Modified method for extraction of watershed boundary with digital elevation modeling

Boundary extraction of watershed is an important step in forest landscape research. The boundary of the upriver wa-tershed of the Hunhe River in the sub-alpine Qingyuan County of eastern Liaoning Province, China was extracted by digital elevation modeling (DEM) data in ArcInfo8.1. Remote sensing image of the corresponding region was applied to help modify its copy according to Enhanced Thematic Mapper (ETM) image抯 profuse geomorphological structure information. Both the DEM-dependent boundary and modified copy were overlapped with county map and drainage network map to visually check the effects of result. Overlap of county map suggested a nice extraction of the boundary line since the two layers matched precisely, which indicated the DEM-dependent boundary by program was effective and precise. Further upload of drainage network showed discrepancies between the boundary and the drainage network. Altogether, there were three sections of the extraction result that needed to correct. Compared with this extraction boundary, the modified boundary had a better match to the drainage network as well as to the county map. Comprehensive analysis demonstrated that the program extraction has generally fine precision in position and excels the digitized result by hand. The errors of the DEM-dependant extraction are due to the fact that it is difficult for program to recognize sections of complex landform especially altered by human activities, but these errors are discernable and adjustable because the spatial resolution of ETM image is less than that of DEM. This study result proved that application of remote sensing information could help obtain better result when DEM method is used in extraction of watershed boundary.

Determining topographic shielding from digital elevation models for cosmogenic nuclide analysis: a GIS model for discrete sample sites

Topographic shielding(TS) is an important factor in cosmogenic nuclide surface exposure dating. The development of geographic information systems(GIS) and the availability of digital elevation models(DEMs) make it possible to derive this factor directly from a DEM. Most available GIS models derive the TS factors for an area(all cells in a DEM) without the consideration of surface conditions of individual sites, such as the strike, dip,and height above ground, into the calculation. This paper presents a new GIS model to derive the TS factors for discrete sample sites. This model uses the Skyline and Skyline Graph functions in ArcGIS to extract the set of azimuth and elevation angles of topographic obstructions around each site from a DEM(considering the sample height above ground)and then incorporates the strike and dip information of the sample surface to derive the TS factor. All processing tools and steps are streamlined in ArcGIS modelbuilder and this model can be run like a standard ArcGIS geoprocessing tool. It provides an easy and user-friendly means to derive the TS factors for discrete samples based on a DEM and the measured strike, dip and sample height for each site.

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.

Determining Topographic Shielding from Digital Elevation Models for Cosmogenic Nuclide Analysis:a GIS Approach and Field Validation

Topographic shielding of cosmic radiation flux is a key parameter in using cosmogenic nuclides to determine surface exposure ages or erosion rates. Traditionally, this parameter is measured in the field and uncertainty and/or inconsistency may exist among different investigators. This paper provides an ArcGIS python code to determine topographic shielding factors using digital elevation models （DEMs）. This code can be imported into ArcGIS as a geoprocessing tool with a user-friendly graphical interface. The DEM-derived parameters using this method were validated with field measurements in central Tian Shan. Results indicate that DEM-derived shielding factors are consistent with field-measured values. It provides a valuable tool to save fieldwork efforts and has the potential to provide consistent results for different regions in the world to facilitate the comparison of cosmogenie nuclide results.

Effect of digital elevation models on monitoring slope displacements in open-pit mine by differential interferometry synthetic aperture radar

Displacement monitoring in open-pit mines is one of the important tasks for safe management of mining processes.Differential interferometric synthetic aperture radar(DInSAR),mounted on an artificial satellite,has the potential to be a cost-effective method for monitoring surface displacements over extensive areas,such as open-pit mines.DInSAR requires the ground surface elevation data in the process of its analysis as a digital elevation model(DEM).However,since the topography of the ground surface in open-pit mines changes largely due to excavations,measurement errors can occur due to insufficient information on the elevation of mining areas.In this paper,effect of different elevation models on the accuracy of the displacement monitoring results by DInSAR is investigated at a limestone quarry.In addition,validity of the DInSAR results using an appropriate DEM is examined by comparing them with the results obtained by global positioning system(GPS)monitoring conducted for three years at the same limestone quarry.It is found that the uncertainty of DEMs induces large errors in the displacement monitoring results if the baseline length of the satellites between the master and the slave data is longer than a few hundred meters.Comparing the monitoring results of DInSAR and GPS,the root mean square error(RMSE)of the discrepancy between the two sets of results is less than 10 mm if an appropriate DEM,considering the excavation processes,is used.It is proven that DInSAR can be applied for monitoring the displacements of mine slopes with centimeter-level accuracy.

