黄土高原洛河流域地貌发育特征与形成演化

黄土地貌形态特征、发育机理及演化过程等一直是地学研究的热点和前沿。选取黄土高原洛河流域作为研究对象,从坡面尺度、流域尺度、区域尺度分类选取14项地貌因子,较为全面地构建了流域地貌发育形态定量参数体系;提取646个小流域为分析单元,利用主成分分析法,获得了描述流域黄土地貌形态特征的4个主因子;这4个主因子分别反映了4种地貌形态空间格局,即南北渐变型、单中心扩散型、东西过渡型、多中心扩散型。结合流域地貌类型和地貌发育程度特征,认为黄土地貌地形起伏和垂直侵蚀特征反映了研究区的总体地貌空间格局,洛河流域黄土地貌主要是在多种因素影响下,随着水系由下游向上游不断地溯源侵蚀、下切扩展,最终形成了现今形态空间分异格局。     

基于DEM的黄土地貌逼近度因子构建及特征分析

沟谷源点作为沟沿线上最为活跃的部位,其分别到上游分水线、下游沟谷线的流线空间比对关系,是表征三线空间结构的重要突破口。它在空间上向流域分水线逼近的程度,是量化黄土流域地貌系统发育程度的重要切入点。为探究黄土地貌区流域沟谷源点向流域分水线逼近的程度,揭示黄土流域地貌发育进程及该进程所表现的主要侵蚀方式,本文从水平和垂直2个维度,构建量化三线空间结构关系的核心因子--逼近度(PI),其中包括水平逼近度(HPI)和垂直逼近度(VPI),基于5 m分辨率数字高程模型,在陕北黄土高原遴选了包含16种地貌类型的42个样区,利用数字地形分析方法,探讨其平均值(MHPI, MVPI)的空间分异规律。另外,选择其中南北序列分别代表黄土塬、残塬、梁状丘陵沟壑和峁状丘陵沟壑区的淳化、宜君、甘泉和绥德4个地区,完备包含一至五级别沟谷的典型流域为重点实验样区,探讨陕北黄土高原流域尺度平均逼近度变异指数(MPIV)序列性特征。实验结果表明:①陕北黄土高原平均逼近度(MPI)存在强烈的空间自相关,MHPI在南北序列上先增大后减小,东西方向上逐渐减小,在黄河沿岸峡谷丘陵区MHPI达到最大;MVPI由西南-东北先减小后增加,由西北-东南逐渐减小,在渭北黄土台塬区达到最小;②在流域尺度上,MPIV值的正负与黄土塬区、丘陵沟壑区敏感相关;③4个重点样区MHPI、MVPI与其它地形因子存在南北序列上的一致性。104个外部汇流区平均水平逼近度与平均坡度相关性较好(P=0.43, a<0.001),平均垂直逼近度与面积高程积分强烈相关(P=0.75, a<0.001)。平均逼近度指标综合考量了黄土高原地区最典型的三条具有结构控制意义特征线的空间关系,对黄土地貌的发育程度有明显的指示性意义。     

基于地形剖面的黄土塬梁峁地形各向异性奇异强度研究

黄土高原不同地貌类型对应的地形起伏变化特征各不相同,地形起伏在不同方向上的变化特征具有很大差异性,即地形各向异性。本文引入多重分形谱参数描述不同地貌类型地形各向异性的变化规律,以反映不同黄土地貌地形各向异性的局部和整体变化格局。本研究以5 m分辨率的DEM数据为基础,选取淳化、甘泉、绥德3个典型黄土塬梁峁地貌类型研究样区,对其地形各向异性的变化特征进行分析。研究表明:①3种黄土地貌类型地形各向异性变化具有显著的多重分形特征,地形各向异性变化的奇异强度由强到弱依次为淳化、绥德、甘泉;②淳化样区地形各向异性奇异强度在1.4的概率最大,在奇异强度为2.2附近又有一个小的峰值,总体以奇异强度1.4为主;③甘泉样区的奇异强度在1.8有一个小的峰值,总体以奇异强度0.7为主;④绥德样区奇异强度为0.8的概率最大,且较为均匀地分布在0.8附近,地形各向异性的概率分布呈现为对称分布。研究结果为黄土塬梁峁地形各向异性变化奇异强度为黄土塬最大,黄土峁次之,黄土梁最小。该研究可为黄土地貌的精确分类提供定量信息支持,为区域水土侵蚀评价提供地形指标。     

