Accuracy Assessment of Alos W3d30, Aster Gdem and Srtm30 Dem: A Case Study of Nigeria, West Africa

Digital Elevation Models (DEMs) depict the configuration of the earth surface and are being applied in many areas in earth and environmental sciences. In this study, the accuracy of the Advanced Land Observing Satellite World 3D Digital Surface Model version 2.1 (ALOS W3D30), the Shuttle Radar Topography Mission Digital Elevation Model version 3.0 (SRTM30) and the Advanced Space borne Thermal Emission and Reflection Radiometer Global DEM version 2.0 (ASTER GDEM2) was statistically assessed using high accuracy GPS survey data. Root-Mean-Square errors of ~5.40 m, ~7.47 m and ~20.03 m were obtained for ALOS W3D30, SRTM30 and ASTER GDEM2 respectively. In further analyses, we discovered that ALOS W3D30 and SRTM30 were much more accurate in regions where the height intervals were within 201 m - 400 m and >801 m. ALOS W3D30 proved to be the most accurate DEM that best represents the topography of the earth’s surface and could be used for some earth and environmental applications in Nigeria. We recommend that this study should serve as a guide in the use of any of these DEMs for earth and environmental applications in Nigeria.

An Object-based Approach for Two-level Gully Feature Mapping Using High-resolution DEM and Imagery： A Case Study on Hilly Loess Plateau Region, China

Gully feature mapping is an indispensable prerequisite for the motioning and control of gully erosion which is a widespread natural hazard. The increasing availability of high-resolution Digital Elevation Model(DEM) and remote sensing imagery, combined with developed object-based methods enables automatic gully feature mapping. But still few studies have specifically focused on gully feature mapping on different scales. In this study, an object-based approach to two-level gully feature mapping, including gully-affected areas and bank gullies, was developed and tested on 1-m DEM and Worldview-3 imagery of a catchment in the Chinese Loess Plateau. The methodology includes a sequence of data preparation, image segmentation, metric calculation, and random forest based classification. The results of the two-level mapping were based on a random forest model after investigating the effects of feature selection and class-imbalance problem. Results show that the segmentation strategy adopted in this paper which considers the topographic information and optimal parameter combination can improve the segmentation results. The distribution of the gully-affected area is closely related to topographic information, however, the spectral features are more dominant for bank gully mapping. The highest overall accuracy of the gully-affected area mapping was 93.06% with four topographic features. The highest overall accuracy of bank gully mapping is 78.5% when all features are adopted. The proposed approach is a creditable option for hierarchical mapping of gully feature information, which is suitable for the application in hily Loess Plateau region.

Multi-Resolution Landslide Susceptibility Analysis Using a DEM and Random Forest

Landslide susceptibility (LS) mapping is a requisite for safety against sediment related disasters, and considerable effort has been exerted in this discipline. However, the size heterogeneity and distribution of landslides still impose challenges in selecting an appropriate scale for LS studies. This requires identification of an optimal scale for landslide causative parameters. In this study, we propose a method to identify the optimum scale for each parameter and use multiple optimal parameter-scale combinations for LS mapping. A random forest model was used, together with 16 geomorphological parameters extracted from 10, 30, 60, 90, 120, 150, and 300 m digital elevation models (DEMs) and an inventory of historical landslides. Experiments in two equal-sized (625 km2) areas in Niigata and Ehime, Japan, with different geological and environmental settings and landslide density, demonstrated the efficiency of the proposed method. It outperformed all other single scale LS analysis with a prediction accuracy of 79.7% for Niigata and 78.62% for Ehime. Values of areas under receiver operating characteristics (ROC) curves (AUC) of 0.877 and 0.870 validate the application of the multi-scale model.

Glacier extraction based on ASAR,DEM and texture feature of ASAR using SVM in the Western Qilian Mountains,Northwest China

