的演化过程进行建模与模拟。实验通过多次训练神经网络,自动获取转换规则,简化了构建元胞自动机模型的难度,同时,模拟的结果总精度达88.5%。研究表明,该方法可以反映黄土小流域正负地形演化过程中其沟谷扩张、沟头向前以及黄土陷穴的发育特点,对黄土高原地貌发育研究具有重要意义和可鉴性。     

基于RILBP的地形结构尺度稳定特征分析

地形结构描述着地表起伏的形态结构,而高低起伏的地形结构又组成了丰富多样的地貌景观。地表形态一般呈现出局部形态相似与区域有序分异的尺度特征。现有的地形尺度研究不能有效地刻画地形结构的尺度特征,地貌形态的适宜表达尺度及地形结构的尺度稳定特征仍值得进一步探讨。该文以黄土高原不同地貌类型区为例,以数字高程模型(DEM)为数据源,从刻画地表形态的局部特征入手,系统地选取了多类具有代表性的地貌形态样本数据,分析了典型地貌类型区域的局部二值模式(LBP)分布特征。考虑到地形结构与RILBP之间一对多的对应关系,利用顾及旋转不变特性的LBP(RILBP)算法探究地形结构的尺度稳定特性,发现随着分析窗口增大,LBP显示出逐渐趋于稳定的尺度特征。研究结果表明,RILBP能够有效地表达地形结构,地形结构稳定单元能够有效地反映适宜的地形分析尺度,地形结构对地形多尺度信息的挖掘具有独特的优势。     

空间关联规则在土地利用与地形特征关系研究中的应用

空间关联规则是空间数据挖掘的重要内容,其结果表明了各种空间对象之间的关联关系．本研究以福州地区作为试验区,以DEM、坡度、坡向等地形特征以及2009年福州地区土地利用现状作为基础数据,利用Apriori算法从中提取出地形特征与土地利用现状之间的关联关系,讨论并分析两者之间关联规则的提取结果及空间关联规则提取方法的优缺点;研究结果表明了2009年福州地区的土地利用现状分布,即林地多,耕地、住宅用地等偏少的情况,林地分布在各种地形上且与坡向之间无强关联性;而且对于不同的最小置信度和支持度,该算法所提取的结果有所不同,如何提高算法效率、合理的设置最小置信度和支持度以及提取结果的评价与解释等将是今后进一步研究的重点．     

川藏公路安久拉山至古乡段雪崩分布规律

根据对川藏公路安久拉山至古乡段调查所得的90处雪崩资料,运用统计方法得出研究区雪崩的分布情况。通过对该区灾害的发育与流域地貌的相关关系分析,发现安久拉山至古乡段的雪崩分布规律与地貌特征因子之间具有以下特性:1.雪崩主要分布在上游4 300~4 900 m峡谷地貌区段,海拔过高和过低较少发育;2.雪崩分布相对高差在300~1 100 m,占总数的74.44%;3.雪崩主要分布地形坡度为30°~40°,大于或小于这个范围较少发育;4.雪崩主要分布在阳坡。     

DEM 点位地形信息量化模型研究

针对DEM 点位, 首先应用微分几何法对其所负载的语法信息量进行测度, 其次根据地形特征点类型及地形结构特征确定其语义信息量, 然后基于信息学理论构建了DEM 点位地形信息综合量化模型。在此基础上, 以黄土丘陵沟壑区作为实验样区, 对DEM 点位地形信息量提取方法及其在地形简化中的初步实例应用进行了探讨和验证。实验结果显示, 所提出的DEM 点位地形信息量化方案可行;基于DEM 地形信息量指数的多尺度DEM 构建方案, 具有机理明确、易于实现的特点, 并通过优先保留地形骨架特征点, 可以有效减少地形失真, 从而满足不同层次的多尺度数字地形建模和表达要求。对DEM 点位地形信息进行有效量化, 为认识DEM 地形信息特征提供了一个新的切入点, 同时为多尺度数字地形建模提供理论依据与方法支持。     

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。     

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.     

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.     

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.     

Impact of sampling intervals on the reliability of topographic variables mapped from grid DEMs at a micro-scale

This paper explores the quantitative relation between the reliability of slope aspect, gradient, and form mapped from a gridded DEM and the sampling interval (SI) of elevations. Grid DEMs initially interpolated from digitised contours at 10 m were sampled to five other resolution levels. The topographic variables mapped at these SIs were compared with those at 10 m. It is found that the reliability of mapped slope aspect and form is not significantly affected by SI. By comparison, the reliability of slope gradient is more susceptible to SI, especially if it is derived from a gently rolling terrain. Around 90% of the variation in the mapped slope aspect and gradient are accounted for by the inaccuracy of DEMs. A lower percentage exists for slope form. The stability of the mapped topographic variables can be reliably predicted from SI and terrain complexity.     

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。     

地形信息对确定DEM适宜分辨率的影响

分辨率会直接影响基于栅格数字高程模型（DEM）的数字地形分析结果,因此在实际应用中,需要选择适宜的DEM分辨率。目前采取的基本方法,基于某种地形信息定量刻画尺度效应曲线,从而确定DEM适宜分辨率,但对于采用不同地形信息时所产生的影响尚缺乏研究。本文针对该方法中通常采用的坡度、剖面曲率、水平曲率等3 种地形信息,每种地形信息提取时,分别使用两种不同的常用算法,在3 个不同地形特征的研究区中,逐一计算其在不同分辨率下的局部方差均值,以刻画尺度效应曲线,确定相应的DEM适宜分辨率,并进行对比分析。结果表明：① 采用剖面曲率或水平曲率所得适宜分辨率结果基本相同,但采用坡度所得出的适宜分辨率结果则有明显差别,后者所得的适宜分辨率更粗;② 采用不同地形信息时,越是在平缓地形为主的研究区,所得的适宜分辨率结果越相近,在复合地形特征的研究区所得到的适宜分辨率区间均明显较宽;③ 地形属性计算时所用的算法对适宜分辨率结果的影响不明显。     

A study on DEM-derived primary topographic attributes for hydrologic applications: Sensitivity to elevation data resolution

Primary topographic attributes play a critical role in determining watershed hydrologic characteristics for water resources modeling with raster-based digital elevation models (DEM). The effects of DEM resolution on a set of important topographic derivatives are examined in this study, including slope, upslope contributing area, flow length and watershed area. The focus of the study is on how sensitive each of the attributes is to the resolution uncertainty by considering the effects of overall terrain gradient and bias from resampling. Two case study watersheds of different gradient patterns are used with their 10 m USGS DEMs. A series of DEMs up to 200 m grid size are produced from the base DEMs using three commonly used resampling methods. All the terrain variables tested vary with the grid size change. It is found that slope angles decrease and contributing area values increase constantly as DEMs are aggregated progressively to coarser resolutions. No systematic trend is observed for corresponding changes of flow path and watershed area. The analysis also suggests that gradient profile of the watershed presents an important factor for the examined sensitivities to DEM resolution.