面向多分辨率DEM的河网相似性测度与分析

河网是地形结构的核心要素,能够有效地反映DEM对地表形态的刻画能力。实现不同分辨率条件下DEM河网相似性测度对DEM地形综合、DEM质量评估及DEM不确定性分析等研究具有重要意义。基于此,本文以黄土高原典型样区为研究区,基于5 m高精度DEM建立的多分辨率DEM数据集,构建了地形特征自适应的DEM河网自动提取方法,建立了综合拓扑关系、方位关系、距离关系及属性特征四维信息的河网相似性度量模型,并分析了河网相似性变化特征及其与地形参数的相关性。实验结果显示,河网自动提取方法的制图精度和用户精度均在90%以上,总体精度优于Passalacqua等提出的GeoNet方法,能够有效实现不同分辨率下河网较高精度提取;河网相似性度能综合反映河网空间分布特征的差异性,河网相似度与分辨率变化率之间的幂函数关系R²达0.978,且河网相似度与高程、坡度中误差分别表现为幂函数和对数函数关系,后者对数关系显著性优于前者幂函数关系。研究表明,在以河网作为DEM构建重要数据源的背景下,本文的研究成果可为DEM质量及其应用适宜性的定量评价提供基础。     

定南县岭北矿区植被覆盖与地形因子关系分析

以岭北稀土矿区植被退化的环境为研究背景,数据选择1990、1999、2008、2013四年30 m分辨率LandsatTM数据,利用像元二分模型估算研究区植被覆盖度;利用DEM数据获取研究区的坡度及坡向地形因子,并对不同地形因子进行定量评价。分析定南县岭北矿区植被覆盖度与不同地形因子条件的相关性,及不同地形因子条件下植被覆盖的分布特点。研究结果表明:植被覆盖度受高程、坡度影响较大,其中在高程400 m到500 m,坡度6°~15°区域内植被覆盖度较其他区域高,坡向影响主要表现在阳坡阴坡上,阴坡植被覆盖度普遍比阳坡高。研究结果能够快速、客观地反映稀土矿区植被的状况,为南方稀土矿区环境的治理和监测提供有效科学依据。     

DEM提取坡度信息的不确定性分析

以陕西省671幅1∶50000比例尺,25m分辨率的DEM数据为信息源,分析DEM分辨率对提取坡度信息的不确定性影响。研究表明:平均坡度随DEM分辨率的减小呈显著递减型二次曲线变化,但当DEM分辨率减小到一定程度时,平均坡度将趋于稳定;并且,随DEM分辨率变化,坡度的不确定性呈现明显的空间结构性分布,DEM栅格单元内部地形的复杂性和变异性越大,坡度提取不确定性越大,如沟坡地坡度提取误差明显大于沟间地。因此,实际应用中要充分考虑研究区域DEM地形描述的尺度效应和不确定性问题,选择合适尺度的DEM提取坡度信息,保证提取结果的科学有效。     

黄土地貌区径流节点提取及其特征信息指数的DEM实验分析

径流节点是一种真实存在于流域单元中的地学实体对象,携带了大量的水文与地貌特征信息。针对当前研究中缺乏定量地度量径流节点所承载的地学特征信息量的相关探讨,本文结合径流节点的已有理论,总结了其地学特征信息,借鉴数学粗集理论提出了径流节点的特征信息指数（FIIRN）,并分析了相关的定义与计算方法。本文以黄土高原的7个典型黄土地貌样区5 m分辨率DEM数据为实验材料,提取了各个实验样区的径流节点,并计算了每个样区的FIIRN指数值。实验结果表明：（1）FIIRN指数可有效地映射流域单元的径流分级、发育状况等地学特征信息;（2）FIIRN指数可定量地表达流域单元的地学特征信息量;（3）FIIRN指数可作为挖掘流域地学特征信息的一个重要参数。     

