Global Digital Elevation Model Research Articles

Vertical accuracy assessment of global digital elevation models and validation of gravity database heights in Niger

ABSTRACT In this study, we assessed the vertical accuracy of ASTER GDEM (Advanced Space-borne Thermal Emission and Reflection Radiometer – Global Digital Elevation Model) version 2, AW3D30 (ALOS World 3D – 30m) and the 1 and 3 arc-seconds versions of SRTM (Shuttle Radar Topography Mission) in Niger Republic. We explored the GDEMs to evaluate large void and erroneous pixel areas. GDEMs were then compared to three kinds of ground control data located on several sites and all merged data after vertical datum matching. We also analysed the vertical accuracy by land cover and compared GDEMs to each other. We finally validated the gravity database heights by using the relatively most accurate GDEM. All GDEMs still contain void pixels except for SRTM3 CGIAR, it was then retained for the assessment with 1 arc-second GDEMs. The vertical accuracies in terms of RMS (Root Mean Square) and in m are: ASTER (6.2, 8.0, 9.8 and 9.2), AW3D30 (2.2, 2.1, 1.8 and 1.6), SRTM1 (3.8, 4.3, 2.5 and 2.9) and SRTM3 (3.7, 4.1, 2.4 and 2.7) compared to levelling data, local DEM of Imouraren, GPS (Global Positioning System) data and all merged data. Absolute height differences are less than 10 m at 74.00%, 99.99%, 99.91% and 99.98% for ASTER, AW3D30, SRTM1 and SRTM3, respectively. AW3D30 is the most accurate and ASTER is the least accurate. For all GDEMs, different accuracies were found depending on land cover classes that could be caused by the random spatial distribution of validation data. Small differences were observed between SRTM and AW3D30 and large values between the two models and ASTER similarly. The gravity database was validated using AW3D30, large values of height differences were found in the northern part in agreement with the database specifications and in the southern part indicating erroneous elevations.

Assessment of open source digital elevation models (SRTM-30, ASTER, ALOS) for erosion processes modeling

The relief has a major impact on the landscape`s hydrological, geomorphological and biological processes. Many geographic information systems used elevation data as the primary data for analysis, modeling, etc. A digital elevation model (DEM) is a modern representation of the continuous variations of relief over space in digital form. Digital Elevation Models (DEMs) are important source for prediction of soil erosion parameters. The potential of global open source DEMs (SRTM, ASTER, ALOS) and their suitability for using in modeling of erosion processes are assessed in this study. Shumsky district of Ternopil region, which is located in the Western part of Ukraine, is the area of our study. The soils of Shumsky district are adverselyaffected by erosion processes. The analysis was performed on the basis of the characteristics of the hydrological network and relief. The reference DEM was generated from the hypsographic data(contours) on the 1:50000 topographical map series compiled by production units of the Main Department of Geodesy and Cartography under the Council of Ministers. The differences between the reference DEM and open source DEMs (SRTM, ASTER and ALOS) are examined. Methods of visual detection of DEM defects, profiling, correlation, and statistics were used in the comparative analysis. This research included the analysis oferrors that occurred during the generation of DEM. The vertical accuracy of these DEMs, root mean square error (RMSE), absolute and relative errors, maximum deviation, and correlation coefficient have been calculated. Vertical accuracy of DEMs has been assessed using actual heights of the sample points. The analysis shows that SRTM and ALOS DEMs are more reliable and accurate than ASTER GDEM. The results indicate that vertical accuracy of DEMs is 7,02m, 7,12 m, 7,60 mand 8,71 m for ALOS, SRTM 30, SRTM 90 and ASTER DEMs respectively. ASTER GDEM had the highest absolute, relative and root mean square errors, the highest maximum positive and negative deviation, a large difference with reference heights, and the lowest correlation coefficient. Therefore, ASTER GDEM is the least acceptable for studying the intensity and development of erosion processes. The use of global open source DEMs, compared with the vectorization of topographic maps,greatly simplifies and accelerates the modeling of erosion processes and the assessment of the erosion risk in the administrative district.

