基于SRTMv4的异龙湖流域地形因子提取

以最新SRTMv4版DEM作为基础数据,选择异龙湖流域为研究区域,利用ArcGIS 10平台中的水文分析扩展模块提取异龙湖流域的流域边界和流域水文特征两方面的流域地形因子。根据提取结果与获取到的实测数据进行有效性检验:①与实际调查数据的水系网和1∶5万水系图对照比较,发现基于SRTM DEM所提取出的流域地形因子等信息是合理有效的。②与1∶5万DEM所提取流域水网进行对比发现基于SRTM DEM所提取的数据精度较为满意,在相同河网密度情况下,基于SRTM的DEM与1∶5万DEM的水网细节表现高度一致,具有可靠性。     

基于信息熵的DEM最佳分辨率确定方法研究

分辨率是DEM的基本属性,它贯穿于DEM数据处理的每一个过程.利用合适的分辨率既可真实的反映地面特征,又可避免造成数据的冗余.本文尝试从信息论的角度出发,引入信息熵的概念来度量不同分辨率的DEM包含的地形信息量,得到地形信息熵随分辨率的变化曲线图.典型山地地区实验表明,利用1∶5万等高线插值生成DEM,当分辨率为20m时,DEM的地形信息熵基本趋于稳定,这说明DEM所包含的地形信息量基本达到饱和,由此,可认为此地区1∶5万DEM最佳分辨率为20m.     

适应地形实时生成的地形数据简化

出于对大范围地形场景实时生成的需要，提出了一种地形数据简化的方法。首先基于“分而治之”思想给出规则数据分割的概念，并给出数据分割算法，然后通过将地形数据的高度值解释为二维图像元素的灰度值，把地形数据变成平面图像，再利用数字图像处理的方法获得地形特征，提出了两种地形分类简化模型，即基于熵的地形类型划分模型和基于DEM数据统计特性的地形类型划分模型，最后比较了不同地形特征的数据简化结果。     

基于DEM的坡向提取算法对比分析——以黄土丘陵沟壑区的研究为例

在陕西绥德黄土丘陵沟壑区韭园沟流域25个样区(每个样区约4Km2),以1∶1万地形图制作的水平分辨率为5m的DEM为研究对象,采用6种不同算法分别提取坡向。运用方差分析、排序分析、比较分析等方法和信息论中熵的概念,通过比较不同算法所提取坡向的标准差、变异系数、坡向余弦中误差、不同坡向的面积数据、坡向提取所耗费的机器时间,认为在黄土丘陵沟壑区提取坡向选用三阶反距离平方权差分算法和三阶反距离权差分较为合理。根据实际生产部门需要,提出并实现了对坡向信息进行评价时必须分类别讨论的思路。研究可望为在本区域基于DEM提取准确的坡向信息时选择算法提供参考。     

数字高程模型坡度误差指标尺度转换分析

针对我国大比例尺DEM数据库尚未建成,但是国家的生产建设又需要1∶5 000DEM所提取的地形因子(如坡度),而目前少有对1∶5 000比例尺DEM转换研究的现状,该研究制定出适合福建全省不同比例尺DEM提取地形因子间互相转换标准。选取福建省典型地貌(山地、丘陵、平原)共7个样区为实验样区,使用python脚本来批量提取7个样区在5种比例尺DEM下的多种地形因子,选取坡度作为研究对象,提出适合中小比例尺DEM向大比例尺DEM转换的3个误差指标:坡度面积、坡度信息熵、坡度鉴别信息,得出1∶10 000、1∶50 000、1∶250 000、1∶500 000DEM所提取坡度因子向1∶5 000转换的定量表达式,制定出中小比例尺DEM提取坡度因子向大比例尺DEM对应因子的转换标准。     