基于区域生长的黄土地貌沟沿线提取方法与实验

沟沿线是黄土地貌正负地形的分界线,地形在沟沿线处存在较大的高程变化和坡度转折。坡面畸变邻域法是一种有效提取沟沿线的方法,但该方法对正负地形进行分割时,往往会产生大量的碎屑多边形和分类错误,严重影响沟沿线的提取精度。为了解决这个问题,本文采用区域生长方法来改进坡面畸变邻域法的提取结果。首先,分别以DEM提取的山顶点和出水口点作为正负地形的生长点进行4邻域生长,生长至正负地形边界或大于坡度阈值为止;然后,采用边缘检测方法提取正负地形分界线;最后,依据形态学图像处理方法去除"毛刺"得到最终的沟沿线。结果显示,该方法实现了对沟沿线的自动提取,解决了由于正负地形分类错误造成的沟沿线定位不准确的问题,提高了沟沿线的提取精度,同时该方法也较好地保持了沟沿线的完整性和连续性,对黄土高原不同地貌类型具有普遍的适用性。     

DEM分辨率与平均坡度的关系分析

由DEM提取坡度时,DEM分辨率的变化会造成局部栅格提取的坡度数值的变化,其变化规律对于深刻理解平均坡度,随DEM分辨率的变化而变化的规律具有现实意义。在黄土高原的研究中,选择了8个典型地貌类型的样区,获得了以1:10 000比例尺地形图为数据源的DEM(分辨率为5 m)。从DEM分辨率对栅格坡度影响规律的分析中,得到如下结论:(1)随着DEM分辨率粗略化,所提取的坡度平均值有可能升高;(2)在所有样区,随DEM分辨率粗略化,负误差的栅格均是正误差的栅格数量的1.13倍以上,保持负误差的栅格是保持正误差的栅格数量的1.81-4.04倍,同时坡度的负误差均值是正误差均值变化幅度的3.1倍以上;(3)结合结论(2)和本文提出的指标,可准确地解释8个样区中坡度平均值随DEM分辨率变化而变化的规律;(4)DEM的分辨率对正负误差的栅格数量没有明显影响,正误差(或负误差)栅格均集中于个别坡度的分级区间,而DEM分辨率对此集中的区间没有明显影响;(5)坡度总体误差可根据本研究所提出的经验公式由DEM分辨率和分辨率为5 m的DEM所提取坡度的平均值计算出来。     

黄土高原沟谷地貌发育演化研究进展与展望

黄土沟谷是黄土地貌中最有活力、最具变化、最富特色的对象单元,黄土高原千沟万壑的地貌形态以及触目惊心的侵蚀状态也让区域内沟谷地貌的形成、发育及演化问题成为研究中焦点及前沿性科学问题。近年来,诸多学者采用地学测年法、特征表达法、监测模拟法力图实现对黄土沟谷发育演化进程中“过去-现代-未来”的科学认知。这些研究在相当程度上丰富了黄土沟谷发育过程的认知。本文梳理了黄土高原沟谷地貌演化相关研究的现状,并从黄土高原地貌演化、黄土沟谷发育、基于DEM的沟谷信息提取与表达等研究进行了系统的回顾、梳理与分析。此外,本文提出“黄土沟道剖面群组”概念与方法,试图从新的视角审视黄土沟谷地貌发育演化过程。沟道剖面在黄土沟谷发育演化进程中传递物质能量和累积地形动力,并通过径流节点的串联实现剖面群的连接与组合,形成独特的剖面“群组”模式;该沟道剖面群组是集黄土沟谷地貌特征与过程于一体的综合信息集成体,其三维空间结构是对黄土沟谷地貌发育演化的高度抽象与映射,并可望进一步丰富黄土高原数字地形分析理论与方法体系,为黄土高原黄土地貌成因机理与空间分异格局带来创新的认识。     

Quantifying spatial scale of positive and negative terrains pattern at watershed-scale: Case in soil and water conservation region on Loess Plateau

