Global Digital Elevation Model Research Articles

Quality Assessment of TanDEM-X DEM 12m Using GNSS-RTK and Airborne IFSAR DEM: A Case Study of Tuba Island, Langkawi

Digital elevation models (DEMs) have been recognized as a primary spatial dataset and essential for numerous scientific applications. The advent of TerraSAR-X for digital elevation measurement (TanDEM-X) has opened a new potential to obtain an accurate DEM. Nowadays, the demand/use of TanDEM-X DEM in scientific applications has become increasingly popular as it offers an alternative to the widely used DEMs: ASTER and SRTM DEM. Although many researches have been conducted to assess the performance of the TanDEM-X DEM at different locations in the world, however, only several multi-regional studies have been performed in Malaysian region. Currently, there are two types of DEMs published by DLR i.e., non-open access (12m and 30m resolution) and open access (90m resolution). In this article, the accuracy of TanDEM-X 12m has been comprehensively and systematically evaluated using 1284 GNSS-RTK control points over Tuba Island and airborne IFSAR-DEM as a reference height. Besides, four available global DEMs: TanDEM-X 90m, AW3D30 DEM, SRTM DEM, and ASTER DEM have also been evaluated to identify the accuracy of TanDEM-X DEM 12m. Based on the evaluation using GNSS-RTK points, TanDEM-X 12m exhibits the highest accuracy with an RMSE of ±1.553m. Unexpectedly, AW3D30 DEM shows a better performance compared to TanDEM-X 90m with RMSE of ±1.964m, followed by SRTM DEM with RMSE of ±3.296m Meanwhile, ASTER DEM exhibits the lowest accuracy with RMSE of ±4.100m The comparison of TanDEM-X 12m and the well-known DEM, SRTM DEM with airborne IFSAR-DEM shows the opposite results. Based on the topographic profile at flat and forest area, the SRTM-DEM exhibits better accuracy than TanDEM-X 12m

Modelling the transport of tailings after Mount Polley tailings dam failure using multisource geospatial data

Tailings dams (TD) are usually located in valleys that are not easily accessible and hence one global digital elevation model (DEM) is used in most of the TD breach outflow modelling studies but the challenges this impose when calibrating visco-plastic rheological models has not been fully investigated. Implications of using GeoBase DEMs for model calibration is studied by comparing it with a model that is calibrated using a merged DEM generated from multiple products. The influence of rheological parameters, roughness coefficient and sediment concentration ( Cv) on simulated variables is studied. It was concluded that when GeoBase DEM was used for back analysis of the event, physically meaningful set of rheology values could not be assigned. Flow behaviour was strongly influenced by Cv and least influenced by Manning’s values. Runout distance was more sensitive to viscosity than yield stress. Mudflow depth and arrival time increased with increase in viscosity and Cv.

Developing a Spatiotemporal Model to Forecast Land Surface Temperature: A Way Forward for Better Town Planning

The change in the local climate is attributed primarily to rapid urbanization, and this change has a strong influence on the adjacent areas. Lahore is one of the fast-growing metropolises in Pakistan, representing a swiftly urbanizing cluster. Anthropogenic materials sweep the usual land surfaces owing to the rapid urbanization, which adversely influences the environment causing the Surface Urban Heat Island (SUHI) effect. For the analysis of the SUHI effect, the parameter of utmost importance is the Land Surface Temperature (LST). The current research aimed to develop a model to forecast the LST to evaluate the SUHI effect on the surface of the Lahore district. For LST prediction, remote sensing data from Advanced Spaceborne Thermal Emission and the Reflection Radiometer Global Digital Elevation Model and Moderate-Resolution Imaging Spectroradiometer sensor are exploited. Different parameters are used to develop the Long Short-Term Memory (LSTM) model. In the present investigation, for the prediction of LST, the input parameters to the model included 10 years of LST data (2009 to 2019) and the Enhanced Vegetation Index (EVI), road density, and elevation. Data for the year 2020 are used to validate the outcomes of the LSTM model. An assessment of the measured and model-forecasted LST specified that the extent of mean absolute error is 0.27 K for both periods. In contrast, the mean absolute percentage error fluctuated from 0.12 to 0.14%. The functioning of the model is also assessed through the number of pixels of the research area, classified based on the error in the forecasting of LST. The LSTM model is contrasted with the Artificial Neural Network (ANN) model to evaluate the skill score factor of the LSTM model in relation to the ANN model. The skill scores computed for both periods expressed absolute values, which distinctly illustrated the efficiency of the LSTM model for better LST prediction compared to the ANN model. Thus, the LST prediction for evaluating the SUHI effect by the LSTM model is practically acceptable.

Application of Unmanned Aerial Vehicle DEM in flood modeling and comparison with global DEMs: Case study of Atrak River Basin, Iran.

