Geodynamic framework of large volcanic fields highlighted by SRTM DEMs: Method evaluation and perspectives exampled on three areas from the Cameroon Volcanic Line

This study is a part of a wider investigation to evaluate how much can be learnt by using low-cost methods such as systematic moderate-resolution remote sensing to map and quantify geological structures at the regional scale on very large volcanic provinces only partly studied in the field. Volcanic-centre and cinder-cone distribution, faults and structural lineaments are mapped combining Shuttle Radar Topography Mission (SRTM), Digital Elevation Models (DEMs) and Landsat satellite images. As an example of the method, we present the interpretation of structural data and morphological features of three contrasted areas from the Cameroon Volcanic Line (Tombel graben, Upper Benue valley, and Ngaoundéré area) for which local field studies are available for comparison. At a local scale, this remote-sensing method of mapping displays good to excellent correlations with previously published data and, by itself, it allows one to constrain the structural setting of each area. Numerical treatment of vent and cinder-cone localisation can be related to tension fractures (T direction), whereas numerical treatment of the lineaments constrains the associated fault system to a single transtensional (strike-slip + extension) Riedel type fracture network. The first results on the Cameroon Volcanic Line are promising and could be used at a larger scale on numerous volcanic provinces for which field data are not yet available.     

Testing new sources of topographic data for flood propagation modelling under structural,parameter and observation uncertainty

ABSTRACT

This study assessed the utility of EUDEM, a recently released digital elevation model, to support flood inundation modelling. To this end, a comparison with other topographic data sources was performed (i.e. LIDAR, light detection and ranging; SRTM, Shuttle Radar Topographic Mission) on a 98-km reach of the River Po, between Cremona and Borgoforte (Italy). This comparison was implemented using different model structures while explicitly accounting for uncertainty in model parameters and upstream boundary conditions. This approach facilitated a comprehensive assessment of the uncertainty associated with hydraulic modelling of floods. For this test site, our results showed that the flood inundation models built on coarse resolutions data (EUDEM and SRTM) and simple one-dimensional model structure performed well during model evaluation.

Editor Z.W. Kundzewicz; Associate editor S. Weijs     

Application of globally available,coarse-resolution digital elevation models for delineating valley bottom segments of varying length across a catchment

The worldwide availability of digital elevation models (DEMs) has enabled rapid (semi-)automated mapping of earth surface landforms. In this paper, we first present an approach for delineating valley bottom extent across a large catchment using only publicly available, coarse-resolution DEM input. We assess the sensitivity of our results to variable DEM resolution and find that coarse-resolution datasets (90 m resolution) provide superior results. We also find that LiDAR-derived DEMs produce more realistic results than satellite-derived DEMs across the full range of topographic settings tested. Satellite-derived DEMs perform more effectively in moderate topographic settings, but fail to capture the subtleties of valley bottom extent in mild gradient, low-lying topography and in narrow headwater reaches. Second, we present a semi-automated technique within ArcGIS for delineating valley bottom segments using DEM-derived network scale metrics of valley bottom width and slope. We use an unsupervised machine-learning technique based on the k-means clustering algorithm to solve a conundrum in GIS-based geomorphic analysis of rivers: the delineation of valley bottom segments of variable length. The delineation of valley bottom segments provides a coarse-scale entry point into automated geomorphic analysis and characterization of river systems. © 2020 John Wiley & Sons, Ltd.     

面向分布式水文模型的SRTM无效高程数据处理方法

获取高精度DEM是分布式水文模型开发和应用的基础,而最新发布的全球高分辨率SRTM数据在很大程度上解决了高分辨率DEM数据获取相对困难的问题,对于水文学研究具有重要意义。由于利用雷达技术获取地面高程数据技术本身的限制,SRTM原始DEM数据中存在着很多问题。本文以雪野水库区域为例,利用ASTER数据通过分析两种数据高程差异的分布特点对SRTM高程数据无效区域进行了填充,计算结果表明该方法可以提高无效数据处理结果的精度,是一种有效的获取相对完整地形数据的方法。     

基于均值变点分析的三峡库区河网提取研究

均值变点是最常见最直观的一种类型,它以平均值为分析对象,通过计算整个样本数据的方差(S)与分段样本的统计量(Si)之差来确定变点,变点的存在会使S和Si的差距增大。本文以SRTM DEM数据作为基本的地形数据,借助Arc Hydro Tools扩展模块,研究基于地表径流漫流模型的数字河网提取方法,采用均值变点分析法确定提取河网的阈值,并对结果进行分析。经对比发现,提取的主干河网与1∶250 000地形图主干上吻合较好,次流上更具真实性,提取结果可以用于各种地形分析。     

Capacity assessment of the Qattara Depression: Egypt as a sink for the global sea level rise

One of the most prominent geomorphological features in the Western Desert of Egypt is the occurrence of the Qattara Depression (20,800 km² or 2% of Egypt’s area), which has the deepest point in Africa. Topographic analysis of the depression was carried out using fine resolution digital elevation models acquired from the Advanced Spaceborne Thermal Emission and Reflection Radiometer-Global Digital Elevation Model (ASTER-GDEM) in order to assess the capacity of the depression. Results showed that the lower point in the depression occurs at ?136 m and its capacity at the sea level is 1340 billion m³, which equals 10 times the live storage capacity of the Lake Nasser behind the Aswan High Dam. Although the depression has the aptitude to be a reservoir for any augmentation in the sea level, detailed environmental impact assessment studies should be implemented to address geologic, climatic, biologic as well as socio-economic impacts.     