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.

Facets of Uncertainty in Digital Elevation and Slope Modeling

This paper investigates the differences that result from applying different approaches to uncertainty modeling and reports an experimental examining error estimation and propagation in elevation and slope, with the latter derived from the former. It is confirmed that significant differences exist between uncertainty descriptors, and propagation of uncertainty to end products is immensely affected by the specification of source uncertainty.

Comparative study and error analysis of digital elevation model interpolations

Researchers in P.R.China commonly create triangulate irregular networks(TINs) from contours and then convert TINs into digital elevation models(DEMs).However,the DEM produced by this method can not precisely describe and simulate key hydrological features such as rivers and drainage borders.Taking a hilly region in southwestern China as a research area and using ArcGISTM software,we analyzed the errors of different interpolations to obtain distributions of the errors and precisions of different algorithms and to provide references for DEM productions.The results show that different interpolation errors satisfy normal distributions,and large error exists near the structure line of the terrain.Furthermore,the results also show that the precision of a DEM interpolated with the Australian National University digital elevation model(ANUDEM) is higher than that interpolated with TIN.The DEM interpolated with TIN is acceptable for generating DEMs in the hilly region of southwestern China.

LAN Tool: A GIS Tool for the Improvement of Digital Elevation Models Using Drainage Network Attributes

Digital Elevation Models (DEMs) are constructed using altitude point data and various interpolation techniques. The quality and accuracy of DEMs depend on data point density and the interpolation technique used. Usually however, altitude point data especially in plain areas do not provide realistic DEMs, mainly due to errors produced as a result of the interpolation technique, resulting in imprecise topographic representation of the landscape. Such inconsistencies, which are mainly in the form of surface depressions, are especially crucial when DEMs are used as input to hydrologic modeling for impact studies, as they have a negative impact on the model’s performance. This study presents a Geographical Information System (GIS) tool, named LAN (Line Attribute Network), for the improvement of DEM construction techniques and their spatial accuracy, using drainage network attributes. The developed tool does not alter the interpolation technique, but provides higher point density in areas where most DEM problems occur, such as lowland areas or places where artificial topographic features exist. Application of the LAN tool in two test sites showed that it provides considerable DEM improvement.

The J_2 invariant relative configuration of spaceborne SAR interferometer for digital elevation measurement

A 3-craft formation configuration is proposed to perform the digital elevation model （DEM） for the distributed spacebome interferometric synthetic aperture radar （InSAR）, and it is optimized by the modified ant colony algorithm to have the best compatibility with J2 invariant orbits created by differential correction algorithm. The configuration has succeeded in assigning the across-track baseline to vary periodically and with its mean value equal to the optimal baseline determined by the relative height measurement accuracy. The required relationship between crafts＇ magnitudes and phases is formulated for the general case of interferometry measure from non-orthographic and non-lateral view. The J2 invariant configurations created by differential correction algorithm are employed to investigate their compatibility with the required configuration. The colony algorithm is applied to search the optimal configuration holding the near-constant across-track baseline under the J2 perturbation, and the absolute height measurement accuracy is preferable as expected.

基于DEM的雷达阵地选址预处理方法研究

防空预警雷达阵地选址的优劣直接影响雷达本身及防空武器作战效能的发挥.针对基于数字高程模型(DEM)的常规实时计算方法存在耗时、耗力的问题,在明确阵地选址预处理内容的基础上,提出了预处理的具体流程和参数计算方法.通过数据预处理,以空间换时间的方式解决了阵地自动选址计算量大、耗时长的问题.实例仿真结果表明,该雷达阵地选址预处理方法大大缩短了自动选址时间,有效提高了选址效率.