基于DEM的小流域地质环境影响因素分析

基于DEM的三维地质实体建模对于流域开发的工程设计与决策具有十分重要的意义。运用数字地形分析技术对DEM进行处理分析以获取地形地貌信息,是对复杂景观资源和地质环境调查的重要手段。以青山小流域为例,应用ArcGIS软件中的空间分析工具提取地质环境特征因子。研究表明,坡度、地形起伏度、地表粗糙度等地形因子相关系数较高,对地质景观旅游资源开发影响显著。同时研究表明,此流域生态环境较为脆弱,应该加强环境整治与景观保护工作。     

一种基于熵的OBDD变量排序算法

有序二叉决策图（OBDD）是一种有效表示布尔函数的数据结构，其大小依赖于所采用的变量序。熵是定量描述布尔函数中变量重要性的一种方法。基于变量的熵值分析了高质量变量序的特征，给出了一种基于熵的OBDD变量排序算法。实验结果表明：该算法与模拟退火算法和遗传算法结果相当。时间仅为相应算法的80．84％和29．79％。     

自适应多特征融合的真实感地形快速绘制

针对真实地形可视化中数字高程模型(DEM)数据结构复杂且绘制速度不佳的问题,提出一种基于自适应多特征融合的真实感地形快速绘制方法.引入地形高程熵,对真实的DEM高程数据进行特征提取以生成地形总体框架;利用随机中点位移分形算法并根据地形特征优化分形参数来增加地形高频细节;计算视点与地形之间的距离阈值,并对应于层次细节(LOD)等级,以实现地形自适应的调度,再根据不确定性判定因子对地形特征进行更新.最后对本文算法进行并行处理,充分利用图形处理单元(GPU)技术对地形进行加速绘制.实验结果表明,该方法生成的地形具有较高逼真度和较好实时性.     

基于算术编码的格网DEM压缩技术综述

DEM是三维地形可视化基础,随着DEM数据量的不断增加,对DEM进行编码压缩已成为三维地形可视化的重要研究内容。算术编码是一种基于熵编码的无损压缩编码,能保留重要细节信息。目前基于算术编码的预测模型可分为简单线性预测、拉格朗日预测和最小二乘预测三类,对这三类算法进行了对比分析。指出了算术编码算法在实际运行中存在的问题,对其未来发展提出展望。     

一种新的基于信息论的PCA特征压缩算法

利用Shannon信息论理论，针对矩阵本征值的内在特性，提出了广义信息函数(GIF)、信息率(IR)和累计信息率(AIR)概念，用它度量了特征压缩的程度，建立了一种新的基于信息论的PCA特征压缩算法，并进行了仿真应用，为特征压缩提供了一种新的研究方法．     

NASA EOS Terra ASTER: Volcanic topographic mapping and capability

Up-to-date, accurate topographic data are a crucial resource for volcanic research and risk mitigation efforts, in particular, for modeling volcanic flow processes at a detailed spatial resolution. In this paper, we examine the utility of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument currently operating on the NASA Terra satellite, which provides near infrared (VNIR) stereo imaging from which topography can be derived. We wrote software to generate digital elevation models (DEMs) from the ASTER level 1A product, which employs an automated stereo matching technique to calculate the parallax offsets between the images acquired by the nadir- and aft-looking sensors. Comparison of ASTER DEMs with DEMs derived from other sources (digitized 1:50 K topographic maps and aerial interferometric radar) at Ruapehu volcano reveal an RMS error of about 10 m for the ASTER DEM, in the absence of significant atmospheric water vapor. A qualitative assessment of surface features showed that the ASTER DEM is superior to the interpolated 1:50 K map product but falls short of the detail provided by aerial interferometric radar, especially in terms of stream channel preservation. A second ASTER DEM was generated for Taranaki volcano, where previously only 1:50 K topographic map data were available. Although the 2000 Space Shuttle radar topography mission (SRTM) will largely remedy the previous global paucity of adequate topographic data at volcanoes, such as Taranaki, we anticipate the problem that at active volcanoes, the topography may change significantly following activity, rendering the SRTM data inaccurate. With the high temporal coverage of the dataset, ASTER not only provides a means to update significant (>10 m) topographic measurements at active volcanoes via a time-series of DEMs, but also provides a simultaneous means to map surface cover and localized land-use via the near infrared sensors. Thus we demonstrate the potential for up-to-date volcanic economic risk assessment using geographic information systems (GIS) analysis.     

