机载LiDAR DEM在流域水文分析与模拟中的尺度效应

DEM数据是流域水文分析和模拟的基础,不同DEM分辨率尺度深刻影响着水文分析和水文过程模拟的结果。本文基于机载LiDAR获取的DEM数据,分析了不同分辨率LiDAR DEM在坡度提取、水文指数分析和流域特征参数提取中的差异及产生原因;基于SWAT分布式水文模型模拟研究了不同分辨率DEM数据的水文效应。研究结果表明：随着DEM分辨率的降低,坡度平均值减小,TWI平均值增大,SPI平均值减小,LSF均值先增大后减小,当分辨率为10 m时,LSF取得最大值;SWAT模型模拟结果表明,随分辨率的降低、坡度值的变小,地形湿度指数变大,蒸散发量增加,地表径流深减小,而土壤渗漏量与地下径流量则是先减小后增加,出现极值时DEM分辨率为10 m,与LSF出现极值时一致。     

基于DEM提取流域特征影响因子的分析

基于DEM的流域特征提取,受数据源、分辨率、重采样技术等因子影响。为系统地评价不同地貌类型对各影响因子的敏感程度,本文提出一种多指标因子分析模型,综合分析不同因子对流域特征,如流域面积、河流分叉比、河网密度、流域长度、流域坡度、流域高程、流域形状等的客观影响。实验过程选取山地、丘陵、平原地形的中小流域为研究区域,以ASTER 30m重采样生成的40—100m分辨率DEM,ASTER 30m、SRTM 90m和GMTED2010 250m的3种数据源及4种重采样技术生成的DEM场景为实验数据。结果表明:分辨率对流域特征影响最敏感,数据源次之,重采样技术不太敏感。山地地形下的流域特征变化趋势性显著,适合山地中小流域的分辨率为最高分辨率,数据源为SRTM,重采样技术为最邻近分配法。丘陵、平原地形评价结果具有随机性。     

DEM空间尺度对岷江上游流域特征提取的影响

DEM分辨率是描述DEM地形精确程度的一个重要指标,同时也是决定DEM使用范围的一个主要影响因素。此处以岷江上游流域为研究区,Arc GIS为技术支撑,分析DEM空间尺度对流域特征提取的影响。首先,采用7组不同分辨率的DEM数据,通过5类不同特征参数的提取来进行DEM尺度效应的定量分析。其次,借鉴坡度中误差法思想和信息熵理论,综合分析高程、坡度和地面粗糙度来确定该地区DEM研究的分辨率合理范围。结论表明:随着DEM栅格大小的不断增大,高程区间和坡度随之减小;地面粗糙度的减小表现出地形的平坦化;信息熵所包含的内容减少;河网总长度和河网密度也随之变短变稀疏。文中岷江上游流域特征提取研究的DEM最佳空间分辨率区间为30~60 m。     

DEM分辨率对小流域地形水文特征提取的影响

基于ArcGIS水文分析工具研究DEM分辨率对提取流域地形和水文参数的影响,选择黄土丘陵沟壑区典型小流域—韭园沟流域为实验区,该流域地形复杂,沟壑纵横,DEM分辨率变化对其地形表达有很大影响。研究表明,DEM分辨率对小流域面积、流域高程、坡向的表达或提取精度影响较小,而对坡度、河道长度、河网密度和河道分级等因子提取有较大影响。     

