基于DEM的坡度坡向误差空间分布特征研究

研究DEM误差和坡度坡向误差的关系,澄清目前关于坡度坡向误差空间分布的矛盾观点,明确指出基于DEM提取的坡度坡向误差主要分布在平坦地区,并通过实验对结论进行验证,所得结论对实际工作有一定的指导意义.     

二、P21 普通测量学、地形测量学

CH20082004顾及DEM误差自相关的坡度计算模型精度分析=The Accuracy Assessment on Slope Algorithms with DEM Error Spatial Autocorrelation/刘学军,卞璐,卢华兴,朱莹(南京师范大学虚拟地理环境教育部重点实验室)//测绘学报.-2008,37(2).-200～206基于DEM的坡度计算,其误差来源于DEM误差、DEM结构和坡度计算模型.在顾及DEM误差自相关的前提下,对4种DEM坡度计算模型进行了分析和评价。研究表明,三阶不带权差分能给出较高的坡度计算精度;在局部窗口中,格网点数量越多,坡度计算越准确;等权比不等权的坡度计算模型更准确;DEM误差自相关结构形     

顾及DEM误差自相关的坡度计算模型精度分析

基于DEM的坡度计算,其误差来源于DEM误差、DEM结构和坡度计算模型。在顾及DEM误差自相关的前提下,对四种DEM坡度计算模型进行了分析和评价。研究表明,三阶不带权差分能给出较高的坡度计算精度;在局部窗口中,格网点数量越多,坡度计算越准确;等权比不等权的坡度计算模型更准确;DEM误差自相关结构形式对坡度计算无影响。进一步的理论分析和试验分析还表明：DEM误差自相关性的存在,不仅能够改善地形分析的精度,也能改善DEM自身精度。     

基于坡度和坡向分析的DCT域DEM数字水印算法

提出了一种基于离散余弦变换(discrete cosine trasform,DCT)域的数字高程模型(DEM)数字水印算法,通过分析坡度坡向计算模型并结合人类视觉系统(human visual system,HVS),推导出坡度坡向精度与水印嵌入强度的数学关系,能实现在满足坡度坡向精度要求下,水印嵌入强度的最大化,增强水印的抗攻击性。实验结果表明,含水印DEM的高程、坡度、坡向的最大误差和中误差均较小,满足DEM精度的近无损及所提取等高线的近无损,且满足水印的视觉不可见性,能抵抗JPEG压缩和几何裁剪攻击。     

关于DEM的高程、坡度、坡向精度评估

本文在南部Appalachian山区的Blacksubury,Virginia中心地区的两个DEM上评估了高程、坡度、坡向的精度。第一个是美国地调局(USGS)在30m格网7.5分的方形图幅上使用Gestalt Photomapper(GPM)仪器,根据1:40000落叶期的航空像片自动立体相关处理完成的。同一地区的第二个DEM,是利用STX公司设计的专业立体相关技术,处理SPOT全色波段立体像对取得的,其间利用SPOT图像公司高解像力的DEM产品,对于DEM高程、坡度、坡向的精度进行了目视评估,并与野外测量获取的高程、坡度、坡向值进行了比较,USGS用GPM获取的DEM在微观地貌表现方面要好一些,而USGS—GPM和SPOT—STX两个DEM的高程差平均值小于6m,且误差分布中心未显著偏离零值,满足1级精度要求。从SPOT—STX的DEM所导出的,在坡度、坡向的统计上表现出一些显著的大误差,而USGS—GPM的坡度、坡向误差发布中心未显著偏离零值。在坡度、坡向与它们各自的误差之间有显著的大的相关性。本文很少的关于DEM导出的坡度、坡向以及高程的评估之一。读者会注意到这些结论不一定适用于不同的DEM生成方式、算法以及不同地形和植被情形的地区。     