多源外部DEM对两轨DINSAR测量结果影响分析

在总结两轨差分中参考DEM影响的最新研究成果基础上,以青藏高原上典型平地和山地作为研究区,利用理论上没有形变的ERS Tandem像对以及3种常用外部参考DEM（SRTM,ASTER GDEM,1∶5万DEM）,使用ROI_PAC软件进行两轨差分干涉试验。实例证明：SRTM更适合作为两轨差分中的外部参考DEM,并对此试验结果予以解释分析,即多源DEM数据质量的差异导致干涉图与DEM配准精度的不同,并最终反映在差分干涉相位误差中。本文研究结论对提高DInSAR处理精度有参考价值。     

Effect of differing DEM creation methods on the results from a hydrological model

It is known that digital elevation models (DEMs) can vary in quality depending on their method of creation. Six DEMs derived from digitised contours from the British Ordnance Survey were compared. The DEMs were used to run TOPMODEL for a small catchment in Devon. There were differences between the DEMs in the prediction of the catchment area and the spatial pattern of topographic index values, although these differences were reduced by smoothing the DEMs. Because runoff in the area is dominated by subsurface flow, many of the model predictions were not sensitive to differences between the DEMs. However, predictions of surface runoff differed by over 200%, and caused variations of up to 25% in the prediction of hourly flow values. The predicted spatial pattern of surface runoff was strongly affected by the presence of interpolation artefacts in the DEM, with completely unrealistic predictions in the case of the worst quality DEMs.     

Estimation of average DEM accuracy under linear interpolation considering random error at the nodes of TIN model

The concept of a digital elevation model (DEM) can be used for a digital representation of any single‐valued surface such as a terrain relief model (digital terrain model, DTM). DEMs are widely used in remote sensing, geographical information systems (GIS), and virtual reality. Estimating the accuracy of a DEM is an essential issue in the acquisition of spatial data, particularly for applications that require a highly accurate DEM, such as engineering applications. The accuracy of a DEM is subject to many factors such as the number of sampling points, the spatial distributions of the sampling points, the methods used for interpolating surface elevations, the propagated error from the source data, and other factors. Of these factors, this study will focus on estimating the mean elevation error in a DEM surface that is caused by errors of component nodes in a triangulated irregular network (TIN). This paper will present a newly derived mathematical formula, with the details of the procedure used to derive this formula, to study the relationship between the errors at the TIN nodes and the propagated mean elevation error of a DEM surface that is linearly constructed from the TIN. We have verified the analytical formula by numerical simulation. The experimental results confirm the theoretical derivation of the formula.     

Accuracy assessment of automatically derived digital elevation models from aster data in mountainous terrain

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite was designed to generate along‐track stereo images. The data are available at low cost, providing a feasible opportunity for generating digital elevation models (DEMs) in areas where little or no elevation data are yet available. This study evaluates the accuracy of DEMs extracted from ASTER data covering mountainous terrain. For an assessment of the achieved accuracies in the Andean study site, comparisons were made to similar topographical conditions in Switzerland, where reference data were available. All raw DEMs were filtered and interpolated by the post‐processing tools included with PCI Geomatica, the software package used. After carefully checking the DEM quality, further post‐processing was undertaken to eliminate obvious artefacts such as peaks and sinks. Accuracy was tested by comparing the DEMs in the Swiss Alps to three reference models. The achieved results of the generated DEMs are promising, considering the extreme terrain. Given accurate and well‐distributed ground control points (GCPs), it is possible to generate DEMs with a root mean square (RMS) error between 15?m and 20?m in hilly terrain and about 30?m in mountainous terrain. The DEMs are very accurate in nearly flat regions and on smooth slopes with southern expositions: errors are generally within ±10?m in those cases. Larger errors do appear in forested, snow covered or shady areas and at steep cliffs and deep valleys with extreme errors of a few hundred metres. The evaluation showed that the quality of the DEMs is sufficient for enabling atmospheric, topographic and geometric correction to various satellite datasets and for deriving additional products.     

