数字高程模型在流域水系拓扑结构计算中的应用

简要回顾了利用数字高程模型自动提取流域水系的方法,着重介绍了Martz和Garbrecht开发的数字高程流域水系模型(DEDNM)的基本原理、模型结构、计算流程,包括数字高程模型中凹陷区域的识别和消除、平坦部位水流流向设定、流域分水线勾划、河网生成、河网与子流域编码及河网结构拓扑关系的建立,并将其应用于淮河史灌河流域--全球能量与水分循环亚洲季风试验强化观测区。结果表明该模型能够很好地自动生成流域水系,从而为分布式水文模型的开发研制提供了坚实的基础。     

How Different Analysis and Interpolation Methods Affect the Accuracy of Ice Surface Elevation Changes Inferred from Satellite Altimetry

Satellite altimetry has been widely used to determine surface elevation changes in polar ice sheets. The original height measurements are irregularly distributed in space and time. Gridded surface elevation changes are commonly derived by repeat altimetry analysis (RAA) and subsequent spatial interpolation of height change estimates. This article assesses how methodological choices related to those two steps affect the accuracy of surface elevation changes, and how well this accuracy is represented by formal uncertainties. In a simulation environment resembling CryoSat-2 measurements acquired over a region in northeast Greenland between December 2010 and January 2014, different local topography modeling approaches and different cell sizes for RAA, and four interpolation approaches are tested. Among the simulated cases, the choice of either favorable or unfavorable RAA affects the accuracy of results by about a factor of 6, and the different accuracy levels are propagated into the results of interpolation. For RAA, correcting local topography by an external digital elevation model (DEM) is best, if a very precise DEM is available, which is not always the case. Yet the best DEM-independent local topography correction (nine-parameter model within a 3,000 m diameter cell) is comparable to the use of a perfect DEM, which exactly represents the ice sheet topography, on the same cell size. Interpolation by heterogeneous measurement-error-filtered kriging is significantly more accurate (on the order of 50% error reduction) than interpolation methods, which do not account for heterogeneous errors.

     

数字高程模型信息提取与数字水文模型研究进展

回顾了数字高程模型(DEM)数据的信息提取方法,阐述了由DEM提取的信息在水文水资源领域应用的现状,探讨了数字模型在水文科学中的作用和数字水文在数字地球所处的地位及应用前景。     

Evaluation of Interpolation Accuracy of Neural Kriging with Application to Temperature-Distribution Analysis

An interpolation method based on a multilayer neural network (MNN), has been examined and tested for the data of irregular sample locations. The main advantage of MNN is in that it can deal with geoscience data with nonlinear behavior and extract characteristics from complex and noisy images. The training of MNN is used to modify connection weights between nodes located in different layers by a simulated annealing algorithm (one of the optimization algorithms of the network). In this process, three types of errors are considered: differences in values, semivariograms, and gradients between sample data and outputs from the trained network. The training is continued until the summation of these errors converges to an acceptably small value. Because the MNN trained by this learning criterion can estimate a value at an arbitrary location, this method is a form of kriging and termed Neural Kriging (NK). In order to evaluate the effectiveness of NK, a problem on restoration ability of a defined reference surface from randomly chosen discrete data was prepared. Two types of surfaces, whose semivariograms are expressed by isotropic spherical and geometric anisotropic gaussian models, were examined in this problem. Though the interpolation accuracy depended on the arrangement pattern of the sample locations for the same number of data, the interpolation errors of NK were shown to be smaller than both those of ordinary MNN and ordinal kriging. NK can also produce a contour map in consideration of gradient constraints. Furthermore, NK was applied to distribution analysis of subsurface temperatures using geothermal investigation loggings of the Hohi area in southwest Japan. In spite of the restricted quantity of sample data, the interpolation results revealed high temperature zones and convection patterns of hydrothermal fluids. NK is regarded as an interpolation method with high accuracy that can be used for regionalized variables with any structure of spatial correlation.     

Sensitivity of Spatial Analysis Neural Network Training and Interpolation to Structural Parameters

A Spatial Analysis Neural Network (SANN) algorithm was applied for the analysis of geospatial data, on the basis of nonparametric statistical analysis and the concepts of traditional Artificial Neural Networks. SANN consists of a number of layers in which the neurons or nodes between layers are interconnected successively in a feed-forward direction. The Gaussian Kernel Function layer has several nodes, and each node has a transfer or an activation function that only responds (or activates) when the input pattern falls within its receptive field, which is defined by its smoothing parameter or width. The activation widths are functions of the model structural parameters, including the number of the nearest neighbor points P and a control factor F. The estimation method is based on two operational modes, namely, a training-validation mode in which the model structure is constructed and validated, and an interpolation mode. In this paper we discuss the effect of varying F and P upon the accuracy of the estimation in a two-dimensional domain for different input field sizes, using spatial data of wheat crop yield from Eastern Colorado. Crop yield is estimated as a function of the two-dimensional Cartesian coordinates (easting and northing). The results of the research led to the conclusion that optimal values of F and P depend on the sample size, i.e., for small data sets F=1.5 and P=7 while for large data sets F=2.5 and P=9. In addition, the accuracy of the interpolated field varies with the sample size. As expected for small sample sizes, the interpolated field and its variability may be significantly underestimated.     