This paper is focused on the method for extracting glacier area based on ENVISAT ASAR Wide Swath Modes （WSM） data and digital elevation model （DEM） data, using support vector machines （SVM） classification method. The digitized result of the glaci- er coverage area in the western Qilian Mountains was extracted based on Enhanced LandSat Thematic Mapper （ETM＋） imagery, which was used to validate the precision of glacier extraction result. Because of similar backscattering of glacier, shadow and wa- ter, precision of the glacier coverage area extracted from single-polarization WSM data using SVM was only 35.4%. Then, texture features were extracted by the grey level co-occurrence matrix （GLCM）, with extracted glacier coverage area based on WSM data and texture feature information. Compared with the result extracted from WSM data, the precision improved 13.2%. However, the glacier was still seriously confused with shadow and water. Finally, DEM data was introduced to extract the glacier coverage area. Water and glacier can be differentiated because their distribution area has different elevations; shadow can be removed from the classification result based on simulated shadow imagery created by DEM data and SAR imaging parameters; finally, the glacier coverage area was extracted and the precision reached to 90.2%. Thus, it can be demonstrated that the glacier can be accurately semi-automatically extracted from SAR with this method. The method is suitable not only for ENVISAT ASAR WSM imagery, but also for other satellite SAR imagery, especially for SAR imagery covering mountainous areas.

Amery ice shelf DEM and its marine ice distribution

The Amery Ice Shelf is the largest ice shelf in East Antarctica. A new DEM was generated for this ice shelf, using kriging to interpolate the data from ICE- Sat altimetry and the AIS-DEM. The ice thickness distribution map is converted from the new DEM, assuming hydrostatic equilibrium. The Amery Ice Shelf marine ice, up to 230 m thick, is concentrated in the northwest of the ice shelf. The volume of the marine ice is 2.38 × 10^3 km^3 and accounts for about 5.6% of the shelf volume.

Assessing cutter-rock interaction during TBM tunnelling in granite:Large-scale standing rotary cutting tests and 3D DEM simulations

The widespread utilisation of tunnel boring machines(TBMs)in underground construction engineering requires a detailed investigation of the cutter-rock interaction.In this paper,we conduct a series of largescale standing rotary cutting tests on granite in conjunction with high-fidelity numerical simulations based on a particle-type discrete element method(DEM)to explore the effects of key cutting parameters on the TBM cutter performance and the distribution of cutter-rock contact stresses.The assessment results of cutter performance obtained from the cutting tests and numerical simulations reveal similar dependencies on the key cutting parameters.More specifically,the normal and rolling forces exhibit a positive correlation with penetration but are slightly influenced by the cutting radius.In contrast,the side force decreases as the cutting radius increases.Additionally,the side force shows a positive relationship with the penetration for smaller cutting radii but tends to become negative as the cutting radius increases.The cutter's relative effectiveness in rock breaking is significantly impacted by the penetration but shows little dependency on the cutting radius.Consequently,an optimal penetration is identified,leading to a low boreability index and specific energy.A combined Hertz-Weibull function is developed to fit the cutter-rock contact stress distribution obtained in DEM simulations,whereby an improved CSM(Colorado School of Mines)model is proposed by replacing the original monotonic cutting force distribution with this combined Hertz-Weibull model.The proposed model outperforms the original CSM model as demonstrated by a comparison of the estimated cutting forces with those from the tests/simulations.The findings from this work that advance our understanding of TBM cutter performance have important implications for improving the efficiency and reliability of TBM tunnelling in granite.

GEDI与Tandem-X DEM估测密林林下地形性能评价

针对密林情况下,GEDI数据与现有的Tandem-X DEM数字地面模型估测林下地形精度没有进行整体评价问题,拟以密林情况作为主要分析场景,通过提取GEDI L2A数据产品对应光斑的经纬度、林下地形信息与数据质量筛选参数,开展数据质量筛选,用以估测基于GEDI数据的林下地形数据,与Tandem-X DEM数据估测密林情况下研究区林下地形开展比较,并进一步探究冠层高度、森林覆盖度与植被类型对估测精度的影响。GEDI与Tandem-X DEM的R~2分别为0.99和0.98,GEDI估测林下地形结果的RMSE、Average与STD分别6.49、-1.92、4.42 m, Tandem-X DEM估测林下地形结果的RMSE、Average与STD分别为18.15、14.63、7.35 m。GEDI数据在混交林和稀疏草原情况下RMSE与Average分别变化8.05 m和6.04 m, Tandem-X DEM数据在常绿针叶林与农田/天然植被情况下,RMSE与Average变化幅度为21.63、26.43 m。实验结果表明,GEDI与Tandem-X DEM数据与机载验证数据存在强相关性,且GEDI相对Tandem-X DEM数据表现出更优的评价标准;地表植被类型相对冠层高度和植被覆盖度会对两数据估测林下地形精度产生更大的影响。