Digital Elevation Models (DEMs) play a significant role in hydraulic modeling and flood risk management. This study initially investigated the effect of Unmanned Aerial Vehicle (UAV) DEM resolutions, ranging from 1m to 30m, on flood characteristics, including the inundation area, mean flow depth, and mean flow velocity. Then, the errors of flood characteristics for global DEMs, comprising ALOS (30m), ASTER (30m), SRTM (30m), and TDX (12m) were quantified using UAV DEM measurements. For these purposes, the HEC-RAS 2D model in steady-state conditions was used to simulate the flood with return periods of 5- to 200 years along 20km reach of Atrak River located in northeastern Iran. Results indicated when UAV DEM resolution decreased from 1m to 30m, inundation area and mean flow depth increased 17.0% (R2=0.94) and 10.2% (R2=0.96) respectively, while mean flow velocity decreased 16.8% (R2=-0.94). Validation of the hydraulic modeling using the modified normalized difference water index demonstrated that the HEC-RAS 2D model in conjunction with UAV DEM simulates the flood with ⁓92% accuracy. Comparing the global DEMs with UAV DEM showed that the root mean square error (RMSE) values of the flow depth for ASTER, SRTM, ALOS, and TDX DEMs were 1.77, 1.12, 1.02, and 0.93m, and the RMSE values of the flow velocity for the same DEMs were 0.81, 0.66, 0.55, and 0.47m/s, respectively. Furthermore, TDX DEM with a 6.15% error in the inundation area was the nearest to UAV measurements. Overall, TDX DEM revealed a better performance in hydraulic modeling of the fluvial flood characteristics. Hence, it is recommended for environments where high-resolution topography data is scarce. The results of this study could potentially serve as a guideline for selecting global DEMs for hydraulic simulations.

A new global dataset of mountain glacier centerlines and lengths

Abstract. The length of a glacier is a key determinant of its geometry and is an important parameter in glacier inventories and modeling; glacier centerlines are the lines along which the main flow of glaciers takes place and, thus, are crucial inputs for many glaciological applications. In this study, the centerlines and maximum lengths of global glaciers were extracted using a self-designed automatic extraction algorithm based on the latest global glacier inventory data, digital elevation model (DEM), and European allocation theory. The accuracy of the dataset was evaluated through random visual assessments and comparisons with the Randolph Glacier Inventory (RGI) version 6.0. A total of 8.25 % of the outlines of the RGI were excluded, including 10 764 erroneous glacier polygons, 7174 ice caps, and 419 nominal glaciers. A total of 198 137 glacier centerlines were generated, accounting for 99.74 % of the input glaciers. The accuracy of glacier centerlines was 89.68 %. A comparison between the dataset and the previous dataset suggested that most glacier centerlines were slightly longer than those in RGI v6.0, meaning that the maximum lengths of some glaciers had been likely underestimated in the past. The constructed dataset comprises 17 sub-datasets, including global glacier centerlines, maximum lengths, and DEMs, all of which can be found at https://doi.org/10.11922/sciencedb.01643 (Zhang and Zhang, 2022).

Advances in InSAR Imaging and Data Processing

Through different phases of synthetic aperture radar (SAR) data acquired on different dates and/or at different satellite imaging locations, the interferometric SAR (InSAR) technique has long been used to map ground deformation or generate global digital elevation model (DEM) (e [...]

Detection, Morphometric Analysis and Digital Surveying of Archaeological Mounds in Southern Iraq with CartoSat-1 and COSMO-SkyMed DEMs

In Near and Middle Eastern archaeology, satellite-derived digital elevation models (DEM) of medium spatial resolution (≥30 m) are mostly used to locate and map archaeological mounds (namely ‘tells’), whereas high resolution DEMs (≤10 m) are still poorly exploited. To fill this gap, the 5 m resolution CartoSat-1 Euro-Maps 3D Digital Surface Model (DSM) is assessed vs. the 30 m Shuttle Radar Topography Mission (SRTM) global DEM, the Advanced Land Observing Satellite (ALOS) World 3D–30 m (AW3D30) and a 10 m COSMO-SkyMed DEM, on a test area in Wasit, southern Iraq, where the high density of tells is yet to be exhaustively documented. A total of 344 sites was mapped, with one order of magnitude improvement compared to previous mapping exercises, existing databases and historical maps. The morphometric analysis not only highlights the reliability of CartoSat-1 DSM height and volume estimates, but also suggests that, in the test area, the volume of a tell can robustly be calculated based on the simple knowledge of its basal area, following a quadratic function. Morphology and elevation of at least 53% irregularly shaped tells were impacted by anthropogenic disturbances. Morphometric indices (e.g., Topographic Position Index, DEViation from mean elevation) are a viable automated method to ease tells detection. When integrated with other satellite datasets (e.g., CORONA, Google Earth, Sentinel-2 imagery), the CartoSat-1 DSM can unveil morphological changes and support condition assessment. In Wasit, agriculture and modern development are among the major threats for tells preservation, alongside looting.