湖泊水下数字高程模型建模方法及应用模型

介绍了当前湖泊水下地形测量的一般方法和作业过程。针对逐点插入构建不规则三角网算法，本文提出了效率改正算法和格网索引号快速计算算法。基于不规则三角网，给出了湖泊水下数字高程模型的一般应用模型——任意点高程计算、填挖方计算模型及等深线计算模型。     

Usefulness of adaptive filtering for improved Digital Elevation Model generation

The Digital Elevation Models (DEMs), which represent the variation of elevation in a terrain at spatial level, are an important source of input to a variety of applications for deriving a number of terrain parameters such as relative relief, slope, aspect direction etc. In recent years, Synthetic Aperture Radar Interferometry has been viewed as a powerful approach to derive quality DEMs from a pair of SAR images. Despite the interferometric technique is often limited by several de-correlations several researchers demonstrate its effectiveness in topographic mapping. The DEM accuracy is strongly influenced by the effectiveness of the phase unwrapping technique. In this study an effective adaptive filtering approach has been used to reduce the phase noise due to de-correlation and in improving the accuracy of phase unwrapping. Two well known phase unwrapping approaches such as branch cut and minimum cost flow network have been used. Interferometric data from ASAR sensor onboard ENVISAT satellite have been used. A highly undulated terrain condition near Dehradun city situated in Uttarakhand state of India was selected to investigate the performance of this adaptive filtering approach. The RMS error between the InSAR derived elevations and the map derived elevations was obtained as 7.2 m using adaptive filter. However, elevation map of the study area could not be generated due to high de-correlation effect without the use of adaptive filter. This result clearly demonstrates the effectiveness of adaptive filtering approach for generation of DEM at meter level accuracy, which is sufficient for many engineering applications.     

Single-element Anomaly Mapping from Stream Sediment Geochemical Landscapes Aided by Digital Terrain Analysis

The identification of anomalies within stream sediment geochemical data is one of the fastest developing areas in mineral exploration. The various means used to achieve this objective make use of either continuous or discrete field models of stream sediment geochemical data. To map anomalies in a discrete field model of such data, two corrections are required: background correction and downstream dilution correction. Topography and geomorphology are important factors in variations of element con...     

空间插值技术在全国地下水业务分析与发布系统中的应用

等值线是地下水监测成果数据表示的重要图件。结合水利部地下水监测中心的业务功能需要,自主开发了空间插值和等值线算法库,包括规则化网格插值、等值线生成、裁剪、区域填充、统计分析、地下水漏斗识别、剖面图绘制等功能。该算法库成功应用于全国地下水业务分析与发布系统,经过18省17个平原区的数据检验,5年来运行良好,提升了地下水监测信息的加工处理效率。在此基础上研发的等值线绘制软件CONMAS可以免费下载试用。     

基于MAPGIS数字高程模型背景校正法的应用—以湖南省铜山岭-祥霖铺地区为例

本文运用Mapgis数字高程模型背景校正法对湖南省铜山岭-祥霖铺地区1∶20万水系沉积物数据进行了地球化学异常信息的提取。借助Mapgis高程库管理系统中的像元邻域统计功能,模拟出研究区内W和Sn元素的背景变化趋势,在此基础上对元素含量做背景校正,并利用残差(矿化叠加值)圈定异常。在背景模拟过程中,通过窗口大小对比试验发现,窗口越大,高背景区异常面积越大,而低背景区异常面积越小。因此,应用该法时,需要通过试验以便选出合理大小的窗口。经过背景校正后,区内W、Sn高背景场引起的非矿化异常得以抑制,传统方法圈定的大面积异常被分解成多个强异常,其空间分布规律性较好,并具有三级浓度分带特征。在低背景区发现了一系列新异常,如W’-7、8、9、13、14、15、21、22、30和Sn’-1、7、11、13、21。校正后的部分异常与已知矿点和成矿岩体或岩脉具有较好的对应关系。     

Application of Digital Elevation Model in the geological mapping of the coastal plain of Tianjin