插值条件下格网DEM坡度计算模型的噪声误差分析

针对目前DEM（Digital Elevation Model, DEM）数字地形分析的精度评价多数不考虑DEM误差的空间自相关性或仅仅采用经验的自相关性模型问题,本文从DEM插值入手,从理论上推导了插值条件下格网DEM邻域窗口内坡度噪声误差的空间自相关性模型以及坡度精度模型,并选取典型的插值方法和坡度差分算法,从实验角度分析了在顾及和不顾及空间自相关性两种情况下的格网DEM坡度计算模型的噪声精度,实验结果表明：坡度精度受DEM噪声误差的空间自相关性影响较大,并与DEM插值方法和坡度计算模型中的差分算法有关。     

格网DEM坡度计算模型的相似性研究

当DEM的精度和分辨率确定后,坡度坡向计算结果取决于计算模型。本文设计了逐栅格单元的相对差等级评价方法,并结合基于整体的频率图和XY散点图评价指标,定量揭示了坡度计算模型之间的异同。主要结论为:①坡度计算模型有离散和连续之分,连续型模型能给出更加符合实际的坡度坡向计算结果;②坡度计算结果与计算点数有关,点数越多,计算结果越稳定;③算法间的差异随DEM分辨率的增大而增大。最后本文给出了实际应用中的坡度计算模型。     

基于DEM的西北干旱区坡度提取分析

简要介绍了DEM及其获取方法以及坡度计算方法,通过选取西北干旱区具有代表性的丘陵地和平地作为试验区,建立数字坡度模型,研究了不同分辨率的DEM提取坡度的变化规律,并对坡度提取误差进行了分析,对西北干旱区进行与坡度有关的生态环境建设具有一定的参考价值。     

不同DEM插值算法对提取坡度和坡向的影响研究

针对数字高程模型数据的精度与内插算法的有关问题,分别选取反距离加权插值算法、径向基函数插值算法、最近邻点插值法和克里格插值算法生成DEM。根据插值参数对插值精度的影响不同,选择插值参数为研究对象,然后运用交叉验证法与方差分析等试验方法来研究插值参数与DEM精度的关系,以便得到合理插值参数,并通过对不同插值算法生成的DEM计算坡度坡向面积,分析不同内插算法对坡度坡向的面积变化规律。通过研究发现,不同的内插算法主要是对小坡度区域(15°)有影响,而坡度较大(15°)时没产生显著的影响。不同插值算法生成的DEM提取的坡向主要在平坦地区有显著的影响。     

DEM坡度、坡向的有效尺度范围

采用曲面矢量合成方法,通过比较点位上的坡度、坡向的矢量值与以点为中心、一定范围地形曲面上的矢量值,进行了DEM坡度、坡向的有效尺度范围研究。结果表明,格网中心点上计算得到的坡度、坡向所代表的范围是DEM分辨率的1.7~2.7倍。这种规律在不同的地貌样区是普遍存在的,且不受DEM分辨率的影响。     

Satellite stereo data for dem surfaces and derivatives

Various attributes can be derived from Digital Elevation Model (DEM), which are essential to analyze watershed physical characteristics. This paper discusses utility and accuracy of satellite DEM surfaces and their derivatives. Facilities available in various software packages were compared to generate DEM from satellite data and other sources. For test site at Chamba, Uttaranchal, DEMs produced from various algorithms were evaluated for accuracy of surface and its derivatives. Most of the algorithms have shown correlation coefficient of 0.99 and above but the desirable maximum error in spot height (1/5 of contour interval) is not achieved. Slope and aspect produced from various algorithms were comparable around 70-80%. Comparison of DEM surface and its derivatives were attempted for test sites at Shimla and Nahan using IRS-1C and SPOT PAN stereo pair, respectively. Model accuracy has shown that error in height is higher than planimetry. Surface derivatives from stereo DEM for Shimla and Nahan test sites have shown an overall accuracy of 56.5% and 59.2% for slope; 49.79% and 71.21% for aspect and 74.15% for topographic level slicing, respectively. Accuracy has improved when observed class value was lowered or put-up by one unit.     

