基于DEM的黄土高原地形纹理概念模型

黄土高原"千沟万壑"的地貌形态,在多尺度空间下表现出显著自相似性,具有"局部无规则,宏观有规律"的纹理特征.目前,黄土高原地形纹理的提取方法及应用已经得到初步发展,但依然缺乏在理论层面的框架体系.本文在已有学者研究成果的基础上,限定黄土高原为研究范围,明确提出黄土高原地形纹理的概念模型,即内涵、特征、分类及表达.将内涵...     

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.     

复杂网络理论在黄土高原沟谷地貌特征研究中的应用

沟谷侵蚀是塑造黄土地表侵蚀形态的主要动力,沟谷的发育过程深刻地影响着黄土地貌的发育及演化.本文在黄土高原选择6个典型地貌样区,以样区的数字高程模型为基本数据源提取沟谷系统.将沟谷系统中的沟谷节点、沟谷源点和流域出水口点作为网络节点,网络节点之间的空间拓扑关系为边,高程差为权值,构建黄土高原沟谷加权复杂网络模型.对黄土沟...     

Clustering gully profiles for investigating the spatial variation in landform formation on the Chinese Loess Plateau

The gully is the most dynamic and changeable landform unit on the Loess Plateau, and the characteristics of gully landforms are key indicators of gully evolution. Different gully profiles are connected and combined through runoff nodes. Thus, it is necessary to cluster gully profiles into a gully profile combination(GPC) to reveal the spatial variation in gully landforms throughout the Loess Plateau. First, the gradient and gully evolution index(GEI) of two sample areas in Changwu and Suide in Shaanxi Province, China are calculated and analysed based on GPC. Then, the gradient and GEI are calculated by using 90-m-resolution digital elevation model(DEM) data for the severe soil erosion area with the basin as the research unit. On this basis, the spatial variation in the development degree is analysed with Getis-Ord Gi*. The results show that the degree of gully undercutting decreases from southeast to northwest under the influence of rainfall. Due to the soil properties, the loess in the northwest is more prone to collapse, resulting in the decrease of GEI from northwest to southeast. The development degree of gullies is closely related to rivers. The strong erosive capacity of rivers leads to greater differences in gullies within the basin. At the same time, the skewness and kurtosis of the gully index in the basin are correlated; when the distribution of the gully index in the basin is less normal, the distribution of the gully index is more concentrated. These results reveal the spatial variation characteristics of the Loess Plateau based on GPC.     

Deriving the slope-mean shielded astronomical solar radiation spectrum and slope-mean possible sunshine duration spectrum over the Loess Plateau

Solar radiation is often shielded by terrain relief, especially in mountainous areas, before reaching the surface of the Earth. The objective of this paper is to study the spatial structures of the shielded astronomical solar radiation(SASR) and the possible sunshine duration(PSD) over the Loess Plateau. To this end, we chose six test areas representing different landforms over the Loess Plateau and the software package of Matlab was used as the main computing platform. In each test area, 5-m-resolution digital elevation model established from 1:10,000 scale topographic maps was used to compute the corresponding slope, SASR and PSD. Then, we defined the concepts of the slope-mean SASR spectrum and the slope-mean PSD spectrum, and proposed a method to extract them from the computed slope, SASR and PSD over rectangular analysis windows. Using this method, we found both spectrums in a year or in a season for each of the four seasons in the six test areas. Each spectrum was found only when the area of the corresponding rectangular analysis window was greater than the corresponding stable area of the spectrum. The values of the two spectrums decreased when the slope increased.Furthermore, the values of the stable areas of the spectrums in a year or in a season were positively correlated with the variable coefficients of the slope or the profile curvature. The values of the stable areas of the two spectrums in a year or in a season may represent the minimum value of test areas for corresponding future research on the spatial structures of the SASR or PSD. All the findings herein suggest that the spatial structures of the PSD and the SASR are caused by the interactions between solar radiation and terrain relief and that the method for extracting either spectrum is effective for detecting their spatial structures. This study may deepen our understanding of the spatial structure of solar radiation and help us further explore the distribution of solar energy in mountainous regions.     

Automatic recognition of loess landforms using Random Forest method

The automatic recognition of landforms is regarded as one of the most important procedures to classify landforms and deepen the understanding on the morphology of the earth. However, landform types are rather complex and gradual changes often occur in these landforms, thus increasing the difficulty in automatically recognizing and classifying landforms. In this study, small-scale watersheds, which are regarded as natural geomorphological elements, were extracted and selected as basic analysis and recognition units based on the data of SRTM DEM. In addition, datasets integrated with terrain derivatives(e.g., average slope gradient, and elevation range) and texture derivatives(e.g., slope gradient contrast and elevation variance) were constructed to quantify the topographical characteristics of watersheds. Finally, Random Forest(RF) method was employed to automatically select features and classify landforms based on their topographical characteristics. The proposed method was applied and validated in seven case areas in the Northern Shaanxi Loess Plateau for its complex andgradual changed landforms. Experimental results show that the highest recognition accuracy based on the selected derivations is 92.06%. During the recognition procedure, the contributions of terrain derivations were higher than that of texture derivations within selected derivative datasets. Loess terrace and loess mid-mountain obtained the highest accuracy among the seven typical loess landforms. However, the recognition precision of loess hill, loess hill–ridge, and loess sloping ridge is relatively low. The experiment also shows that watershed-based strategy could achieve better results than object-based strategy, and the method of RF could effectively extract and recognize the feature of landforms.     