The positive and negative terrains (P-N terrains) widely distributed across China’s Loess Plateau constitute the dual structure characteristic of loess landforms. Analysis of loess P-N terrains at the watershed scale can serve to elucidate the structural characteristics and spatial patterns of P-N terrains, which benefits a better understanding of watershed evolution and suitable scales for loess landform research. The Two-Term Local Quadrat Variance Analysis (TTLQV) is calculated as the average of the square of the difference between the block totals of all possible adjacent pairs of block size, which can be used to detect both the scale and the intensity of landscape patches (e.g., plant/animal communities and gully networks). In this study, we determined the latitudinal and longitudinal spatial scale of P-N terrain patterns within 104 uniformly distributed watersheds in our target soil and water conservation region. The results showed that TTLQV is very effective for examining the scale of P-N terrain patterns. There were apparently three types of P-N terrain pattern in latitudinal direction (i.e., Loess Tableland type, Loess Hill type, and Transitional Form between Sand and Loess type), whereas there were both lower and higher values for P-N terrain pattern scales in all loess landforms in the longitudinal direction. The P-N terrain pattern also clearly presented anisotropy, suggesting that gully networks in the main direction were well-developed while others were relatively undeveloped. In addition, the relationships between the first scales and controlling factors (i.e., gully density, nibble degree, watershed area, mean watershed slope, NDVI, precipitation, loess thickness, and loess landforms) revealed that the first scales are primarily controlled by watershed area and loess landforms. This may indicate that the current spatial pattern of P-N terrains is characterized by internal force. In selecting suitable study areas in China’ Loess Plateau, it is crucial to understand four control variables: the spatial scale of the P-N terrain pattern, the watershed area, the main direction of the watershed, and the loess landforms.     

Hierarchy structure characteristics analysis for the China Loess watersheds based on gully node calibration

A land surface region can be decomposed into a series of watershed units with a hierarchical organizational structure. For loess landform, the watershed is a basic spatial–structural unit that can express natural landforms, surface morphology characteristics, spatial organization and developmental evolution. In this research we adopted the concept of node calibration in the watershed structure unit, selected six complete watersheds on China Loess Plateau as the research areas to study the quantitative characteristics of the hierarchical structure in terms of watershed geomorphology based on digital elevation model(DEM) data, and then built a watershed hierarchical structure model that relies on gully structure feature points. We calculated the quantitative indices, such as elevation, flow accumulation and hypsometric integral and found there are remarkably closer linear correlation between flow accumulation and elevation with increasing gully order, and the same variation tendency of hypsometric integral also presented. The results showed that the characteristics of spatial structure become more stable, and the intensity of spatial aggregation gradually enhances with increasing gully order. In summary, from the view of gully node calibration, the China Loess watershed structure shows more significantly complex, and the developmental situation variation of the loess landforms also exhibited a fairly stable status with gully order increasing. So, the loess watershed structure and its changes constructed the complex system of the loess landform, and it has the great significance for studying the spatial pattern and evolution law of the watershed geomorphology.     

坡谱信息熵尺度效应及空间分异

选取陕北黄土高原48个不同地貌类型区,以其对应的1∶10000及1∶50000数字高程模型(DEM)为数据源,运用比较分析与数理统计的方法,分析了坡谱信息熵在陕北黄土高原的空间分异特征及尺度效应。结果显示,坡谱的信息熵在一定程度上可以反映地表的复杂度,坡谱信息熵和沟壑密度间有较好的幂函数关系,随着坡谱信息熵的增大,样区沟壑密度也增大。坡谱信息熵的空间分异和陕北黄土高原的黄土地貌形态在空间上的变异是相关的,可将其作为地貌类型划分的判别因子之一。     

基于随机森林的黄土地貌分类研究

地貌分类在指导人类建设活动的规模与布局中有着重要的意义。然而,传统的基于数字高程模型(DEM)的地貌分类方法使用的地形因子和考虑到的地貌特征往往比较单一。本文提出了一种基于流域单元的地貌分类方法,该方法考虑了流域单元的多方面特征,包括基本地形因子统计量、地形特征点线统计量、小流域特征和纹理特征。本研究首先基于DEM进行水文分析将研究区域划分成不同的小流域。然后利用数字地形分析提取29个不同方面的特征来表征流域的形态,并基于随机森林(RF)算法进行了特征选择和参数标定。RF是一种基于决策树算法的集成分类器,能有效地处理高维数据,分类精度高。最后选择训练集小流域对RF分类器进行训练,使用训练完成的分类器对整个研究区域的地貌进行分类,研究地貌分异的规律。该实验在我国陕北黄土高原典型黄土地貌区域的地貌分类中取得了较好的结果,结果表明不同的地貌之间存在明显的区域界线,特定的地貌类型在空间上表现出明显的聚集性。通过人工判读进行验证的分类精度达到了85%,Kappa系数为0.83。     