Effect of sensor modelling methods on computation of 3-D coordinates from Cartosat-1 stereo data

The orbital and the rational polynomial coefficients (RPC) models are the two most commonly used models to compute a three-dimensional coordinates from an image stereo-pair. But it is still confusing that with the identical user provided inputs, which one of these two models provides more accurate digital elevation model (DEM), especially for mountainous terrain. This study aimed to find out the answer by evaluating the impact of used models on the vertical accuracy of DEM extracted from Cartosat-1 stereo data. We used high-accuracy photogrammetric DEM as the reference DEM. Apart from general variations in statistics, surprisingly in a few instances, both the DEMs provided contrasting results, thus proving the significance of this study. The computed root mean square errors and linear error at 90% (LE90) were lower in case of RPC DEM for various classes of slope, aspect and land cover, thus suggesting its better relative accuracy.     

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.     

Landscape drainage modelling to enhance Landsat classification accuracies

Studies integrating digital elevation models (DEMs) with multispectral digital satellite data have typically concentrated on geographic areas characterized by moderate to high topographic relief. Variables such as elevation, slope gradient and aspect contribute most significantly to the zonation of vegetation in these environments. In areas where relief is low, vegetation zonation is based not on individual form elements but rather on physical processes. The purpose of this research was to investigate the potential of integrating multispectral and ancillary process data in such a low relief environment. For this a study area was chosen in the Boreal forest of west central Alberta where the zonation of vegetation is based, to a large extent, on landscape drainage. An initial classification of forest cover based on Landsat multispectral data yielded overall classification accuracies of 58%. A DEM was developed from a digitized 1:50,000 topographic map sheet. The differential geometry of the DEM was mapped as a series of coverages: slope, aspect, and directional curvatures (down ‐ and across slope). Two additional coverages, relief and flow paths, were also developed and mapped. A data set was extracted from the DEM through which landscape drainage could be evaluated. A univariate analysis of drainage using the form variables resulted in a 45% to 47% explanation of the observed variation. Multivariate analysis combining slope gradient, across and down slope curvatures, relief, and flow paths increased the explanation to 68%. The MSS data were reinterpreted integrating the DEM ‐ based landscape drainage model. The resulting classification accuracy was increased to 73%.     

栅格DEM的水平分辨率对地形信息的影响分析

数字高程模型（DEM）是当前用于地形分析的主要数据源,可以从DEM提取不同的地形因子得到地形信息为各种地学分析提供基础服务。对三峡库区应用6种不同网格分辨率进行地形因子数据的提取和分析。研究表明,DEM的水平分辨率对地形信息的精确性有影响,网格的增大增加了DEM对地形信息的概括．应根据不同的需要选择不同分辨率的DEM。     

InSAR DEM精度与地形特征的关系分析

为研究InSARDEM与地形特征的关系,本文以从不同空间位置获取的两幅SAR影像作为实验数据,将InSARDEM与USGSDEM进行比较,分析了InSARDEM的精度,并研究其与坡度、坡向之间的关系。结果表明,本次实验InSARDEM与USGSDEM高程差异中误差为+19.11m,其精度与地形特征强烈相关,随着坡度的增加,InSARDEM精度降低,且前坡处高程精度高于后坡。     

基于填挖方分析的DEM精度评价模型

针对DEM高程中误差评价指标的不足,提出了一种基于填挖方分析的DEM精度评价模型以及计算方法,将DEM填挖方误差E_c定义为待评价DEM与参考DEM在同一区域的三维体积差异和与该区域面积之商。探究了DEM填挖方误差和DEM分辨率R以及地形平均坡度S之间的关系,得到DEM填挖方误差的定量估算模型为E_c=0.004 8·R·S。实验表明,模型估算精度达95.85%以上。该模型为在不同地形条件下,确定满足限差要求的DEM分辨率提供了依据。     

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。