Effect of the SRTM global DEM on the determination of a high-resolution geoid model: a case study in Iran

Any errors in digital elevation models (DEMs) will introduce errors directly in gravity anomalies and geoid models when used in interpolating Bouguer gravity anomalies. Errors are also propagated into the geoid model by the topographic and downward continuation (DWC) corrections in the application of Stokes’s formula. The effects of these errors are assessed by the evaluation of the absolute accuracy of nine independent DEMs for the Iran region. It is shown that the improvement in using the high-resolution Shuttle Radar Topography Mission (SRTM) data versus previously available DEMs in gridding of gravity anomalies, terrain corrections and DWC effects for the geoid model are significant. Based on the Iranian GPS/levelling network data, we estimate the absolute vertical accuracy of the SRTM in Iran to be 6.5 m, which is much better than the estimated global accuracy of the SRTM (say 16 m). Hence, this DEM has a comparable accuracy to a current photogrammetric high-resolution DEM of Iran under development. We also found very large differences between the GLOBE and SRTM models on the range of −750 to 550 m. This difference causes an error in the range of −160 to 140 mGal in interpolating surface gravity anomalies and −60 to 60 mGal in simple Bouguer anomaly correction terms. In the view of geoid heights, we found large differences between the use of GLOBE and SRTM DEMs, in the range of −1.1 to 1 m for the study area. The terrain correction of the geoid model at selected GPS/levelling points only differs by 3 cm for these two DEMs.     

基于SRTM资料的小海岛CFD计算模型构建——以东澳岛为例

提出了一种利用SRTM资料构建海岛CFD计算模型的技术方法,并以珠江口的东澳岛为对象,进行了模型构建试验及边界层风场的数值模拟试验.实验结果表明,SRTM资料作为开源的资料,可有效地解析空间尺度在1 km以内数量级的海岛地形,并可以此为基础构建用于CFD模拟的计算模型,真实地刻画出岛屿的地形.利用计算模型进行的模拟试验表明,岛屿地形对风场的影响明显,且这种影响可以被计算模型有效地描述.所提出的技术未来在海岛风资源评估、风电场选址、污染扩散等领域有望发挥作用.     

大地重力学的新进展

介绍了当前利用卫星探测地球重力场的技术及其实践,也就是目前采用的高轨卫星追踪低轨卫星技术(hl-SST)、低轨卫星追踪低轨卫星技术(ll-SST)、卫星重力梯度测定技术(SSG),及其相应的正在运行的CHAMP、GRACE、GOCE卫星和考虑发射的GRACEFollow-On卫星。运行的三颗卫星所提供的地球重力场信息不论在精度和分辨率方面都是大地重力学的一个重大进展。介绍了地形数据在构建地球重力场模型中的作用和美国SRTM对全球地形数据的测量。最后介绍了EGM2008与我国已有大陆重力值的比较,平均差值约为11mgal,与我国大陆现有的高程异常值的比较,平均差值为27cm左右。     

A practical method for SRTM DEM correction over vegetated mountain areas

Digital elevation models (DEMs) are essential to various applications in topography, geomorphology, hydrology, and ecology. The Shuttle Radar Topographic Mission (SRTM) DEM data set is one of the most complete and most widely used DEM data sets; it provides accurate information on elevations over bare land areas. However, the accuracy of SRTM data over vegetated mountain areas is relatively low as a result of the high relief and the penetration limitation of the C-band used for obtaining global DEM products. The objective of this study is to assess the performance of SRTM DEMs and correct them over vegetated mountain areas with small-footprint airborne Light Detection and Ranging (Lidar) data, which can develop elevation products and vegetation products [e.g., vegetation height, Leaf Area Index (LAI)] of high accuracy. The assessing results show that SRTM elevations are systematically higher than those of the actual land surfaces over vegetated mountain areas. The mean difference between SRTM DEM and Lidar DEM increases with vegetation height, whereas the standard deviation of the difference increases with slope. To improve the accuracy of SRTM DEM over vegetated mountain areas, a regression model between the SRTM elevation bias and vegetation height, LAI, and slope was developed based on one control site. Without changing any coefficients, this model was proved to be applicable in all the nine study sites, which have various topography and vegetation conditions. The mean bias of the corrected SRTM DEM at the nine study sites using this model (absolute value) is 89% smaller than that of the original SRTM DEM, and the standard deviation of the corrected SRTM elevation bias is 11% smaller.