Global open-access DEM performances in Earth's most rugged region High Mountain Asia: A multi-level assessment

Over the past decades, climate change has exerted pronounced influences on the cryo-hydrologic environments in High Mountain Asia (HMA). Digital elevation models (DEMs) are one of the critical datasets required in many hydrology- and cryosphere-related studies in HMA, which include estimations of glacier mass balances and lake water storage changes and hydrological runoff modelling. Several global or near-global coverage DEMs (e.g. SRTM and ASTER missions) have been widely utilized for such studies. However, a comprehensive assessment of the quality of these DEMs, particularly over the high-relief HMA area, is still lacking. This study investigated the performances of seven public freely-accessed DEM datasets (ASTER GDEM V2, SRTM-3 V4.1 DEM, SRTM-1 DEM, AW3D30 DEM, VFP-DEM, MERIT DEM, Seamless SRTM-1 DEM) over the HMA region by referring to high-accuracy elevation data from ICESat altimetry. We also provided an additional detailed assessment for typical lake basins and extremely rugged areas in the Himalayas by using available global positioning system (GPS) measurements and gridded SETSM DEM raster data. Results show that AW3D30 exhibits the highest accuracy in HMA land areas among these datasets. The accuracy of all studied DEMs demonstrates high spatial variation, which shows the strongest relationship with slope among several topographical factors, such as elevation and aspect. Over these rugged terrains with a large slope, such as the Hengduan Mountains and Himalayas, the vertical accuracy is relatively low in all investigated DEMs. We established empirical models for fitting the relationship between DEM vertical error and mean slope, which can be used to estimate the average elevation errors for any given local or basin-scale DEM grids. In addition, this study identified regions with anomalous elevation data in each dataset caused by the imperfect void-filling processing scheme. In sum, the 3-arc-second MERIT DEM is judged to be relatively dependable for HMA which not only achieves good performances in statistical error values but also retains few void-filling anomalies. The 1-arc-second AW3D30 could be the most promising product over HMA with its high spatial resolution and accuracy, although some void-filling anomalies need to be noted in some regions.

Mine landslide susceptibility assessment using IVM, ANN and SVM models considering the contribution of affecting factors.

The fragile ecological environment near mines provide advantageous conditions for the development of landslides. Mine landslide susceptibility mapping is of great importance for mine geo-environment control and restoration planning. In this paper, a total of 493 landslides in Shangli County, China were collected through historical landslide inventory. 16 spectral, geomorphic and hydrological predictive factors, mainly derived from Landsat 8 imagery and Global Digital Elevation Model (ASTER GDEM), were prepared initially for landslide susceptibility assessment. Predictive capability of these factors was evaluated by using the value of variance inflation factor and information gain ratio. Three models, namely artificial neural network (ANN), support vector machine (SVM) and information value model (IVM), were applied to assess the mine landslide sensitivity. The receiver operating characteristic curve (ROC) and rank probability score were used to validate and compare the comprehensive predictive capabilities of three models involving uncertainty. Results showed that ANN model achieved higher prediction capability, proving its advantage of solve nonlinear and complex problems. Comparing the estimated landslide susceptibility map with the ground-truth one, the high-prone area tends to be located in the middle area with multiple fault distributions and the steeply sloped hill.

