面向地貌学本源的数字地形分析研究进展与展望

数字地形分析(DTA)是地理信息科学(GIS)研究的热点.但是,当前基于数字高程模型(DEM)的数字地形分析在地貌学研究中存在重形态轻机理、重现象轻过程、重地上轻地下等问题,急需从单一的地貌形态分析,迈向面向成因、过程与机理等地貌学本源问题的研究转变.据此,本文系统梳理了面向地貌学本源的数字地形分析的相关研究现状,并从...     

我国数字高程模型与数字地形分析研究进展

数字高程模型是最重要的国家基础地理信息数据,基于GIS的数字地形分析的理论、方法与应用,是当今地理学、地貌学界,特别是地理信息科学研究的热点问题。本文从DEM的数据模型、数字地形分析的不确定性、分析方法、尺度效应、高性能计算方法以及地学应用等方面,对我国学者在该领域的研究情况,特别是研究成果进行较全面的梳理与分析。综述显示,我国具有一批从事数字高程模型与数字地形分析的高水平研究力量,研究方向紧跟国际前沿,并取得了丰硕的成果,部分研究内容具有显著创新,年轻一代科学家正加速成长。在黄土高原、青藏高原的区域数字地形分析方面更彰显我国科学家的优势与特色,在国际学术界产生了重要的影响。     

数字地形分析

对地形的描述、表达及分析历来是跟地球有关的所有学科之关注焦点。长期以来,人们采用等高线图来表达地形并发展了许多基于等高线的分析方法。自20世纪50年代后期,人们开始用数字化方法来作描述及表达地形。数字高程模型（DEM）一术语在1958年首次提出。数字高程模型已成为国家空间数据基础设施的“4D”产品之一．正在逐步取代传统（描述地形）的地形图。目前我国已经完成了1：100万、1：25万、1：5万等多种比例尺的数字高程模型之建立,1：1万数字高程模型也正在积极的建设中。这些数字高程模型已在制图、土木、水利、交通、水文、农业、规划等地学领域得到广泛应用。可以想象,每个应用所需的地形信息是不一样的。因而,人们发展了许多从数字高程模型提取各种地形信息的理论、技术与方法．从而导致了数字地形分析这一学科的成长。     

DEM与地形分析的并行计算

总结了数字高程模型构建、特征提取等并行算法的研究进展,概述了不同并行算法的主要内容;探讨了DTA并行技术在海量地形数据可视化和高性能地学计算的应用,随着DEM的需求日益增大,高精度、高分辨率DEM产品及其附加服务也逐步产品化。最后,通过分析并行计算发展的关键问题,提出DTA并行技术的研究趋势及研究意义,合适的数据划分和结果融合策略、通用并行算法、容错机制和负载均衡策略的设计是今后研究的重要内容,尤其是如何在多种计算模式共同发展的背景下利用并行计算解决地学难题,从而得到更接近现实世界地理环境的模拟,并扩大数字地形分析的应用范围。     

DEM地形简化指标的分析研究

该文对基于局部误差、曲率和法向量的5个地形简化指标进行分析评价,用离散的高斯合成曲面来模拟真实DEM,以解析得到的高斯曲率作为地形简化指标“真值”,通过对各个指标“保特征性”可信度的分析,获得对这5个指标的整体评价：1)基于法向量的地形简化指标更能反映地形特征;2)各指标的“保特征性”随简化比的减小呈线性上升;3)各指标的优劣排序对地表形状和分辨率不敏感;4)各指标“保特征性”可信度在同一分辨率下较为稳定。并用实例验证结论的正确性。     

地形复杂度对坡度坡向的影响

采用三阶不带权差分算法，研究了地形复杂度与坡度坡向的关系，澄清了目前关于坡度坡向误差空间分布的矛盾观点，并分别在凹向椭球和高斯合成曲面数学模型曲面DEM上对其进行验证。通过研究得出：①坡度、坡向误差与坡度值正相关；②坡度坡向误差主要分布在平坦地区；③坡向误差较坡度误差对DEM高程数据误差敏感，较小的DEM误差引起较大的坡向误差。     

山区地形开阔度的分布式模型

 地形开阔度是影响山地辐射平衡及其分量的重要地形因子,是山区散射辐射、地形反射辐射等计算的重要参数。在复杂的地形条件下,地形开阔度的计算很难用数学公式描述。 利用数字高程模型（DEM）,全面考虑了坡地自身遮蔽和周围地形相互遮蔽的影响,提出了山区地形开阔度的分布式模型和算法。以1 km×1 km分辨率的DEM数据作为地形的综合反映,计算了起伏地形下中国地形开阔度的空间分布。同时,利用100 m和1 km两个分辨率的DEM数据,从不同DEM分辨率和不同地貌类型两个方面探讨了地形开阔度的空间尺度效应,阐明了区域地形开阔度随地形地貌和空间分辨率的变化规律。所提供的山地开阔度的数据可作为基础地理数据供相关研究应用。     