基于倾斜三维模型与机载LiDAR点云的DEM快速更新

随着倾斜摄影技术的发展和实景三维建设的不断推进,地形级实景三维地理场景对DEM现势性要求日益提高。为了解决传统方法更新DEM成本高、工作量大的问题,本文提出了利用倾斜三维模型成果转换点云,融合两期DSM和DOM进行变化检测,替换已有机载LiDAR点云,快速更新DEM的方法,并通过项目验证了该方法的可行性,极大地节约了生产成本,为DEM更新提供了思路。

多源参考数据下的边坡DEM提取与精度分析

参考DEM是InSAR DEM提取精度分析中不可或缺的重要数据。考虑到当前可供使用的DEM数据层出不穷,如何选择可靠的参考DEM以解决不同地形DEM提取精度的需求,是DEM提取中一个亟待解决的问题。本文分别选择12.5 m的ALOS DEM、30 m的STRM DEM、90 m的STRM DEM作为参考DEM,依据2020年两景Sentinel-1A影像对德兴市部分地区边坡进行DEM数据提取,利用InSAR技术提取实验区的S1ADEM数据,并以ASTGTM DEM数据为参考,使用检测点法随机选择约300个检测点,选择相应的评价指标,分别对不同参考DEM下提取得到的S1ADEM进行精度检验。研究结果显示,使用12.5 m分辨率的ALOS DEM作为外部DEM,提取得到的S1ADEM精度更高,其在实验区A的RMSE为9.412 m,使用90 m的STRM DEM,提取得到的S1ADEM精度更低,其在实验区A的RMSE为10.293m。该实验为不同地形提取DEM提供了指导,能够帮助学者们在进行InSAR实验时更好地选择参考DEM,研究成果可为边坡灾害及预警提供重要的技术支持。

矿区沉陷DEM多重滤波方法研究

针对传统地表移动监测方法周期较长、工作量大的问题,通过无人机LiDAR和点云滤波获取地面点云,并构建沉陷DEM,实现地表沉陷监测的方法具有快速、高效的优势;由于现有点云滤波和插值算法构建的沉陷DEM模型仍会包含噪声,限制了该技术在矿区的普及,因此,进一步研究了沉陷DEM噪声的去除方法,对比分析了多重滤波与经典滤波方法。实验分析结果表明:在几种去噪方法中,中值滤波组合维纳滤波的去噪效果最好,保留了下沉盆地的细节特征,能够满足矿区地表形变监测的基本要求。

基于DEM的陕西省中小流域设计洪水软件开发

为规范和高效简捷地计算暴雨推求设计洪水,避免烦琐的查表和手工计算,针对陕西省中小流域设计洪水软件的空白,研发了基于DEM(Digital Elevation Model)的暴雨推求设计洪水的软件。该软件利用不同历时的点暴雨均值和变差系数等值线图生成DEM数据源,点选可自动获取工程所在位置的所有参数。采用推导的数值解法对产流过程和汇流过程进行程序开发,实现了陕西省无资料地区中小流域设计洪水计算的可视化高效计算和快捷规范的输出,显著提高了计算精度和工作效率。该软件算法和开发方法可推广应用于全国其他省市中小流域无资料地区设计洪水的计算。

一种DEM辅助下的LiDAR点云PTD滤波改进算法

针对传统渐进加密不规则三角网(PTD)滤波算法在复杂地形环境下需要反复调试地面点判断参数才能获得较好结果的局限性,以往期DEM数据提取的地形高程和地形梯度为辅助,改进PTD中初始地面种子点的选取方法,优化地面点判断参数,并对往期DEM数据和现势LiDAR点云数据之间的地形变化进行检测和处理,适用于不同坡度地形条件的复杂地形,滤波效果较好。对比分析实验数据精度可知,该算法能有效降低I类与II类误差,且样本分类精度均在90%以上,说明DEM辅助可切实提高PTD滤波算法的精度。