The Devdoraki Glacier Catastrophes, Georgian Caucasus

This study analyses the Devdoraki Glacier surge type catastrophes since 1776, lead to human casualties, destruction of settlements and the international road in the Georgian Caucasus. According to archival data, at least six ice and ice-rock avalanches fell from the Devdoraki Glacier onto the Tergi (Terek) River valley during the period 1776–1876, the largest on June 18, 1776 and on August 13, 1832. The first blocked the Tergi River for three days and was breached catastrophically; the second was ~100 m high and ~2 km wide and its breach started after 8 hours. The most recent hazard occurred on May 17, 2014 killing nine people, and destroyed the Trans-Caucasus gas pipeline, Dariali Hydropower Plant (HPP) and international road. Using aerial and satellite imagery – Landsat, ASTER, SENTINEL along with the 30 m resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM; 17 November 2011) we have reconstructed this event. On the basis of subsequent detailed field observations, new geological and tectonic maps of the study region have been compiled. After that collapse we have registered ~180 m advance of the Devdoraki Glacier snout between 2014 and 2015, which was mostly caused by rock-ice avalanche deposits. This part of the glacier should be monitored continuously as it can raise debris flow activity in the future. We consider the main hypotheses behind these events, namely a) tectonic and seismic, b) permafrost, c) volcanic and d) morphological factors; interpret the data for mechanisms and velocities of the catastrophic movement and argue that the 2014 event should not be classified as a glacier surge, although the possibility of similar glacial surges can not be excluded. The Kazbegi-Jimara massif should be considered as a natural laboratory that enables the investigation of rock-ice avalanches and glacial mudflows.

Flash flood susceptibility modelling using geomorphometric approach in the Ushairy Basin, eastern Hindu Kush

This study focuses on flash flood susceptibility modelling using geomorphometric ranking approach in the Ushairy Basin. In the study area, flash floods are highly unpredictable and the worst hydrometeorological disaster. An advanced spaceborne thermal emission and reflection radiometer global digital elevation model was used as input data in a geographic information system environment to delineate the target basin. A total of 17 sub-basins were delimited using a threshold of $$4 \hbox {km}^{2}$$ . The attribute information of each sub-basin was analysed to compute the geomorphometric parameters by applying Hortonian and Strahler geomorphological models. The results were analysed and categorised into five classes using statistical techniques, and the rank score was assigned to each class of all parameters depending on their relation with flash flood risk. In this study, 16 parameters were analysed to quantify the geomorphometric number of each sub-basin depicting the degree of flash flood susceptibility. The geomorphometric number of each sub-basin was linked to the geo-database for spatial visualisation. The analysis reveals that extremely high, very high, high and moderate sub-basins susceptible to flash floods were spread over an area of 55%, 8.5%, 23.7%, and 11.5%, respectively. It was found that out of total settlements, 53% are located in the extremely highly and very highly susceptible sub-basins. In the study area, the upper reaches are characterised by snow-covered peaks, steep slopes and high drainage densities ( $${>}1.7 \hbox { km/km}^{2})$$ . The analysis further indicated that the flash flood susceptibility increases with the increase in area, relief and relief ratio of the sub-basins. Model accuracy was assessed using primary data regarding past flood damages and human fatalities. Similarly, socio-demographic conditions of each sub-basin were also compared and linked to the extent of flash flood susceptibility. This study may assist the district government and district disaster management authority of Dir upper to initiate flood risk reduction strategies in highly susceptible zones of the Ushairy Basin.

Accuracy assessment of ASTER, SRTM, ALOS, and TDX DEMs for Hispaniola and implications for mapping vulnerability to coastal flooding