SRTM(1″)DEM在流域水文分析中的适用性研究

高精度的数字高程模型(digital elevation model,DEM)数据是流域水文分析应用的基础。美国地质调查局新发布了全球高分辨率数字高程数据产品,其空间分辨率为1″(约为30 m)。为评价该数据在流域水文分析中的适用性,以鹤壁汤河流域为实验区,以机载LiDAR DEM数据为参考,统计了SRTM(1″)数据的高程误差,分析了坡度、坡向、地表覆盖等对误差的影响;在基于地形的水文分析中,统计分析了SRTM(1″)数据误差对地形湿度指数、坡度坡长因子以及汇流动力指数等地形指数计算的影响;最后选取流域汇水区面积、最长水流路径长度、形状系数、弯曲度系数等流域特征参数对两种DEM数据提取结果进行了对比。研究表明SRTM(1″)DEM数据具有较高的精度,原始数据均方根误差为5.98 m,在消除平面位移误差后减小为4.32 m。基于地形的水文分析表明SRTM DEM与LiDAR DEM计算结果具有一定的差异,地形湿度指数平均值略高,坡度坡长因子和汇流动力指数平均值偏低,离散度偏小,这与SRTM DEM在微地貌以及高坡度地形区存在失真相关。两种DEM数据提取流域特征参数差异较小。上述研究表明SRTM DEM(1″)数据在流域水文分析中具有较大的应用潜力。     

基于LRIS-3D建立高分辨率DEM的方法及对比研究

在基于LRIS-3D系统建立高分辨率DEM基础上,以黄土高原丘陵沟壑区桥沟小流域为对象,利用GIS工具,以三维激光扫描系统扫描数据为基础数据,研究基于DEM的数字地形特征和水文特征的提取与分析方法。研究结果表明：与普通DEM相比,高分辨率DEM提取研究区平均坡度变小、坡度标准差变大,总体地形向平坦转化,坡面曲率增大,沟壑密度增大,更详细地描述了地表特征。对流域水文过程分析、特别是对流域汇流的参数确定及汇流模型的建立有积极作用。     

不同分辨率SRTM-DEM的数字地形分析比较研究

以通化地区为试验区,利用Arc/Info软件,将原始的SRTM数据生成等高线,再插值生成不同分辨率的DEM数据,提取了高程差、坡度、坡向、地形阴影数字地形信息,并根据D8算法,对流域信息进行提取。结果表明:不同分辨率的DEM在描述地形的整体变化上存在的差异很小,但高分辨率的DEM可以更好地反映出地形的细微变化;在水文模拟方面,流域网络的数量及沟壑密度与DEM的分辨率成正相关的关系,但由于高分辨率的DEM信息冗余,在水文模拟方面,提取流域网络的时候会出现生成伪沟谷的现象。     

小波派生多尺度DEM的精度分析

利用陕北5 m分辨率DEM数据为基本数据,对Haar小波派生出一系列更低分辨率DEM进行复合精度分析。通过等高线套合、数据中误差以及表面重合指数等方法,分析其高程采样误差与空间分布;通过分析对比其在所提取的地面坡度、沟谷网络等地形因子上的差异,分析其地形描述误差。研究结果显示:小波派生多尺度DEM在精度的颓减上呈现指数形的变异规律,当达到三级重构DEM(40 m分辨率)时,其精度仍优于1:5万(25 m分辨率)DEM。该结果对于实现地形的有效简化与掌握多尺度DEM不确定性规律具有一定的意义。     

Python辅助下的坡度提取不确定性分析

以30 m空间分辨率的DEM为试验数据源,借助Python地理建模技术深入研究坡度提取的不确定性。以平均坡度来代表坡度的一般水平,将研究区划分为7种地貌类型,将30 m分辨率的DEM数据重采样成30~120 m分辨率的10组DEM数据,使用以Arc GIS平台和Python开发语言为基础的地理建模技术,定量分析平均坡度与DEM空间分辨率、区域地貌特征的关系,研究坡度提取的不确定性。结果表明:研究区内不同地貌区域提取的平均坡度都随DEM分辨率的减小而减小,衰减速率基本不变;其回归方程的常数项与所在地貌单元的沟壑密度呈二次函数变化特征;坡度提取的精度与DEM的分辨率呈正相关的关系;基于Python的地理建模技术有效地整合了坡度提取分析方法,极大地提高了分析效率;研究结果进一步验证了现有坡度提取方法的不确定性。     