DEM数据坐标转换和成果质量的检查方法

针对数字高程模型(DEM)数据三维坐标转换和转换成果质量检查的需求,本文研究了基于阿尔克·吉斯(ArcGIS)开发引擎平台的DEM数据的平面和高程坐标转换技术方法;同时根据DEM数据本身的特点,研究确定了合理的DEM数据转换成果质量检查内容和指标,解决了DEM数据转换成果质量检查标准的实际生产应用问题。本项目研究成果可保障北京市DEM数据在统一的基准下应用,推动与测绘地理信息相关的规划、建设和管理工作。

结合潮位与DEM的红树林遥感识别研究

以广西北部湾为研究区,针对潮位周期性变化导致稀疏低矮红树林难以被准确提取的问题,基于多潮位Landsat8 OLI图像和数字高程模型(DEM)数据,通过构建红树林识别决策树模型,并以支持向量机(SVM)为对照,评价结合潮位和DEM信息的决策树法提取红树林信息的可行性.研究结果表明:1)不同高度、不同密度以及不同潮位红树林之间光谱差异均较大,稀疏低矮红树林也与阴坡林地、水体-陆生植被混合像元光谱存在严重“异物同谱”效应;2)无论是基于低潮位、高潮位图像,还是多潮位图像,相比未区分高度和密度,在SVM中将细分为高密红树林和稀矮红树林,其总体精度(分为红树林和非红树林两类)可分别提高4.65、4.41和7.22个百分点;3)基于多潮位图像及DEM的决策树模型识别的总体精度和Kappa系数分别为98.80%和0.973,比SVM中最佳值分别高出1.62个百分点和0.035.因此,通过同时考虑红树林高度、密度、潮位和DEM等特征,可明显提高红树林遥感识别的精度.

基于多尺度DEM一体化融合技术构建水利枢纽三维地形技术研究与应用

本文通过研究多尺度DEM一体化融合技术,构建了水利枢纽的三维地形模型,并深入研究了该技术在数字孪生乌鲁瓦提水利工程汛期模拟、汛期预演、汛期预警中的应用。首先对不同尺度DEM数据进行预处理,如数据清洗和去噪,以提高数据质量,然后采用多尺度分析方法,将不同尺度的DEM数据进行一体化融合,得到更准确、全面的地形信息。该技术的核心是基于多分辨率频域融合方法,将高分辨率DEM数据与低分辨率的DEM数据结合起来。通过分析不同尺度上的地形特征,可以提取出更丰富的地貌信息,为水利工程的规划和设计提供了重要的参考依据。

融合自注意力机制与生成对抗网络的DEM空洞填充

针对现有数字高程模型(digital elevation model, DEM)数据空洞填充算法存在修复效果不连续、适用空值范围狭小以及细节重构丢失等问题,提出了一种融合自注意力机制的生成式对抗网络的DEM空洞填充方法。首先,构造自注意力机制提取DEM数据特征信息,改善DEM空洞填充结果高程值不连续和纹理细节缺失的问题。其次,在生成器中使用对称结构的卷积与反卷积网络结构,保证生成可靠度较高的数据以实现空洞区域填充,并利用判别器实现空洞填充结果的预分类。最后,结合重构损失函数进行训练,提升DEM空洞填充结果对异常值的鲁棒性,增强模型的回归能力。采用不同分辨率DEM数据进行空洞填充并与现有方法进行对比,结果表明:所提方法能够大幅提升填充精度,有效解决原始数据中存在的空洞问题。

基于DEM数据和遗传算法的对海雷达部署优化研究

针对当前雷达组网部署优化问题缺少对海探测研究,以及基于实际地形数据的遗传算法(GA)求解复杂度高的问题,开展了基于数字高程模型(DEM)数据和遗传算法的对海探测部署优化研究。基于预先阵地和对海探测雷达威力模型,所提的算法可有效减少遗传算法寻优空间,极大提高优化求解速度。仿真表明,该算法可获得和遍历法近似的最优结果,随着部署规模的增大,具有明显的速度优势。

Modelling of piping collapses and gully headcut landforms: Evaluating topographic variables from different types of DEM