Digital elevation models (DEMs) derived from remote sensing data provide a valuable and consistent data source for mapping coastal flooding at local and global scales. Mapping of flood risk requires quantification of the error in DEM elevations and its effect on delineation of flood zones. The ASTER, SRTM, ALOS, and TanDEM-X (TDX) DEMs for the island of Hispaniola were examined by comparing them with GPS and LiDAR measurements. The comparisons were based on a series of error measures including root mean square error (RMSE) and absolute error at 90% quantile (LE90). When compared with >2000 GPS measurements with elevations below 7 m, RMSE and LE90 values for ASTER, SRTM, ALOS, TDX DEMs were 8.44 and 14.29, 3.82 and 5.85, 2.08 and 3.64, and 1.74 and 3.20 m, respectively. In contrast, RMSE and LE90 values for the same DEMs were 4.24 and 6.70, 4.81 and 7.16, 4.91 and 6.82, and 2.27 and 3.66 m when compared to DEMs from 150 km2 LiDAR data, which included elevations as high as 20 m. The expanded area with LiDAR coverage included additional types of land surface, resulting in differences in error measures. Comparison of RMSEs indicated that the filtering of TDX DEMs using four methods improved the accuracy of the estimates of ground elevation by 20–43%. DTMs generated by interpolating the ground pixels from a progressive morphological filter, using an empirical Bayesian kriging method, produced an RMSE of 1.06 m and LE90 of 1.73 m when compared to GPS measurements, and an RMSE of 1.30 m and LE90 of 2.02 m when compared to LiDAR data. Differences in inundation areas based on TDX and LiDAR DTMs were between −13% and −4% for scenarios of 3, 5, 10, and 15 m water level rise, a much narrower range than inundation differences between ASTER, SRTM, ALOS and LiDAR. The TDX DEMs deliver high resolution global DEMs with unprecedented elevation accuracy, hence, it is recommended for mapping coastal flood risk zones on a global scale, as well as at a local scale in developing countries where data with higher accuracy are unavailable.

Country-scale discontinuity analysis of AW3D30 and SRTM Global DEMS: case study in Turkey

The quantitative model of the Earth is provided by optical and radar space-borne remote sensing global digital elevation models (GDEMs). GDEMs are fundamental for many geo-spatial analysis and demanded by several applications that need topographical data. Recently released ALOS World 3D 30 m (AW3D30) and 1 arc-second (~ 30 m) Shuttle Radar Topography Mission (SRTM) C-band GDEMs have the advantages of high quality and free availability from JAXA and NASA and much in demand in scientific community. In this paper, we comprehensively analyzed the discontinuities between AW3D30 and SRTM C-band GDEMs in country-scale calculating and interpreting the influence of terrain inclination and land cover classes. The coherence between two GDEMs was estimated by absolute horizontal and vertical accuracy analysis in the basis of model-to-model validation approaches. During the analysis, standard deviation and normalized median absolute deviation of height differences between GDEMs were utilized as the main coherence indicators. The frequency distribution of height differences and the incoherent outliers were presented by error distribution graphics and height error maps, respectively. The results clearly demonstrated the significance of ascending and descending orbits, terrain inclination, and land cover on the discontinuities.

Commentary: The Need for a High-Accuracy, Open-Access Global DEM

A Commentary on 'The Need for a High-Accuracy, Open-Access Global DEM' by Schumann, G. J.-P., and Bates, P. D. (2018). Front. Earth Sci. 6:225. doi: 10.3389/feart.2018.00225

Using direct transformation approach as an alternative technique to fuse global digital elevation models with GPS/levelling measurements in Egypt

Abstract Open global digital elevation models (GDEMs) represent a free and important source of information that is available to any country. Fusion processing between global and national digital elevation models is neither easy nor inexpensive. Hence, an alternative solution to fuse a GDEM (GTOPO30 or SRTM 1) with national GPS/levelling measurements is adopted. Herein, a transformation process between the GDEMs and national GPS/levelling measurements is applied using parametric and non-parametric equations. Two solutions are implemented before and after the filtration of raw data from outliers to assess the ability of the generated corrector surface model to absorb the effect of the outliers’ existence. In addition, a reliability analysis is conducted to select the most suitable transformation technique. We found that when both the fitting and prediction properties have equal priority, least-squares collocation integrated with a least-squares support vector machine inherited with a linear or polynomial kernel function exhibits the most accurate behavior. For the GTOPO30 model, before filtration of the raw data, there is an improvement in the mean and root mean square of errors by 39.31 % and 68.67 %, respectively. For the SRTM 1 model, the improvement in mean and root mean square values reached 86.88 % and 75.55 %, respectively. Subsequently, after the filtration process, these values became 3.48 % and 36.53 % for GTOPO30 and 85.18 % and 47.90 % for SRTM 1. Furthermore, it is found that using a suitable mathematical transformation technique can help increase the precision of classic GDEMs, such as GTOPO30, making them to be equal or more accurate than newer models, such as SRTM 1, which are supported by more advanced technologies. This can help overcome the limitation of shortage of technology or restricted data, particularly in developed countries. Henceforth, the proposed direct transformation technique represents an alternative faster and more economical way to utilize unfiltered measurements of GDEMs to estimate national digital elevations in areas with limited data.