基于DEM的无人驾驶拖拉机前馈稳速控制

针对农田坡度变化影响无人驾驶农机行驶速度稳定性,进而降低播种均匀性和肥药施用精度等问题,该研究设计了一种基于农田数字高程模型(digital elevation model,DEM)和前馈控制策略的拖拉机稳速控制方法。首先建立坡地干扰补偿模型,基于拖拉机实时位置从农田DEM中提取前方作业路径的坡度信息,计算拖拉机前方目标速度补偿量,实现拖拉机行驶的稳速控制。以DF1204无级变速拖拉机为试验平台,在中国农业大学烟台研究院开展3组不同目标速度的上坡、平地和下坡行驶对比试验。试验结果表明,拖拉机以目标速度4、6和8 km/h行驶时,上坡行驶的实测速度均值分别为4.03、5.94和7.85 km/h,平地行驶的实测速度均值分别为4.04、6.02和8.03 km/h,下坡行驶的实测速度均值分别为4.00、6.10和8.19 km/h,与对照组相比,在上坡、平地和下坡行驶时的速度均方根误差平均分别降低了46.63%、21.92%和37.15%,试验组上坡和下坡行驶的实测速度均值更接近目标速度。所提方法可有效提高无人驾驶拖拉机在起伏农田的稳速控制精度,有助于提高农机作业质量。

基于DEM的旋转给料器叶片磨损特性研究

为探究旋转给料器工作时,颗粒在给料器内流动对给料器的磨损特性,使用SoildWorks软件构建旋转给料器叶片结构,借助EDEM软件对仿真模型进行离散建模分析,分别研究旋转给料器不同转速、不同叶片数下给料器叶片磨损情况,得出给料器叶片数相同,叶片转速为230 r/min、267 r/min与305 r/min时,随着叶片转速的增加,磨损量反而减小。当转速都为230 r/min,叶片数量为4、6和8时,6叶片的情况下给料器叶片的磨损程度最小。综合得出的结果,给料器可以设计成叶片数量为6、额定转速为305 r/min,这样对叶片的磨损程度不大,可以提高给料器的使用寿命。

融合生成对抗网络与SRTM的ASTER GDEM数据重建

航拍死角、匹配偏差、点位不足、云雾遮盖等易使数字高程模型(DEM)存在数据异常。鉴于光学立体摄影测量获得的ASTER GDEM受天气因素影响大,雷达测量得到的SRTM DEM受地形起伏因素影响大,为提高ASTER GDEM数据的质量,该文构建一种多源多尺度残差连接门控卷积生成对抗网络(Multi-Source and Multi-Scale Residual-Connected Gated Convolutional Generative Adversarial Network, MSSRGC-GAN),利用SRTM DEM数据辅助重建ASTER GDEM中异常数据,并以实验区范围内多组不同地貌的ASTER GDEM样本数据重建为例,对模型进行定量评价。结果显示:重建数据RRMSE小于0.06,R~2大于0.9,PSNR大于60,SSIM在0.999 5以上,优于反距离插值法和SRTM镶嵌法等传统方法以及无门控卷积模型和无空洞卷积模型等深度学习方法。

利用星载激光雷达数据校正森林区DEM误差

在植被区,通过光学遥感或InSAR技术生产的DEM产品不能反映真实林下地形高度。森林区DEM误差主要是植被高引起的系统偏差,植被覆盖度和地形是森林区DEM的主要误差来源。新一代星载激光雷达可以提供大量高精度林下地形控制点产品,为森林区DEM误差的纠正提供了新的契机。鉴于此,文章提出基于机器学习框架下顾及植被覆盖及地形因素的林区DEM误差校正方法。首先,获取高精度星载激光雷达地形控制点与DEM的地形残差;其次,利用光学遥感数据、SAR遥感数据及DEM产品数据计算与植被覆盖和地形有关的特征参数;最后,联合这些特征参数与获取的地形残差点分别建立不同类型DEM产品误差校正模型。选取位于美国田纳西州和北卡罗来纳州交界处的山地林区作为本研究的实验区。研究结果表明,相对原始DEM,校正高程误差后的DEM精度提升超过40%,有效校正了林区DEM误差。

基于ICESat-2的横断山区NASA DEM高程精度评价与误差校正

以星载激光雷达ICESat–2为参考数据源,将NASA DEM作为实验数据,分析了其在横断山区中西部复杂地形地貌区的整体高程精度;同时,研究了DEM误差与地表变量(如坡度、坡向、起伏度、植被覆盖度、土地利用类型等)之间的关系。为校正NASA DEM的高程误差,引入随机森林、反向传播神经网络、极度梯度提升树模型和轻量级梯度提升模型等4种机器学习方法,结合地表变量构建了高程误差校正模型并对校正后的NASA DEM进行精度分析。结果表明:NASA DEM的高程平均误差为–3.5 m,平均绝对误差为8.2 m,均方根误差为11.7 m,高程误差符合正态分布。NASA DEM的高程精度随着坡度、起伏度和植被覆盖度的增大而降低,不同坡向和土地利用类型下的高程精度存在较大差异。4种机器学习模型均能校正NASA DEM的高程精度,校正后的平均误差、平均绝对误差和均方根误差均有所改善;RF、XGBoost和LightGBM校正后的平均误差均为0 m;BPNN校正后平均绝对误差最低为6.9 m;BPNN和XGBoost校正后均方根误差最低均为10.6 m;BPNN校正后的R2值最高;BPNN在不同土地利用类型下的校正精度表现最佳。本研究结果为地学研究中选择和应用NASA DEM时提供精度上的参考依据,并通过引入多种机器学习模型,为NASA DEM及其他全球DEM产品高程误差校正研究提供了有效的方法论。