数字地形分析在滑坡研究中的应用综述

高效的数字地形分析（Digital Terrain Analysis,DTA）是滑坡预测与评估研究的重要手段。文章综述了DTA在滑坡研究中的应用现状,基本内容包括地形因子分析、地形形态分析、地形单元划分以及DEM与滑坡模型的结合分析。地形因子分析的应用多而广,主要思路是在地形因子与滑坡发育的关系研究基础上分析其滑坡敏感性,进而构建滑坡预测和评估模型;地形形态分析是滑坡识别的重要手段,加强地貌形态和滑坡发育的关系研究有助于对潜在滑坡地形的识别;地形单元划分能为滑坡研究提供统计和分析单元;DEM与滑坡专业模型的结合方式多样,程度各异。同时,从尺度选择与转换的角度探讨了DTA滑坡研究的尺度问题,分析了DTA的局限性,指出DEM不能提供完备无误的地形信息,DTA不能完全取代常规的地形分析。最后,基于以上论述对未来的研究趋势提出了展望。     

地形分析与地理信息系统在水文地貌学中的应用

本文阐述了利用地理信息系统进行大面积及高分辨率的地形分布方面的最新进展，并且讨论了一些由地理信息系统获得地形参数的规律，并提供了作者本人的一些设想。     

栅格数字地形分析中的尺度问题研究方法

栅格数字高程模型（DEM）固有的尺度特征给以栅格DEM为基本输入的数字地形分析带来各种尺度问题。对栅格数字地形分析中涉及的尺度进行梳理,以分辨率和分析窗口为重点,对栅格数字地形分析中的多尺度表达、尺度效应、适宜尺度选择、尺度转换等尺度问题及其相互关系进行阐述;分别介绍各类尺度问题的现有定量研究方法,尤其对尺度效应定量刻画和适宜尺度选择方法,根据不同方法计算定量指标所利用的信息类别进行分类归纳;最后讨论了其中有待进一步开展研究的几方面工作。     

Geomorphology-oriented digital terrain analysis: Progress and perspectives

Digital terrain analysis(DTA) is one of the most important contents in the research of geographical information science(GIS). However, on the basis of the digital elevation model(DEM), many problems exist in the current research of DTA in geomorphological studies. For instance, the current DTA research appears to be focused more on morphology, phenomenon, and modern surface rather than mechanism, process, and underlying terrain. The current DTA research needs to be urgently transformed from the study of landform morphology to one focusing on landform process and mechanism. On this basis, this study summarizes the current research status of geomorphology-oriented DTA and systematically reviews and analyzes the research about the knowledge of geomorphological ontology, terrain modeling, terrain derivative calculation, and terrain analytical methods. With the help of DEM data, DTA research has the advantage of carrying out geomorphological studies from the perspective of surface morphology. However, the study of DTA has inherent defects in terms of data expression and analytic patterns. Thus, breakthroughs in basic theories and key technologies are necessary. Moreover, scholars need to realize that DTA research must be transformed from phenomenon to mechanism, from morphology to process, and from terrain to landform. At present, the research development of earth science has reached the critical stage in which the DTA research should focus more on geomorphological ontology. Consequently, this study proposes several prospects of geomorphology-oriented DTA from the aspects of value-added DEM data model, terrain derivatives and their spatial relations, and macro-terrain analysis. The study of DTA based on DEM is at a critical period along with the issue on whether the current GIS technology can truly support the development of geography. The research idea of geomorphology-oriented DTA is expected to be an important exploration and practice in the field of GIS.     

Integrated Teaching of Geographic Information Science and Physical Geography Through Digital Terrain Analysis

Abstract

We present an outline of a course in digital terrain analysis that provides students with integrated instruction in geographic information science (GISci) and topics in physical geography and earth science. Integrated teaching of GISci and other sub-fields of geography has value because it presents GISci technologies in the context of their application. Nevertheless, the design of college and university geography courses is often fragmented rather than integrated. Our course provides one potential model for such integration. Assessment of student reaction, using focus groups of both enrolled and non-enrolled students, revealed a generally positive attitude toward the course and pointed out the barriers that prevent some students from taking it.     