Application of 30-meter global digital elevation models for compensating rational polynomial coefficients biases

Generation of precise digital elevation models (DEMs) from stereo satellite images by using rational polynomial coefficients (RPCs) usually needs several ground control points (GCPs). This is mainly due to RPCs biases. However, since GCPs collection is a time consuming and expensive process, global DEMs (GDEMs), as the most inexpensive geospatial information, can be used to improve stereo satellite imagery-based DEMs (IB-DEMs). In this study, a 2.5 D mutual information based DEM matching, between a GDEM and an IB-DEM, was introduced for bias correction of satellite stereo images. Three well-known 30-meter GDEMs, namely, SRTM, ASTER, and AW3D30, were used and compared to assess the efficiency of this approach. The performance of the proposed method was evaluated by processing the stereo images acquired by CARTOSAT-1 satellite from two regions with flat, hilly, and mountainous topography. Evaluation results revealed that the proposed method could significantly improve the geometric accuracy of IB-DEM using all GDEMs.

Layered compressive sensing reconstruction for non-scanning three-dimensional laser imaging

ABSTRACTAs an active remote-sensing technique, three-dimensional (3D) laser radar enables accurate target detection and identification. However, the resolution of obtained image is limited by the integrated level of the sensor array. In this article, we propose a layered compressive sensing reconstruction method for high-resolution 3D laser imaging. The range profile is first reconstructed by applying a designed range observation matrix to the original sampling data. According to the distribution of range values in the reconstructed range profile, the original sampling data are divided into several layers and the corresponding intensity images are reconstructed by different algorithms. The global intensity image is generated by the reconstructed intensity images with different range compensation coefficients. In our simulations based on real data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model Version 2 (ASTER GDEM V2) and Landsat-8 Operational Land Imager (OLI), the proposed method realised 3D laser imaging for complex landforms with a pixel resolution of , and reached a satisfactory performance for reconstructions of the range profile (peak signal-to-noise ratio (PSNR) = 33.08 dB, feature similarity (FSIM) = 0.9450) and the intensity image (PSNR = 20.63 dB, FSIM = 0.8893) with a subrate of 0.25.

Geomorphic evolution and neotectonics of the Qianhe River Basin on the southwest margin of the Ordos Block, North China

The Qianhe River Basin is located at the convergence zone of the northeastern margin of the Tibetan Plateau (NETP), the Ordos Block and the Qinling Mountains. A tectonic geomorphology study of the Qianhe River is significant for providing a deeper understanding of the tectonic transition between the NETP and the Ordos Block and the dynamic relationship of these three tectonic units. Based on Advanced Spaceborne Thermal Emission and Reflection global digital elevation model (ASTER-GDEM) data and geographic information system (GIS) techniques, four tectonic geomorphic indices, the hypsometric integral (HI), stream length-gradient (SL), drainage basin asymmetry (AF), and drainage basin shape (BS), were calculated and analyzed. Geologic evidence from field surveys, deformation measurements, and fault slip rate estimates was also obtained to further discuss the tectonic activity and tectonic geomorphic evolution model. Through analytical comparisons, we proposed that the variations in the applied geomorphic index values were not significantly affected by climate and lithology but indicated variations in related tectonic activity. The geomorphic index value analysis suggested relatively strong tectonic activity in Liupanshan Mountain and Longshan Mountain and northwestward tectonic tilting of the southwest margin of the Ordos Block. The actual mechanisms responsible for the observed variations in the Qianhe River Basin are the rapid uplift and northeastward extrusion of the Qinghai-Tibetan Plateau and the local tilting uplift of the southwestern Ordos Block.