等高线生成规则格网DEM适宜分辨率的选取方法研究

等高线数据是生产规则格网DEM的常见数据,生产过程中DEM适宜分辨率的选取直接决定DEM的地形表达精度,影响下一步数字地形分析的结果。本文以辽宁某丘陵样区1∶50 000地形图中等高线为基础数据,首先,基于整体地形特征及等高距对适宜分辨率做出大致判断,通过初步分析确定6种备选分辨率;然后,基于不同分辨率坡度均方根误差(Slope RMSE)在格网大小逐渐减小的过程中趋于稳定的特性确定适宜分辨率;最后,利用重构等高线与原始等高线的对比结果验证适宜分辨率选择的准确性。经过实验得到样区数据适宜分辨率为20 m。     

坡度随水平分辨率变化及其空间格局研究

以黄土丘陵沟壑区的县南沟流域为研究区,基于1∶1万地形图,利用ANUDEM软件生成5m到200m分辨率DEM,并利用Arc/Info中计算坡度的方法提取了各种分辨率的坡度。研究表明,随着DEM分辨率的降低,单个样点坡度值表现出不确定性,但同一坡度级所有栅格点的坡度均值呈现一定的规律性,低坡度段表现为先升高后降低,中坡度段呈现微弱变化,陡坡度段呈现对数降低趋势;沟沿线上坡度值呈比较剧烈的下降趋势、分水线和流水线上坡度缓慢下降。     

黄土丘陵沟壑第三副区水文地貌关系正确DEM的建立与评价

本文以黄土丘陵沟壑第三副区的藉河流域为研究区,利用ANUDEM软件和1:5万地形图研究了水文地貌关系正确DEM的建立方法,从派生等高线与原始数字化等高线对比等方面对建立的DEM进行了质量评价。并且与传统TIN方法建立的不同水平分辨率的DEM做了比较。结果表明:由等高线、高程点、河流和陡崖线在ANUDEM5.1中生成的DEM质量优于由等高线、高程点和地形特征点用TIN方法生成的DEM。ANUDEM建立的DEM更能精确地反映水文地貌特征。在此基础上,研究了确定集水面积阈值的方法,通过在Arc/Info环境下运行AML程序自动提取了基于水文地貌关系正确DEM的流域特征。     

Effect of Contour Intervals and Grid Cell Size on the Accuracy of DEMs and Slope Derivatives

Digital Elevation Models (DEMs) are indispensable tools in many environmental and natural resource applications. DEMs are frequently derived from contour lines. The accuracy of such DEMs depends on different factors. This research investigates the effect of sampling density used to derive contours, vertical interval between contours (spacing), grid cell size of the DEM (resolution), terrain complexity, and spatial filtering on the accuracy of the DEM and the slope derivative. The study indicated different alternatives to achieve an acceptable accuracy depending on the contour interval, the DEM resolution and the complexity of the terrain. The effect of these factors on the accuracy of the DEM and the slope derivative was quantified using models that determine the level of accuracy (RMSE). The implementation of the models will guide users to select the best combination to improve the results in areas with similar topography. For areas with variable terrain complexity, the suggestion is to generate DEMs and slope at a suitable resolution for each terrain separately and then to merge the results to produce one final layer for the whole area. This will provide accurate estimates of elevation and slope, and subsequently improve the analyses that rely on these digital derivatives.     

The Effect of DEM Raster Resolution on First Order, Second Order and Compound Terrain Derivatives

It is well known that the grid cell size of a raster digital elevation model has significant effects on derived terrain variables such as slope, aspect, plan and profile curvature or the wetness index. In this paper the quality of DEMs derived from the interpolation of photogrammetrically derived elevation points in Alberta, Canada, is tested. DEMs with grid cell sizes ranging from 100 to 5 m were interpolated from 100 m regularly spaced elevation points and numerous surface‐specific point elevations using the ANUDEM interpolation method. In order to identify the grid resolution that matches the information content of the source data, three approaches were applied: density analysis of point elevations, an analysis of cumulative frequency distributions using the Kolmogorov‐Smirnov test and the root mean square slope measure. Results reveal that the optimum grid cell size is between 5 and 20 m, depending on terrain com‐plexity and terrain derivative. Terrain variables based on 100 m regularly sampled elevation points are compared to an independent high‐resolution DEM used as a benchmark. Subsequent correlation analysis reveals that only elevation and local slope have a strong positive relationship while all other terrain derivatives are not represented realistically when derived from a coarse DEM. Calculations of root mean square errors and relative root mean square errors further quantify the quality of terrain derivatives.     

