基于等高线隔断线确定DEM适宜分辨率的方法研究

分辨率是等高线数据插值生成格网DEM数据过程中需要考虑的一个重要参数,适宜的分辨率既能将等高线高程信息尽可能保留,又不会因插值造成数据冗余及误差。基于对格网DEM生成方式的理解,提出了等高线隔断线的相关概念,分析了基于地形图矢量化的等高线数据插值生成格网DEM数据,由不同长度等高线隔断线频率统计来确定格网适宜分辨率参考值的方法。同时,不同长度等高线隔断线的长度与其频率相乘得到标准长度,以及等高线隔断线中心点生成的密度分析图,均可在频率特征决定适宜分辨率参考值时起到一定的参考作用。通过样区实验验证,实现简便,可度量性强,与其他相关研究具有一致性,对确定适宜格网分辨率参考值具有一定的借鉴意义。     

最佳DEM分辨率的确定及其验证分析

在玛尔挡地区格网DEM的数据上选择实验样区,以不同分辨率情况下DEM数据对地表模拟表达的逼近程度为研究对象,最优逼近时的栅格单元大小的临界值就是所求的最佳分辨率。在分析坡度中误差法和公式法等常见方法的基础上,借鉴坡度中误差的思想,选取区域地形粗糙度K、剖面线长度SL两个定量指标来综合分析确定该地区格网DEM的最佳分辨率。在ArcGIS平台上对方法进行了实验验证,得出分别以2m和8m作为玛尔挡地区1∶10 000和1∶50 000 DEM生产时是最佳分辨率的结论。研究表明这种解决办法不仅可以克服GIS空间分析中DEM分辨率确定的盲目性和随意性,而且能确保基于DEM的各种空间分析的精度,为相关研究提供重要的参考价值。     

基于重构等高线的格网细化模型

以规则格网DEM为基础,利用回放等高线与原等高线进行比较,提出两个误差指标和一种格网细化模型,以生成多分辨率的格网DEM,并提高DEM的等高线精度。针对该模型的两个关键步骤,进行了较为详细的论述。通过对一幅实际地形数据进行试验,比较不同方法得出的DEM等高线精度,为DEM精度研究,特别是多分辨率DEM精度研究,提供了一种新的方法和思路。     

数字高程模型地形描述精度量化模拟研究

在首先提出数字高程模型（DEM）地形描述误差（Et)概念的基础上，以我国5个不同地貌类型区为试验样区，采用比较分析的方法，研究EDEM地形描述误差的成因、影响因素、量测方法以及误差的数学模拟途径。统计分析的结果证明DEM地形描述误差与DEM空间分辨率及其地面粗糙度之间存在着线性相关关系，回归分析结果显示，DEM地形描述误差Et的均方差RMS值可以表达为DEM水平分辨率（R）与地面垂直曲率（V）的函数：RMS Et=(0.0063V 0.0066)R-0.022V 0.2415。该结果可用以估算估算所建立的DEM的地形描述精度，也为确定适宜的DEM分辨率提供了理论依据。     

一种顾及地形复杂度的LiDAR点云多尺度滤波方法

针对复杂地形区域的机载LiDAR数据滤波方法中自适应阈值设置问题,根据地形多尺度效应,提出一种自适应阈值的机载LiDAR点云多尺度滤波方法。该方法采用影像金字塔策略按分辨率从高至低逐级构建LiDAR点云分层格网,滤波过程则从最大尺度格网(顶层格网,最低分辨率)开始,采用局部统计分析的方法自适应地确定高差阈值,同时结合薄板样条内插出下层各格网控制点的高程值,直至最底层格网完成原始激光点云滤波。通过我国某山区城市复杂地形的LiDAR数据实验表明顾及地形复杂度的LiDAR点云多尺度滤波方法能够快速有效地提取高精度DEM,能够满足实际生产需求。     