European Digital Elevation Model Validation against Extensive Global Navigation Satellite Systems Data and Comparison with SRTM DEM and ASTER GDEM in Central Macedonia (Greece)

Digital elevation models (DEMs) are a widely used form of topographic information, with some of the most popular being the Shuttle Radar Topography Mission (SRTM) DEM and the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM). These two sources of topographical information are the main constituents of the European Union Digital Elevation Model (EU-DEM), which is a relatively new dataset of the EU’s Copernicus Land Monitoring Service. In this context, the purpose of this study was to validate EU-DEM for its vertical accuracy and to compare it with SRTM DEM and ASTER GDEM data. This was achieved in a Geographic Information System (GIS) environment, using extensive—in the order of tens of thousands of points—geodetic Global Navigation Satellite System (GNSS) measurements and appropriate pre-processing steps. The absolute elevation errors results had a Root Mean Square Error (RMSE) of 2.7 m at a 90% confidence level and characterize the performance of EU-DEM from local to regional scale, generally confirming that it is an enhanced source of elevation information when compared with its predecessors.

Evaluation of TanDEM-X 90 m Digital Elevation Model

ABSTRACTGerman Aerospace Center (DLR), EADS Astrium GmbH and Infoterra GmbH alliance came up with the idea of taking DTED-2 (Digital terrain elevation data, level-2) specifications to even higher standard of HRTE-3 (High resolution terrain elevation, level-3) in 2006, as a result TDX (TerraSAR-X, TanDEM-X) constellation was born. The mission was geared to create a rather sensitive, high precision 3 dimensional map of the entire Earth in seamless and very high quality. After Shuttle Radar Topography Mission (SRTM) in 2000 and its derivatives, along with numerous prior and subsequent other similar data, have practically set the standard for defining the topographical surfaces in global scale, the twin satellites acquired all of Earth’s land surfaces numerous times to produce varying resolution digital elevation models (DEM) between 2011 and late 2015. DEMs are widely used in many planning, decision making and engineering related projects. They provide sound backing for mankind’s endeavors. Ground resolution is the most sought after feature of any DEM. Finer resolution is usually associated with a better surface definition. Recently, an entirely new global DEM has been released DLR. The 90 m DEM is the latest variant derived from such an undertaking. This study aimed to examine the overall effectiveness of this alleged new data in four previously surveyed locations and against the performances of finer SRTM 1- and comparable SRTM 3 arc second data. The results showed that TanDEM-X 90 m data overestimated. They seemed to be rather accurate in flat to slightly undulating terrain, but overestimated in broken to treacherous terrain than both SRTMs. Root Mean Square Error was greater in site one and site four, and lower in site two and site three compared to both SRTM 1 and SRTM 3 arc second data.

Evaluasi Tingkat Akurasi Digital Elevation Model (DEM) SRTM dan ASTER GDEM dalam Pemodelan Daerah Aliran Sungai (DAS) Ciliwung

Availability of Digital Elevation Model (DEM) dataset and Geographic Information System (GIS), makes the watershed properties can be extracted automatically. There are two DEM providers which are freely accessible for research purposes and commonly use that is the Shuttle Radar Topographic Mission (SRTM) - DEM (30m) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model Version 2 (GDEM V2). Based on the result of modeling conducted at Ciliwung River Basin with Qgis application, area generated from SRTM data is 5% smaller than Ciliwung River Basin which obtained from BPDAS Ciliwung-Citarum as a reference, while the result of ASTER-GDEM data is 87% larger than reference. Linear Regression Test and t-Test performed on three segments of the watershed shows that the upstream of both samples gives a good accuracy result that is R2 = 0,999; P = 0,499 (SRTM) and R2 = 0,999; P = 0,481 (ASTER-GDEM), while in the middle and downstream segments respectively for both samples are SRTM with R2 = 0,993; P = 0,413 and R2 = 0,734; P = 0,088; and then ASTER-GDEM with R2 = 0,784; P = 0,00038 and R2 = 0,376; P = 1,27209 x10-22.