Tianjin coastal plain is flat and its landform is not easy to be divided. The grain size of the sediments is fine, with poor remote sensing interpretation accuracy and field identification, which leads to weak geological map expression effect by the traditional geological survey method. Digital Elevation Model (DEM) is a digital representation of the topographic surface and it has 3D visual information that cannot be expressed by the general topographic map, which can truly reflect the features of the landform. The authors divided the geomorphic units of shallow sediments during the geological mapping process of Tianjin coastal plain based on DEM and the geological survey of the route, the construction of the shallow groove drilling and the sample testing. The shallow sediments can be divided into three sedimentary systems: fluvial sedimentary system, transgression sedimentary systm and deltaic sedimentary system. The fluvial sedimentary system includes several genetic types of point bar, oxbow lake, crevasse splay, natural levee, flood basin and lake marsh. And the transgression sedimentary system can be divided into beach ridge, overland fan, high tide flat, residual lagoon, while the deltaic sedimentary system includes the delta front. DEM can fully make up for the shortage of remote sensing images after the comparative analysis with the results of remote sensing interpretation of different types. Besides, DEM can also be used for the detailed genetic classification of the shallow sediments and improve the cognition about shallow geological process, which will guide the field mapping. The application of high-precision DEM data to the geological mapping on the covered areas of quaternary system can greatly improve the mapping accuracy and efficiency, and provide basic geological support for urban ecological security, territorial space planning and industrial structure layout.     

数字高程模型在天津滨海平原区地质填图中的应用

天津市滨海平原地区地势平坦,地貌类型不易划分,沉积物粒度较细,遥感解译精度及实地可识别性差,按照传统的地质调查方法开展填图,图面表达效果不佳.数字高程模型(Digital Elevation Model,DEM)是地形的数字化表达,具有一般地形图无法表达的三维可视化信息,能够真实反映地形地貌特征.在开展天津滨海平原地质填图过程中,通过建立研究区DEM,并结合路线地质调查、槽型浅钻施工、样品测试分析,进行了地貌单元划分,将浅地表沉积物划分为河流、海侵和三角洲3个沉积体系:河流沉积体系包含边滩(曲流砂坝)、充填河槽(牛轭湖)、决口扇、天然堤、洪泛盆地和湖沼沉积微相;海侵沉积体系包含海滩脊、越岸扇、高潮坪和残留潟湖沉积微相;三角洲沉积体系主要为三角洲前缘沉积.通过与不同类型遥感解译结果进行对比分析可知,DEM可充分弥补遥感影像的不足,对浅地表沉积物进行详细的成因类型划分,提升对浅地表地质作用过程的认知程度,较好地指导野外地质填图.将高精度DEM数据应用于第四系覆盖区地质填图,可以大大提高填图精度及效率,为城市生态安全保障、国土空间规划、产业结构布局等提供基础地质依据.     

TOPMODEL模型的空间尺度分析

以东江流域的岳城、胜前、东坑、蓝塘和九州五个子流域为例,应用前四个子流域分析DEM分辨率和流域大小对地形指数和TOPMODEL模型模拟结果的影响,探讨TOPMODEL模型对DEM分辨率的依赖性.结果表明:DEM分辨率对地形指数有着显著的影响,且径流模拟精度依赖于DEM空间分辨率,随着DEM空间分辨率的降低模拟得到的确定性系数逐渐减小.为了克服TOPMODEL模型难以考虑降雨空间分布不均对径流过程的影响,建立基于子流域的TOPMODEL模型,将基于子流域的TOPMODEL模型和整个流域的TOPMODEL模型应用九州子流域进行模拟比较,发现基于子流域的TOPMODEL模型能够得到精度更好的模拟效果,而且可以得到不同子流域对流域出口流量过程的贡献度,进而能够分析不同降雨情况下的流域出口洪水过程.     

地形法计算库容的公式分析

本文对地形法计算库容的公式进行了分析,提出了各种公式的适用范围,为库容计算公式的选用提供了依据。     

Terrain Morphometry and Mudflow Features in the Northern Slope of the Great Caucasus

Doklady Earth Sciences - Morphometric terrain parameters such as slope angles and altitudes make a considerable contribution to the features of mudflows. In order to assess the contribution of...     

旅行时线性插值射线追踪提高计算精度和效率的改进方法

旅行时线性插值（LTI）射线追踪算法是基于线性假设的,在向前处理过程中仅用按行或按列扫描的方法来计算节点旅行时没有考虑逆向传播射线,导致其计算精度与网格剖分大小有关,在处理复杂介质时会使得追踪出来的射线路径不一定满足最短旅行时。因此,笔者提出了两点改进措施：在向前处理时需采用全方位循环的方法来计算节点最小旅行时;在网格边界加入次生节点。模型试算结果表明：采用全方位循环的LTI法考虑了来自各个方向的射线,可提高其对复杂模型的适应能力;在节点间距相同的情况下,网格边界插入次生节点的LTI法较传统的LTI法计算精度至少可以提高一个数量级,同时,计算速度也更快;随着节点间距剖分的越精细,计算耗时下降也越明显,计算速度较传统的方法可提高n~10n倍。