基于DEM数据预处理的小流域泥石流防治工程效果分析——以漳县方家沟泥石流为例

2013年7月22日岷县—漳县6.6级地震后,漳县方家沟爆发泥石流。为减轻泥石流的潜在危害,2015年在沟内修建了三级拦挡坝和排导槽,以调节泥石流峰值流量,减轻对下游堆积扇保护对象的威胁。当前研究区防治工程是基于前期泥石流发育特征所设计,未来防治效果有待检验。在野外调查的基础上,采用双线性插值法精细化处理DEM数据,结合高精度遥感影像,重新构建了方家沟小流域的拦挡坝以及地形模型,运用FLO-2D软件模拟分析了不同降水概率条件下方家沟泥石流的运动特征和危险性,以评价方家沟泥石流防治工程治理效果。结果表明:随着降雨强度的逐渐增大,拦挡坝对于泥石流的停淤能力逐渐增强,泥石流均未越过拦挡坝;泥石流流速限制效率达到了80.1%,大大弱化了泥石流冲击破坏能力;泥石流高危险区面积降低了约45.34%,有效地减小了泥石流的影响范围。综上所述,在构建方家沟拦挡坝的模拟条件下泥石流拦挡工程治理效果显著,研究成果可为类似小流域泥石流拦挡工程可行性检验提供借鉴。

基于高分7号卫星DEM的坡度坡长计算精度评价

[目的]坡度和坡长作为重要的地形因子,其计算的准确性直接影响坡面土壤侵蚀模型的评价精度。高分7号卫星的高精度高程测量能力在地形因子的准确提取上具有较大潜力,期望能将其利用到坡度和坡长提取之中,实现对地形的准确表达。这需要对利用高分7号卫星DEM提取坡度坡长的结果进行精度评价。[方法]利用地形因子(LS)计算工具,对陕西省吴堡县4个小流域高分7号卫星、1∶10000地形图、激光雷达影像生成的DEM进行坡度、坡长的提取。采用相关系数(r)、相对偏差和绝对偏差作为评价指标,评价高分7号提取地形因子的精度。[结果]与激光雷达和1∶10000地形图的坡度和坡长相比,高分7号提取的流域平均坡度偏低7.50%~9.02%,坡长偏大1.83%~19.35%,但坡长和坡度分级的面积比例并不存在显著差异;高分7号提取的坡度结果偏差(16.46%~44.26%)明显小于坡长的偏差(75.25%~140.87%);高分7号所提取的坡度坡长在沟间地上的相对偏差(坡度15.48%~56.63%,坡长50.02%~130.79%)明显低于沟谷地(坡度21.28%~63.61%,坡长93.01%~192.51%)。[结论]利用高分7号DEM提取坡度坡长时,对于获取坡长坡度面积分级和对指定点的坡度提取时是可行的,而对于指定点的坡长提取时则结果不够可靠,在研究流域中坡长坡度的空间分布上具有较大优势,而提取具体某一位置处的坡长坡度时的优势则不明显。

基于DEM的新疆土地利用变化时空格局

为了制定合理的土地利用政策和规划,促进新疆经济可持续发展,基于2000—2020年数据,通过引用土地利用动态度以及土地利用转移矩阵,同时叠合DEM高程数据,对新疆土地利用时空变化格局进行分析,探讨了土地利用变化的影响因素。结果表明,2000—2020年,新疆耕地面积增长最多,城乡、工矿、居民用地增幅较大,2005—2010年土地利用变化最为明显;各高程区间内土地利用类型面积变化差异较大;城市化的快速发展、高标准农田的建设、耕地保护制度的落实以及自然地理位置等因素影响着土地利用时空格局的变化。