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。     

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。     

Spatial-temporal pattern and formation mechanism of county urbanization on the Chinese Loess Plateau

Urbanization is a comprehensive and complex socioeconomic phenomenon that plays an influential role in promoting global socioeconomic development. The Loess Plateau region is an important part of the China's ecological security pattern, and occupies an important position in the implementation of China's new-type urbanization strategy and the realization of the urban dream. The characteristics of the staged changes and regional differentiation of urbanization in the area from 1990 to 2018 were studied with focus on regions and subregions by selecting 341 county-level administrative units on the Chinese Loess Plateau as the research area, and employing partition analysis and geographic detector methods. This revealed the formation mechanism of the spatial differentiation pattern of urbanization on the Loess Plateau. We found that the urbanization of the Loess Plateau,previously in a slow growth phase, entered the accelerated development phase, presenting a macro pattern of high rates of urbanization in central and eastern areas and low rates in western areas. The formation of the regional differentiation patterns of urbanization on the Loess Plateau were the combined results of natural geographical and socioeconomic factors. Among these factors, the interaction of any two factors had a stronger impact on regional urbanization patterns than a single factor, which was specifically manifested as nonlinear or bi-factor enhancement effects. The findings of this paper may provide a theoretical reference and scientific basis for the scientific promotion of healthy urbanization on the Chinese Loess Plateau and the ecologically fragile areas of developing countries around the world.     

Review of Digital Elevation Model （DEM） Based Research on China Loess Plateau

Introduction The Loess Plateau is located in the upper and middle reaches of the Yellow River, among the western Taihang Mt, eastern Riyue-Helan Mt, northern Qinling Mt, and southern Yinsan Mt (from 100°54′to 114°33′E and 33°43′to 41°31′N; Figure 1). It covers a total area of 624,000 km2. The Loess Plateau of China has drawnworldwide attention in geographical research for its unique morphological features, abundant nature resources, most serious soil erosion, as well as its pot…     

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。     

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.     

基岩露头采样密度对黄土古地形重建的影响

下伏古地形对黄土地貌的形成、演化与发育具有重要的控制作用。基于下伏地层露头的采样数据,通过空间插值方法进行古地形数字模型(DEM)重建是研究黄土地貌的重要方法。其中,采样点密度是下伏地形DEM重建精度的主要影响因子。本文以1:20万绥德幅地质图所涉及区域为实验样区,研究采样点密度及样条函数方法对下伏古地形重建精度的影响。实验结果表明,在高密度样本条件下,采用规则样条插值方法进行古地形重建时,插值结果呈现显著的“龙格现象”,即多项式插值结果出现剧烈波动现象,且随着样本密度增加,样条插值结果的误差呈逐步趋缓的降低趋势,并逐步趋于稳定。同时,基于古地形DEM提取的特征点,其局部最高点和局部最低点的数目呈直线上升趋势,说明在一定程度上基于有限数据采用样条函数进行地下三维建模并不一定能获得平滑曲面。研究结果对如何选择合理的空间采样密度进行古地形DEM重建具有重要的指导意义。     

Spatial patterns and storage composition of woody debris in a natural secondary forest dominated by <Emphasis Type="Italic">Pinus tabulaeformis</Emphasis> on Loess Plateau,China

Woody debris (WD) is an important part of natural Pinus tabulaeformis mixed stands, and it affects the forest ecosystem stability and development. The WD spatial patterns are especially important structural characteristics that can provide insights into forest dynamics. In this paper, the WD storage, WD spatial patterns and WD associations among the main species were examined in the natural secondary forest on Loess Plateau in northwest China. Data were collected in a 1 ha (100 m × 100 m) permanent plot, and all the trees with a diameter at breast height of more than 3 cm were measured and stem-mapped. Ripley’s K functions from the spatial-point-pattern-analysis method were used to analyze the spatial distribution and associations. The results showed that: (1) The total storage of WD was 10.73 t/ha, fallen wood was the main source of WD, and the majority diameters were greater than 20 cm, and in intermediate levels of decay; (2) The overall spatial pattern was closely related to the spatial scale, which exhibited an aggregated pattern on a small scale, and a random pattern on a large scale. The spatial patterns of coarse woody debris also gradually transitioned from an aggregated pattern in fine scales to a random pattern in broader spatial scales, which matched the overall spatial pattern. The spatial intensity was gradually decreased with the increasing diameters, and increased with the decomposition classes; (3) The WD of Pinus tabulaeformis species was negatively associated with Betula platyphylla and Populus davidiana on a small scale but positively associated with these species on a large scale. The spatial pattern and interspecies relations were the results of long-term interactions between the natural secondary forest community and the surrounding natural environment. These findings would provide a scientific basis for the sustainable management and protection of natural secondary forest ecosystems on Loess Plateau.     