Cartosat-1 derived DEM (CartoDEM) towards Parameter Estimation of Microwatersheds and Comparison with ALTM DEM

Hydrologic analysis of microwatersheds is essential for water resources planning at large scale. Space based input for decentralized planning at panchayat level use high resolution DEM. Drainage and slope play important role in planning and Digital Elevations Models (DEM) are widely being used for estimation of hydrologic parameters which are useful as input for hydrologic models. The estimates vary as per resolution and type of DEM. This paper evaluates the suitability of DEM derived through Cartosat-1 satellite stereo data(CartoDEM) for hydrologic parameter estimation of microwatersheds and compares the results with Airborne Laser Terrain Mapper (ALTM) based DEM data. Comparison is based on the hydrologic parameters delineated in Geographical Information System. Microwatersheds are delineated and drainage length extracted using two different cell sizes for both DEMs. Correctness Index, Figure of Merit, visual comparison, Percent within buffer and Junction comparison method, compared extracted river network. Average watershed slope is calculated using three different methods. CartoDEM derived drainage is comparable with ALTM derived drainage. There is high correlation between Carto5 and Caro10 DEMs in terms of drainage delineation and slope calculation. Average watershed slope vary as per calculation methods but average channel slope value (S3) although less, is comparable across DEMs.     

Comparison of basin morphometry derived from topographic maps,ASTER and SRTM DEMs: an example from Kerala,India

The drainage network of a sixth-order tropical river basin, viz. Ithikkara river basin, was extracted from different sources such as Survey of India topographic maps (1: 50,000; TOPO) and digital elevation data of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) (30 m) and Shuttle Radar Topography Mapping Mission (SRTM) (90 m). Basin morphometric attributes were estimated to evaluate the accuracy of the digital elevation model (DEM)-derived drainage networks for hydrologic applications as well as terrain characterization. The stream networks derived from ASTER and SRTM DEMs show significant agreement (with slight overestimation of lower order streams) with that of TOPO. The study suggests that SRTM (despite the coarser spatial resolution) provides better results, in drainage delineation and basin morphometry, compared to ASTER. Further, the variability of basin morphometry among the data sources might be attributed to spatial variation of elevation, raster grid size and vertical accuracy of the DEMs as well as incapability of the surface hydrologic analysis functions in the GIS platform.     

Spheroidal equal angular DEMs: The specificity of morphometric treatment

Digital elevation models (DEMs) are commonly constructed using two main types of regular grids: plane square grids and spheroidal equal angular grids. Methods and algorithms intended for plane square‐gridded DEMs should not be directly applied to spheroidal equal angular DEMs. This is because these grids have fundamentally different geometry. However, some researchers continue to apply square‐grid algorithms to spheroidal equal angular DEMs. It seems appropriate to consider once again the specifity of morphometric treatment of spheroidal equal angular DEMs. This article, first, demonstrates possibilities of direct calculation of local, nonlocal, and combined morphometric variables from spheroidal equal angular DEMs exemplified by slope gradient, catchment area, and topographic index. Second, the article shows computational errors when algorithms for plane square‐gridded DEMs are unreasonably applied to spheroidal equal angular DEMs. The study is exemplified by two DEMs. A medium‐resolution DEM of a relatively small, high‐mountainous area (Mount Elbrus) was extracted from the SRTM1 DEM. A low‐resolution DEM of a vast region with the diverse topography (the central and western regions of Kenya) was extracted from the SRTM30_PLUS DEM. The results show that application of square‐grid methods to spheroidal equal angular DEMs leads to substantial computational errors in models of morphometric variables.