Snake Model for the Extraction of Loess Shoulder-line from DEMs

Shoulder lines are the most important landform demarcations for geographical analysis,soil erosion modeling and land use planning in the Loess Plateau area of China.This paper proposes an automatic,effective and accurate method of determining loess shoulder line from DEMs by integrating a hydrological D8 algorithm and a snake model.The watershed boundary line is adopted as the initial contour which evolves to identify the exact position of loess shoulder-line by the guidance of an external force of snake model from DEMs.Experiments show that the method overcomes the difficulties in both threshold selection for edge detection and the disconnecting issues in former extraction approaches.The accuracy evaluation of shoulder-line maps from the two test sites of the loess plateau area show obvious improvements in the extraction.The average contour matching distance of the new method is 12.0 m on 5 m resolution DEM,and shows improvement in the accuracy and continuity.The comparisons of accuracy evaluations of the two test sites show that the snake model method performs better in the loess plain area than in the area with high gully density.     

Uncertainty of slope length derived from digital elevation models of the Loess Plateau,China

Although many studies have investigated slope gradient uncertainty derived from Digital Elevation Models（DEMs）, the research concerning slope length uncertainty is far from mature. This discrepancy affects the availability and accuracy of soil erosion as well as hydrological modeling. This study investigates the formation and distribution of existing errors and uncertainties in slope length derivation based on 5-m resolution DEMs of the Loess Plateau in the middle of China. The slope length accuracy in three different landform areas is examined to analyse algorithm effects. The experiments indicate that the accuracy of the flat test area is lower than that of the rougher areas. The value from the specific contributing area（SCA） method is greater than the cumulative slope length（CSL）, and the differences between these two methods arise from the shape of the upslope area. The variation of mean slope length derived from various DEM resolutions and landforms. The slope length accuracy decreases with increasing grid size and terrain complexity at the six test sites. A regression model is built to express the relationship of mean slope length with DEM resolution less than 85 m and terrain complexity represented by gully density. The results support the understanding of the slope length accuracy, thereby aiding in the effective evaluation of the modeling effect of surface process.     

多尺度DEM提取地势起伏度的对比分析——以福建低山丘陵区为例

坡度和起伏度是地形描述中最常用的参数,它们能快速、直观地反映地势起伏特征;坡度是划分平原和非平原的重要依据之一,地势起伏度可进一步划分台地、丘陵、小起伏山地、中起伏山地和大起伏山地等类型,基本地貌类型就是由海拔和起伏度两个指标确定的形态类型,它是遥感解译划分更详细地貌类型的基础。本研究以福建省1∶25万和1∶10万的DEM为实验数据,计算坡度划分平原和山地大区,其临界坡度值约为3°;利用ArcG IS空间分析中栅格窗口递增方法,对应不同尺度的DEM,计算地势起伏度,确定研究区的最佳分析窗口面积为4.41km²,得出中国低山丘陵区计算基本地貌形态类型的最佳尺度DEM为1∶25万比例尺,而1∶10万比例尺DEM适用于没有连绵起伏的更小范围的低山丘陵区;利用已有研究成果得出不同尺度DEM计算地势起伏度与最佳格网单元之间的函数关系。该研究对提取我国低山丘陵区基本地貌形态类型具有一定的借鉴作用。     

Extraction and analysis of gully head of Loess Plateau in China based on digital elevation model

In China′s Loess Plateau area, gully head is the most active zone of a drainage system in gully areas. The differentiation of loess gully head follows geospatial patterns and reflects the process of the loess landform development and evolution of its drainage system to some extent. In this study, the geomorphic meaning, basic characteristics, morphological structure and the basic types of loess gully heads were systematically analysed. Then, the loess gully head′s conceptual model was established, and an extraction method based on Digital Elevation Model(DEM) for loess gully head features and elements was proposed. Through analysing the achieved statistics of loess gully head features, loess gully heads have apparently similar and different characteristics depending on the different loess landforms where they are found. The loess head characteristics reflect their growth period and evolution tendency to a certain degree, and they indirectly represent evolutionary mechanisms. In addition, the loess gully developmental stages and the evolutionary processes can be deduced by using loess gully head characteristics. This study is of great significance for development and improvement of the theoretical system for describing loess gully landforms.