Evaluating Shuttle radar and interpolated DEMs for slope gradient and soil erosion estimation in low relief terrain

The error in slope gradient estimates provided by digital elevation models propagates to spatial modelling of erosion and other environmental attributes, potentially impacting land management priorities. This study compared the slope estimates of Shuttle Radar Topographic Mission (SRTM) DEMs with those generated by interpolation of topographic contours, at two grid cell resolutions. The magnitude and spatial patterns of error in DEM slope, and derived erosion estimates using the Revised Universal Soil Loss Equation (RUSLE), were evaluated at three sites in eastern Australia. The sites have low-relief terrain and slope gradients less than 15%, characteristics which dominate the global land surface by area and are often highly utilised. Relative to a reference DEM resampled to the same resolution (a measure of DEM ‘quality’), the 90 m (3-s) SRTM DEM provided the best estimates of slopes, being within 20% for each 5% slope class outside alluvial floodplains where it over-predicted by up to 220%. Relative to a hillslope scale 10 m reference DEM, the 30 m (1-s) SRTM-derived DEM-S, provided slope gradient estimates slightly less biased towards under-prediction than the 90 m SRTM and significantly less biased on alluvial floodplains. In contrast, the 20 m vertical contour intervals underpinning the interpolated DEMs resulted in under-prediction of slope gradient by more than a factor of 5 over large contiguous areas (>1 km²). The 30 m DEM-S product provided the best estimate of hillslope erosion, being 3–4% better than the 90 m SRTM. The slope errors in the interpolated DEMs translated into generally poorer and less consistent erosion estimates than SRTM. From this study it is concluded that the SRTM DEM products, in particular the 30 m SRTM-derived DEM-S, provide estimates of slope gradient and erosion which are more accurate, and more consistent within and between low relief study sites, than interpolated DEMs.     

基于视觉特征的尺度空间信息量度量

图像的多尺度表示指的是从原始图像出发,导出一系列越来越平滑、简化的图像。这种简化意味着信息的丢失。如果能定量描述每一个尺度中图像的信息,这对于多尺度表示来说有着重要的作用。虽然Sporring等人提出的尺度空间信息熵度量能解决一些问题,但是并不满足从视觉理论和直观的基础上提出的尺度空间信息量度量的基本要求,例如形态不变性等,为此在M arr视觉理论基础上定义了一个新的具有视觉意义的尺度空间信息度量,并在典型的高斯尺度空间中,证明了它确实满足从视觉理论和直观的基础上提出的尺度空间信息量度量的基本要求。数值试验验证了这种定义在视觉上是可靠的,从而为图像尺度的自适应选择提供了一种可靠的方法。     