等高线套合差及在DEM质量评价中的应用研究

DEM再生等高线与原始数字化底图等高线的套合检查,是目前基于等高线生产DEM中质量检查的主要方法。针对该方法在自动判读及定量评价方面的不足,首次提出等高线套合差的概念,阐述套合差的自动计算与分析方法,并在此基础上,以地形较为复杂多样的黄土丘陵沟壑区为实验样区,研究等高线套合差在评价DEM质量上的应用条件、应用方法与效果。通过用等高线套合积差、超限区个数比、系统偏差等几个测算因子定量检查DEM数据质量,不仅能反映DEM的精度特征,也能有效揭示误差的空间分布,模型更为全面,易于实现自动获取,是一种评价DEM质量的有效方法。     

小波派生多尺度DEM的精度分析

利用陕北5 m分辨率DEM数据为基本数据,对Haar小波派生出一系列更低分辨率DEM进行复合精度分析。通过等高线套合、数据中误差以及表面重合指数等方法,分析其高程采样误差与空间分布;通过分析对比其在所提取的地面坡度、沟谷网络等地形因子上的差异,分析其地形描述误差。研究结果显示:小波派生多尺度DEM在精度的颓减上呈现指数形的变异规律,当达到三级重构DEM(40 m分辨率)时,其精度仍优于1:5万(25 m分辨率)DEM。该结果对于实现地形的有效简化与掌握多尺度DEM不确定性规律具有一定的意义。     

基于DEM增强黄土典型地貌表达效果的方法研究

基于黄土典型地貌类型样区高分辨率DEM数据(5 m分辨率),及其衍生出的系列地形信息图层(山体阴影图、明暗等高线、坡度变率图、坡向变率图、地表曲率图),设计了针对黄土典型地貌、增强信息表达的制图方案。结果表明,山体阴影图与明暗等高线的叠加,可保留表达的真实感,增加地形计量化信息,在黄土塬区效果较好。山体阴影图与上述其他图层叠加,增强了对坡面纹理特征的刻画,在丘陵沟壑的表达效果较好。     

不同空间尺度DEM地形信息容量综合对比研究

DEM包含了大量地形信息,是进行地形分析的基本数据。由于DEM数据的多尺度因素,加之地形、地貌特征具有宏观性与区域分异性的特点,不同尺度下的DEM地形信息容量具有较大的差异。本研究选取黄土高原地区的绥德、佳县、富县和宜君县四个实验样区,以Arc view/GIS软件为技术平台,提取了基于DEM数据的地形因子,并运用比较分析与数理统计的方法,对地形因子的提取结果进行了分析,获取了单一值因子的量化表达模型,确定了DEM地形信息容量与分辨率、地域及比例尺之间的量化相关关系,并在此基础上分析了DEM地形信息容量在不同空间尺度上的分异规律。     

基于规则格网DEM的等高线提取算法的优化与实现

随着DEM数据获取质量的日渐提高,利用规则格网DEM准确快速地提取等高线已经成为等高线自动绘制及DEM精度评估的重要方法之一。本文在传统算法的基础上,提出了遍历状态值、中心点符号法、"视点"等概念,分别对格网遍历原则、等高线走向二义性问题及等高线方向一致性处理等方面进行了优化,并使用C++语言在VC++6.0集成开发环境中实现了该算法。     

基于栅格DEM的地形特征提取与分析

以陕北延安地区燕儿沟流域为实验样区,运用比较分析法和数理统计法进行基于栅格DEM的地形特征提取和分析,以及DEM分辨率对地形特征的影响,并计算和比较了地形特征的空间统计分布。研究表明:一个相对真实的DEM能够通过修改生成DEM的基本材料,以及对DEM进行再加工而获得。由于DEM分辨率的不同,由此得到的地形特征值(如坡度、地形指数、河网密度等)在统计特性上也会随之变化。随着DEM分辨率的降低,坡度减小,地形坦化,地形指数均值变大,流域总面积变大,子流域数量减少,河流总长度减小,河网密度降低。     

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.     