A mutual assessment of the uncertainties of digital elevation models using the triple collocation technique

ABSTRACT This study investigates the uncertainties of digital elevation models (DEMs) using the triple collocation (TC) method. DEMs from satellite missions are important for many geoscience disciplines and for economic benefits and are freely available. Validating DEMs is necessary to select an appropriate model for a given region and application. Provided certain assumptions about the error structure of any three data sets – measuring the same phenomenon – can be made, the TC approach can be used to provide an unbiased and scaled estimate of the error variances of the data sets, without requiring a reference data. We compared the TC approach to the traditional approach of using a reference data set using the Shuttle Radar Topography Mission version 4.1 (SRTM v4.1) DEM, ASTER (the Advanced Spaceborne Thermal Emission and Reflection Radiometer) GDEM (Global DEM) version 2, the 1 arc-minute global relief model (ETOPO1), a DEM compiled by the Survey and Mapping Division of Ghana (SMD DEM), and 545 ground control stations (GCSs). The error estimates for the DEMs via TC were considerably smaller than those obtained from the reference-based approach. As an example, the best performing DEM (SRTM v4.1) recorded a root-mean-square error (RMSE) of 15.601 m using the GCSs as reference, while its TC-derived accuracy was 6.517 m. We note that based on the results of the TC, the estimated error of the GCSs is approximately 14 m. Using a data set with an error of 14 m to validate other data sets is certainly bound to result in unfavorable results. Thus, we have demonstrated in this work that the TC approach is able to provide an unbiased error of DEMs. The approach is important even for regions where GCSs are highly accurate, but more so for regions with low-quality GCSs.

UAV-Derived Himalayan Topography: Hazard Assessments and Comparison with Global DEM Products

Topography derived using human-portable unmanned aerial vehicles (UAVs) and structure from motion photogrammetry offers an order of magnitude improvement in spatial resolution and uncertainty over small survey extents, compared to global digital elevation model (DEM) products, which are often the only available choice of DEMs in the high-mountain Himalaya. Access to fine-resolution topography in the high mountain Himalaya is essential to assess where flood and landslide events present a risk to populations and infrastructure. In this study, we compare the topography of UAV-derived DEMs, three open-access global DEM products, and the 8 m High Mountain Asia (HMA) DEMs (released in December 2017) and assess their suitability for landslide- and flood-related hazard assessments. We observed close similarity between UAV and HMA DEMs when comparing terrain elevation, river channel delineation, landside volume, and landslide-dammed lake area and volume. We demonstrate the use of fine-resolution topography in a flood-modelling scenario relating to landslide-dammed lakes that formed on the Marsyangdi River following the 2015 Gorkha earthquake. We outline a workflow for using UAVs in hazard assessments and disaster situations to generate fine-resolution topography and facilitate real-time decision-making capabilities, such as assessing landslide-dammed lakes, mass movement volumes, and flood risk.