Impact of DEM accuracy and resolution on topographic indices

Topography is an important land-surface characteristic that affects most aspects of the water balance in a catchment, including the generation of surface and sub-surface runoff; the flow paths followed by water as it moves down and through hillslopes and the rate of water movement. All of the spatially explicit fully distributed hydraulic and hydrological models use topography (represented by the DEM of the area modelled) to derive bathymetry. DEM is also used to derive some other key information critical in fully distributed hydraulic and hydrological models.With high-resolution DEMs such as LiDAR (Light Detection and Ranging) becoming more readily available and also with the advancements in computing facilities which can handle these large data sets, there is a need to quantify the impact of using different resolution DEMs (e.g. 1 m against 10 m or 25 m) on hydrologically important variables and the loss of accuracy and reliability of the results as we move from high resolution to coarser resolution.The results from statistical analysis carried out to compare field survey elevations with the LiDAR DEM-derived elevations, show that there are small differences between the two data sets but LiDAR DEM is a reasonably good representation of the actual ground surface compared to other commonly used DEMs derived from contour maps.The results from the analysis clearly show that the accuracy and resolution of the input DEM have serious implications on the values of the hydrologically important spatial indices derived from the DEM. The result also indicates that the loss of details by re-sampling the higher resolution DEM to coarser resolution are much less compared to the details captured in the commonly available coarse resolution DEM derived from contour maps. Topographic indices based on contour derived DEMs should be used with caution and where available, the higher resolution DEM should be used instead of the coarse resolution one.     

Evaluating and comparing performances of topographic correction methods based on multi-source DEMs and Landsat-8 OLI data

Topographic correction is a crucial and challenging step in interpreting optical remote-sensing images of extremely complex terrain environments due to the lack of universally suitable correction algorithms and digital elevation models (DEMs) of adequate resolution and quality. The free availability of open source global DEMs provides an unprecedented opportunity to remove topographic effects associated with remote-sensing data in remote and rugged mountain terrains. This study evaluated the performances of seven topographic correction methods including C-correction (C), Cosine C-correction (CC), Minnaert correction (M), Sun–canopy–sensor (SCS) correction (S), SCS+C-correction (SC), Teillet regression correction (TR), and the Terrain illumination correction model (TI) based on multi-source DEMs (local topographic map, Shuttle Radar Topography Mission (SRTM) DEM filled-finished A/B and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) global digital elevation model (GDEM) data sets) and Landsat-8 Operational Land Imager (OLI) data using visual and statistical evaluation strategies. Overall, these investigated topographic correction methods removed topographic effects associated with Landsat-8 OLI data to varying degrees. However, the performances of these methods generally depend on the use of different DEMs and evaluation strategies. Among these correction methods, the SCS+C-correction performed best and was less sensitive to the use of different DEMs. The performances of topographic corrections based on free and open-access DEMs were generally better than or comparable to those based on local topographic maps. In particular, the topographic correction performance was greatly improved using the SRTM filled-finished B (FFB) data set with a resampling scheme based on the average value within a 3 × 3 pixel window. Nevertheless, further quantitative investigation is needed to determine the relative importance of DEMs and evaluation strategies used to select topographic correction methods.     

An assessment of shuttle radar topography mission digital elevation data for studies of volcano morphology

The Shuttle Radar Topography Mission has provided high spatial resolution digital topographic data for most of Earth's volcanoes. Although these data were acquired with a nominal spatial resolution of 30 m, such data are only available for volcanoes located within the U.S.A. and its Territories. For the overwhelming majority of Earth's volcanoes not contained within this subset, DEMs are available in the form of a re-sampled 90 m product. This has prompted us to perform an assessment of the extent to which volcano-morphologic information present in the raw 30 m SRTM product is retained in the degraded 90 m product. To this end, we have (a) applied a simple metric, the so called dissection index (di), to summarize the shapes of volcanic edifices as encoded in a DEM and (b) using this metric, evaluated the extent to which this topographic information is lost as the spatial resolution of the data is reduced. Calculating di as a function of elevation (a di profile) allows us to quantitatively summarize the morphology of a volcano. Our results indicate that although the re-sampling of the 30 m SRTM data obviously results in a loss of morphological information, this loss is not catastrophic. Analysis of a group of six Alaskan volcanoes indicates that differences in di profiles calculated from the 30 m SRTM product are largely preserved in the 90 m product. This analysis of resolution effects on the preservation of topographic information has implications for research that relies on understanding volcanoes through the analysis of topographic datasets of similar spatial resolutions produced by other remote sensing techniques (e.g., repeat-pass interferometric SAR; optical stereometry).