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DEM提取坡谱信息的不确定性

坡谱是黄土高原地学分析新方法、新思路的探索。本文基于坡谱不确定性的概念及其过程分布模型的论述,以陕北黄土高原国家1∶10000和1∶50000DEM数据为基本信息源,分析了坡谱不确定性的产生原因、主要影响因素与影响规律,阐述了坡谱提取与应用中应注意的主要问题,为正确应用坡谱进行地学分析提供重要依据。     

黄土高原地貌形态图谱三维符号指标体系与应用

长期以来,地貌学界和制图学界一般是采用文字、地图和图像等方式来描述黄土高原独特的地貌形态,故往往不够形象,缺乏系统性。采用地学信息图谱和三维可视化的方法,对挖掘揭示黄土高原地貌形态特征规律是一个有效的方法。黄土高原地貌形态图谱三维符号的指标体系,是将地貌学家和制图学家对黄土高原正负地貌类型的认知结果经过系统化、标准化和科学化的归纳和提炼,从中提取出的描述黄土高原地貌三维特征的参数集合。既是对黄土高原地貌形态图谱三维立体特征的充分概括,又是三维形式建模表达的参考和依据。根据黄土高原地貌类型的分类和侵蚀特征规律,该体系分为正地貌形态指标体系、负地貌形态指标体系和坡度一侵蚀特征谱系描述指标,采用定性和定量相结合的方法来制定指标体系的具体参数。最后通过实例来验证指标体系在构造三维符号时的应用。细致精确的描述单个地貌类型的三维形态,将有助于对黄土高原地貌特征的认识和研究,为水土保持和生态环境建设提供帮助,同时也为其他地貌类型的信息图谱研究提供借鉴。     

近20年来黄土高原地区的经济增长时空分异特征

 经济不均衡增长是区域发展的一种常态。分析区域经济增长时空差异及成因,对于认识和加快落后地区的经济发展具有重要的意义。本研究在GIS技术的支持下,对黄土高原地区近20年来以县市为单元的经济增长时空分异特征进行了系统的分析。主要结论有:改革开放以来,黄土高原地区的GDP水平呈现出持续的快速增长态势。近20年来,陕北和内蒙古鄂尔多斯地区增长最为迅速;人均GDP的空间分布整体上呈现出"两高一低"的带状分布格局,且这种格局明显地受到极化增长的扰动和重塑;经济增长表现出显著的极化增长特征,且经济增长极的极化作用与增长极之间地位的调整是同时进行的;与常态化的城市产业集聚推动型经济相比,机遇性的资源开发拉动型经济对人均GDP的拉动速度更快,但可持续性较差。未来,黄土高原地区应走以中心城市带动为主,以能矿产资源开发拉动为辅,两者相互促进,共同带动整个区域经济更快、更好、更可持续地发展的道路。     

面向点云数据的黄土丘陵沟壑区沟沿线自动提取方法

基于点云数据地表建模中,沟沿线既是点云去噪的重要分割线,又是黄土丘陵沟壑区最典型的地形特征线。因此,本文提出了面向点云数据的基于多尺度格网采样和坡度分割的沟沿线自动提取方法,即在适宜格网尺度采样的基础上构建地表模型,利用沟沿线周围坡度陡变的特性提取缓坡面与陡坡面的分界线,从而生成沟沿线。通过对8个样区反复实验,确定了各自的最佳格网尺度,并发现格网尺度随点密度的增大而迅速减小,而后趋近平稳的幂函数关系,同时随机选取了另外5个样区验证了该关系的适用性。最后,通过全域分块计算得到了该地区的完整沟沿线。相比于人工识别的沟沿线,本文方法提取沟沿线的精度在0.5 m缓冲范围内为85%,效果较好,且位置更为精确。产生差异的原因主要是面向点云数据的沟沿线有更多的细节,沟沿线曲率更大,造成了其长度明显大于手动提取结果。该方法有助于提高丘陵沟壑区点云数据去植被处理和地形表面重建精度。     

基于DEM的黄土崾岘提取及其地形特征分析

崾岘是将要被切穿的鞍部,是正负地形矛盾斗争的结果,也是重要的地形控制点。典型的崾岘多位于黄土高原黄土地貌区,又称黄土崾岘,其对识别沟间地与沟谷的斗争程度有一定的指示作用。本文以黄土高原样区为例,基于1:1万DEM（5 m分辨率）和影像分辨率为0.95 m的遥感影像,利用流域边界算法和缓冲区标定,分析窗口选择5×5,实现了崾岘点位的半自动化提取。并对各崾岘点位求取坡度等地形因子,总结崾岘的空间格局和地形特征。结果显示,崾岘多分布在主流域边界和垂直于主沟道的最宽部分,地形控制作用明显。崾岘的坡度、起伏度、切割深度等值均大于鞍部值,同时,高级流域区的崾岘值大于低级流域区的崾岘值,反映出崾岘具有侵蚀程度强、表层完整性低、地表破碎度高的特点。总体而言,崾岘受沟道蚕食度高,从侧面反映了黄土地貌的发育阶段,是黄土地貌发育到中期的标志性产物。