The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model(DEM)data.The unique terrain characteristics of a particular landscape are derived from DEM,which are responsible for initiation and development of ephemeral gullies.As the topographic features of an area significantly influences on the erosive power of the water flow,it is an important task the extraction of terrain features from DEM to properly research gully erosion.Alongside,topography is highly correlated with other geo-environmental factors i.e.geology,climate,soil types,vegetation density and floristic composition,runoff generation,which ultimately influences on gully occurrences.Therefore,terrain morphometric attributes derived from DEM data are used in spatial prediction of gully erosion susceptibility(GES)mapping.In this study,remote sensing-Geographic information system(GIS)techniques coupled with machine learning(ML)methods has been used for GES mapping in the parts of Semnan province,Iran.Current research focuses on the comparison of predicted GES result by using three types of DEM i.e.Advanced Land Observation satellite(ALOS),ALOS World 3D-30 m(AW3D30)and Advanced Space borne Thermal Emission and Reflection Radiometer(ASTER)in different resolutions.For further progress of our research work,here we have used thirteen suitable geo-environmental gully erosion conditioning factors(GECFs)based on the multi-collinearity analysis.ML methods of conditional inference forests(Cforest),Cubist model and Elastic net model have been chosen for modelling GES accordingly.Variable’s importance of GECFs was measured through sensitivity analysis and result show that elevation is the most important factor for occurrences of gullies in the three aforementioned ML methods(Cforest=21.4,Cubist=19.65 and Elastic net=17.08),followed by lithology and slope.Validation of the model’s result was performed through area under curve(AUC)and other statistical indices.The validation result of AUC has shown that Cforest is the most appropriate model for predicting the GES assessment in three different DEMs(AUC value of Cforest in ALOS DEM is 0.994,AW3D30 DEM is 0.989 and ASTER DEM is 0.982)used in this study,followed by elastic net and cubist model.The output result of GES maps will be used by decision-makers for sustainable development of degraded land in this study area.

arcPycor:an open-source automated GIS tool to co-register elevation datasets

Subtraction of elevation datasets(e.g.digital elevation models(DEMs)and non-continuous elevation points)acquired at different times is a useful method to monitor landform surface change.Due to heavy post-processing of these elevation datasets,multi-source errors are introduced into the resulting elevation data products.To improve the estimation of elevation change,co-registration of elevation datasets is a prerequisite.This paper presents an open-source automated GIS tool(arc Pycor)for co-registering elevation datasets.arc Pycor is coded in Python 2.7 and is run via Arc GIS for Desktop.The performances of arc Pycor have been evaluated using a series of experiments.In benchmark tests,the resolved co-registration vectors of arc Pycor are compared to the predefined shift vectors obtained by artificially misaligning the slave DEMs from the master elevation datasets.Results show that arc Pycor is able to co-register DEMs with relative high accuracy and can well align slave DEMs to non-continuous elevation points,which indicates its robustness in co-registering of elevation datasets.arc Pycor is also able to co-register multi-sourced DEMs of different resolutions in mountain areas.

双站与重轨InSAR数据融合获取DEM的方法

多样性InSAR数据融合是弥补单基线InSAR生成DEM所存在不足的重要手段。鉴于以往的融合研究大多基于相同InSAR系统构型与工作模式的同源数据,文章提出一种双站与重轨InSAR异源数据融合获取DEM的方法和处理流程,重点研究了融合区域识别、重轨干涉大气校正等关键问题。为验证方法的有效性,使用一对天绘二号双站干涉数据结合多个异源重轨干涉数据进行融合,开展获取DEM实验,并采用GNSS实测数据和WorldDEM对DEM精度进行了验证。结果表明,融合后的DEM解缠错误及叠掩、阴影导致的无效点数明显减少,融合后的DEM相比单基线天绘二号干涉生成的DEM高程精度提高了11.6%。

不同森林覆盖类型对LiDAR生成DEM的精度影响分析

运用机载激光雷达(LiDAR)获取的高精度数字高程模型(DEM)是目前地学分析应用满足精细化要求的基础数据。目前对森林覆盖下DEM产品的精度影响分析依然有所欠缺。以实时动态载波相位差分技术(RTK)结合全站仪实测的高程碎部点与机载LiDAR数据生成的高精度DEM产品数值做差,进行单因素方差分析(ANOVA)检验以及独立样本T-检验。经多重比较分析(LSD)可知,以马尾松为代表的针叶林和以桉树、茶树、黄连木、荔枝、阔叶混合林为代表的阔叶林之间差值相差较大,说明针叶林和阔叶林两种不同森林覆盖类型的绝对精度存在差异。但Robust检验结果显示阔叶林地表DEM的精度均值相等性为1,说明阔叶林(以桉树、茶树、黄连木、荔枝、阔叶混合林林地为代表)地表DEM精度不受树种的影响。综上,阔叶林与针叶林的地表DEM精度差异显著,说明阔叶林和针叶林对机载LiDAR生成森林区域地表DEM存在一定的影响。