Third-order geomorphometric variables (derivatives): definition,computation and utilization of changes of curvatures

Third-order geomorphometric variables (based on third derivatives of the altitudinal field) have been neglected in geomorphometry, but their application to the delimitation of surface objects will lead to their increasing significance in future. New techniques of computation, presented and evaluated here, facilitate their use. This paper summarizes recent knowledge concerning definition, computation and geomorphologic interpretation of these variables. Formulae defining various third-order variables are unified based on the physical definition of slope gradient. Methods for their computation are compared from the point of view of method error and error generated by digital elevation model (DEM) inaccuracy. For exact mathematical test surfaces, the most natural and simple variant of the method of central differences (CD2) shows a method error 2–3 times smaller than the other methods used recently in geomorphometry. However, success in coping with DEM inaccuracy depends (for a given grid mesh) on the number and weighting of points from which the derivative is computed. This was tested for surfaces with varying degrees of random error. Here least squares-based methods are the most effective for mixed derivatives (especially for finer grids and less accurate DEMs), while a variant of the CD method, that repeats numerical evaluation of first derivatives (CD1), is the most successful for derivatives in cardinal directions. The CD2 method is generally the most successful for coarser grids where the method error is dominant.

Utilization of third-order variables is documented from examples of terrain feature (ridge, valley and edge) extraction and from a first statistical test of the hypothesis that real segments of the land surface have a tendency to a constant value of some morphometric variable. For detection of (sharp) ridges and valleys, it is shown that the rate of change of tangential curvature is inadequate: rate of change of normal curvature is also required. A basic confirmation of the constant-value tendency is provided.     

Digital Terrain Modeling and Industrial Surface Metrology: Converging Realms

Digital terrain modeling has a micro- and nanoscale counterpart in surface metrology, the numerical characterization of industrial surfaces. Instrumentation in semiconductor manufacturing and other high-technology fields can now contour surface irregularities down to the atomic scale. Surface metrology has been revolutionized by its ability to manipulate square-grid height matrices that are analogous to the digital elevation models (DEMs) used in physical geography. Because the shaping of industrial surfaces is a spatial process, the same concepts of analytical cartography that represent ground-surface form in geography evolved independently in metrology. The surface topography of manufactured components, exemplified here by automobile-engine cylinders, is routinely modeled by variogram analysis, relief shading, and most other techniques of parameterization and visualization familiar to geography. This article introduces industrial surface-metrology, examines the field in the context of terrain modeling and geomorphology and notes their similarities and differences, and raises theoretical issues to be addressed in progressing toward a unified practice of surface morphometry.     

Digital Terrain Modeling and Industrial Surface Metrology: Converging Realms

Digital terrain modeling has a micro‐ and nanoscale counterpart in surface metrology, the numerical characterization of industrial surfaces. Instrumentation in semiconductor manufacturing and other high‐technology fields can now contour surface irregularities down to the atomic scale. Surface metrology has been revolutionized by its ability to manipulate square‐grid height matrices that are analogous to the digital elevation models (DEMs) used in physical geography. Because the shaping of industrial surfaces is a spatial process, the same concepts of analytical cartography that represent ground‐surface form in geography evolved independently in metrology. The surface topography of manufactured components, exemplified here by automobile‐engine cylinders, is routinely modeled by variogram analysis, relief shading, and most other techniques of parameterization and visualization familiar to geography. This article introduces industrial surface‐metrology, examines the field in the context of terrain modeling and geomorphology and notes their similarities and differences, and raises theoretical issues to be addressed in progressing toward a unified practice of surface morphometry.     

Cartography: visualization of spatial data (3rd ed.), by Menno-Jan Kraak and Ferjan Ormeling

Conventionally, a raster operation that needs to scan the entire image employs only one scanning order (i.e., single scanning order (SSO)), and the scan usually runs from upper left to lower right and row by row. We explore the idea of alternately applying multiple scanning orders (MSO) to raster operations that are based on the local direction, using the flow accumulation (FA) calculation as an example. We constructed several FA methods based on MSO, and compared them with those widely used methods. Our comparison includes experiments over digital elevation models (DEMs) of different landforms and DEMs of different resolutions. For each DEM, we calculated both single-direction FA (SD-FA) and multi-direction FA (MD-FA). In the theoretical aspect, we deducted the time complexity of an MSO sequential algorithm (MSOsq) for FA based on empirical equations in hydrology. Findings from the experiments include the following: (1) an MSO-based method is generally superior to its counterpart SSO-based method. (2) The advantage of MSO is more significant in the SD-FA calculation than in the MD-FA calculation. (3) For SD-FA, the best method among the compared methods is the one that combines the MSOsq and the depth-first algorithm. This method surpasses the commonly recommended dependency graph algorithm, in both speed and memory use. (4) The differences between the compared methods are not sensitive to specific landforms. (5) For SD-FA, the advantage of MSO-based methods is more obvious in a higher DEM resolution, but this does not apply to MD-FA.