Can regional to continental river hydrodynamic models be locally relevant? A cross-scale comparison

Regional to global river hydrodynamic models are now a reality, and have largely improved in the recent years due to increasing computation power, remote sensing datasets and new modeling methods. It is fundamental then to understand to which extent these models can provide locally relevant estimates of variables as discharge and water levels. It is addressed here by setting up three different versions of the large scale MGB hydrologic-hydrodynamic model with increasing spatial scale (global, regional and local), based on different topography datasets, cross section parameterization and reach lengths. These model versions are then compared to a detailed HEC-RAS model, set up with >620 locally surveyed cross sections in the Itajaí-Açu basin in Brazil. All models are run with calibrated rainfall-runoff parameters, so that effects of non-calibrated runoff fields or uncertain forcing data are not taken into consideration. To assist interpretation, three main requirements to define estimates from a river hydrodynamic model as locally relevant are defined: the model errors should be equal or smaller (i) than the accuracy requirement for a particular application and location, (ii) than typical local, reach scale models’ errors, and (iii) than observation uncertainties. Results then indicate that the regional and local MGB versions (and to a lesser extent, the global one) could estimate locally relevant discharges and water level anomalies for many parts of the basin. For absolute water levels, all models failed to provide RMSE smaller than 0.4 m basin-wide, although the local MGB model yields an average 2.1 m RMSE, in comparison to 4.4 m (regional) and 26.1 m (global). For flood extent, all model versions generally yielded unsatisfactory results with average Fit metric values smaller than 65%. Lastly, different setups of the regional MGB model were run to investigate the role of different factors in improving model estimates. Results showed that a coarse reach length (15 km) is unable to capture flood dynamics and water level variations in the basin, while a smaller 1 km long reach improves discharges, water level and flood extent. A locally derived DEM did not lead to significant improvements in relation to a global DEM. In turn, the smallest water level errors would be attained by using information from the in-situ cross sections in the regional models. This study’s outcomes are encouraging for the future development of regional to global hydrodynamic models, with new remote sensing techniques and higher computational power improving cross section estimation and model discretization.

Pixel-Based Geometric Assessment of Channel Networks/Orders Derived from Global Spaceborne Digital Elevation Models

Digital Elevation Models (DEMs) contribute to geomorphological and hydrological applications. DEMs can be derived using different remote sensing-based datasets, such as Interferometric Synthetic Aperture Radar (InSAR) (e.g., Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR) and Shuttle Radar Topography Mission (SRTM) DEMs). In addition, there is also the Digital Surface Model (DSM) derived from optical tri-stereo ALOS Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) imagery. In this study, we evaluated satellite-based DEMs, SRTM (Global) GL1 DEM V003 28.5 m, ALOS DSM 28.5 m, and PALSAR DEMs 12.5 m and 28.5 m, and their derived channel networks/orders. We carried out these assessments using Light Detection and Ranging (LiDAR) Digital Surface Models (DSMs) and Digital Terrain Models (DTMs) and their derived channel networks and Strahler orders as reference datasets at comparable spatial resolutions. We introduced a pixel-based method for the quantitative horizontal evaluation of the channel networks and Strahler orders derived from global DEMs utilizing confusion matrices at different flow accumulation area thresholds (ATs) and pixel buffer tolerance values (PBTVs) in both ±X and ±Y directions. A new Python toolbox for ArcGIS was developed to automate the introduced method. A set of evaluation metrics—(i) producer accuracy (PA), (ii) user accuracy (UA), (iii) F-score (F), and (iv) Cohen’s kappa index (KI)—were computed to evaluate the accuracy of the horizontal matching between channel networks/orders extracted from global DEMs and those derived from LiDAR DTMs and DSMs. PALSAR DEM 12.5 m ranked first among the other global DEMs with the lowest root mean square error (RMSE) and mean difference (MD) values of 4.57 m and 0.78 m, respectively, when compared to the LiDAR DTM 12.5 m. The ALOS DSM 28.5 m had the highest vertical accuracy with the lowest recorded RMSE and MD values of 4.01 m and −0.29 m, respectively, when compared to the LiDAR DSM 28.5 m. PALSAR DEM 12.5 m and ALOS DSM 28.5 m-derived channel networks/orders yielded the highest horizontal accuracy when compared to those delineated from LiDAR DTM 12.5 m and LiDAR DSM 28.5 m, respectively. The number of unmatched channels decreased when the PBTV increased from 0 to 3 pixels using different ATs.