An improved ANUDEM method combining topographic correction and DEM interpolation

Void filling and anomaly replacement in conjunction with auxiliary sources of data have been widely used to improve the quality of existing problematic high-resolution digital elevation models. However, the traditional interpolation methods used for this purpose have always failed to eliminate the discrepancies between different data-sets. In this paper, an improved ANUDEM method is presented for DEM interpolation, which incorporates the idea of topographic correction using high correlation of topological structure between contour lines (CLs) from multi-scale digital elevation models (DEM). Firstly, the terrain topological structure is extracted from the CLs of a low-resolution DEM. The topographic surface correction is then undertaken based on the extracted structure, which recovers the topographic information of the sharp depressions and eminences to fit the high-resolution representation. Finally, the breaklines of the terrain surface are distilled and integrated into the denser DEM generation. The experiments undertaken confirmed the superiority of the proposed method over the other DEM interpolation methods. It is shown that the proposed method can provide results with a higher accuracy, as well as a better visual quality.     

基于主成分变换模型的DEM格网聚合及其误差分析

利用主成分分析揭示变量之间关系的特性,进而提出一种既能保证较高精度又能较好地保持地形形态特征的DEM格网聚合方法。首先根据主成分变换模型推导DEM格网聚合数学公式,构建主成分聚合模型;然后以30m分辨率DEM转换为90m分辨率DEM为例,根据格网点属性间的权重关系聚合重构DEM。在此基础上,以均值聚合和双线性重采样聚合方法为比较对象,从聚合前后的检查点高程偏差的统计描述、空间分布与自相关性、地形形态保持程度方面分析3种聚合策略下重构DEM的误差特性。最后运用描述统计、半变异分析和等高线套合方法,定量评价主成分聚合重构DEM的质量效果。试验分析结果表明,同均值聚合和重采样聚合相比较,该方法重构的DEM既能保持较高精度,又能很好地保持地形形态特征。     

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.     

基于杨赤中滤波推估法的地形剖面分析的设计与实现

应用杨赤中滤波推估法,将地形碎部点高程观测值经插值转换为格网DEM数据,并利用VB和MapInfo来实现其立体等高线的绘制功能。在此基础上,阐述其地形剖面分析功能的设计与实现。最后通过实验比较,验证了基于杨赤中滤波推估法的地形剖面分析能取得较好的效果。     

DEM空间尺度对岷江上游流域特征提取的影响

DEM分辨率是描述DEM地形精确程度的一个重要指标,同时也是决定DEM使用范围的一个主要影响因素。此处以岷江上游流域为研究区,Arc GIS为技术支撑,分析DEM空间尺度对流域特征提取的影响。首先,采用7组不同分辨率的DEM数据,通过5类不同特征参数的提取来进行DEM尺度效应的定量分析。其次,借鉴坡度中误差法思想和信息熵理论,综合分析高程、坡度和地面粗糙度来确定该地区DEM研究的分辨率合理范围。结论表明:随着DEM栅格大小的不断增大,高程区间和坡度随之减小;地面粗糙度的减小表现出地形的平坦化;信息熵所包含的内容减少;河网总长度和河网密度也随之变短变稀疏。文中岷江上游流域特征提取研究的DEM最佳空间分辨率区间为30~60 m。     

基于空间插值彩色扫描地形图等高线的自动矢量化

本文主要描述了一种基于彩色扫描地形图等高线的自动提取以及自动矢量化的方法,提出了通过空间插值解决等高线不连通问题的新方法。首先利用图像分割方法分色提取出栅格等高线,自动矢量化等高线(CLs1),然后对这些不连续的等高线赋值,结合其他地形要素(高程点、山脊线、山谷线等)创建DEM,从DEM中提取等高线(CLs2),最后利用提取出的等高线(CLs2)修正从地形图中自动矢量化得到的等高线(CLs1),得到连通的矢量化等高线。通过实验证明此方法是有效的,提高了等高线自动化程度。     

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.     

坡度随水平分辨率变化及其空间格局研究

以黄土丘陵沟壑区的县南沟流域为研究区,基于1∶1万地形图,利用ANUDEM软件生成5m到200m分辨率DEM,并利用Arc/Info中计算坡度的方法提取了各种分辨率的坡度。研究表明,随着DEM分辨率的降低,单个样点坡度值表现出不确定性,但同一坡度级所有栅格点的坡度均值呈现一定的规律性,低坡度段表现为先升高后降低,中坡度段呈现微弱变化,陡坡度段呈现对数降低趋势;沟沿线上坡度值呈比较剧烈的下降趋势、分水线和流水线上坡度缓慢下降。