Sensitivity assessment of morphometric parameters of monogenetic volcanic landforms with global free DEMs

Improvements in the resolution of Digital Elevation Model (DEM) have greatly facilitated the research of small to moderate landforms such as dunes, landslides/rockfalls, moraines/drumlins and monogenetic volcanoes. Global free 30 m DEMs including data derived from Shuttle Radar Topography Mission (SRTM), Advanced Land Observing Satellite (ALOS) World 3D 30 m (AW3D30), and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER GDEM) are widely used. However, little is known of whether they can be used effectively in monogenetic volcanology. The focus of this study is to explore the accuracy and potential application of global free SRTM 30 m and AW3D30, as well as ASTER GDEM (previously studied) in monogenetic volcanic fields. We compared SRTM and AW3D30 with four reference higher-resolution DEM dataset, including National Elevation Dataset (NED) 10 m in Uinkaret Volcanic Field (UVF) (United States), WorldDEM 12 m in Longgang Volcanic Field (LVF) (China), Contour Line Based DEM (CLBD) 1 m in Jeju Island Volcanic Field (JIVF) (South Korea), and Light Detection And Ranging (LiDAR) 1 m in Lunar Crater Volcanic Field (LCVF) (United States). The results indicate that AW3D30 has higher accuracy than SRTM in all comparisons including elevation, slope angle and morphological parameters of scoria cones and associated lava flows. However, the accuracy of AW3D30 is almost the same as that of SRTM in that it is affected by slope angle, volume of volcanic edifices, and morphological features of scoria cones. In general, slope angle has a significant effect on the elevation and slope angle errors, which is consistent with previous studies. When the volume of the scoria cones is >5 × 106 m3 and the volume of the lava flows is above 10 × 106 m3, the average errors of their morphological parameters generated by SRTM and AW3D30 do not exceed 16.3 %. The morphological features are classified as crater (the central depression within a scoria cone), crater rim (the top 15 % of the highest elevations), lower flank (the lowest 15 % of the elevations), and middle flank (the remainder of a scoria cone). The area near the crater rim is often the area where larger errors occur, especially on the crater side. The middle and lower flank areas have milder errors. Additionally, the simulation of pre-eruptive surfaces should take into account the effects of certain factors such as roughness and flatness when calculating the volume. Overall, AW3D30 has the best potential in monogenetic volcano studies, followed by SRTM and ASTER GDEM.

The ATL08 as a height reference for the global digital elevation models

ABSTRACT High-quality height reference data are embedded in the accuracy verification processes of most remote sensing terrain applications. The Ice, Cloud, and Land elevation Satellite 2 (ICESat-2)/ATL08 terrain product has shown promising results for estimating ground heights, but it has not been fully evaluated. Hence, this study aims to assess and enhance the accuracy of the ATL08 terrain product as a height reference for the newest versions of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the Shuttle Radar Topography Mission (SRTM), and TanDEM-X (TDX) DEMs over vegetated mountainous areas. We used uncertainty-based filtering method for the ATL08 strong and weak beams to enhance their accuracy. Then, the results were evaluated against a reference airborne LiDAR digital terrain model (DTM), by selecting 10,000 points over the entire area and comparing the accuracy of ASTER, SRTM, and TDX DEMs assessed by the LiDAR DTM to the accuracy of the ASTER, SRTM, and TDX DEMs assessed by the ATL08 strong beams, weak beams, and all beams. We also detected the impact of the terrain aspect, slope, and land cover types on the accuracy of the ATL08 terrain elevations and their relationship with height errors and uncertainty. Our findings show the accuracy of the ATL08 strong beams was enhanced by 43.91%; while the weak beams accuracy was enhanced by 74.05%. Furthermore, slope strongly influenced ATL08 height errors and height uncertainty; especially on the weak beams. The errors induced by the slope significantly decreased when the uncertainty levels were reduced to <20 m. The evaluations of ASTER, SRTM, and TDX DEMs by ATL08 strong and weak beams are close to those assessed by LiDAR DTM points within 0.6 m for the strong beams. These findings indicate that ATL08 strong beams can be used as a height reference over vegetated mountainous regions.

Structural lineament mapping of Central-Eastern high atlas, Morocco, using ASAR/Envisat and SAR/sentinel 1B data

The Central-Eastern part of the High Atlas is dominated by carbonate of Mesozoic age which is affected by the Alpine Orogeny. The deformation manifest in area by different geological structures. The analysis of these later lead to their classification in different category for understanding the geodynamic of the area. This study focuses to map structural lineaments in the Central-Eastern High Atlas using two types of Radar data: Synthetic Aperture Radar (SAR)/Sentinel 1B with polarization (VV + VH) and Advanced Synthetic Aperture Radar (ASAR)/Envisat with polarization (VV + HH). This research aims to demonstrate the utility of Radar data for extracting structural lineaments in carbonate deposits. In this work, two techniques of processing data are used: First, the automatic extraction technique, we are employing the Algorithm Line Module of PCI Geomatica program, after the enhancement of images by applying the mean Co-occurrence filter. Second, the manual extraction technique, it was accomplished by applying directional filters with four directions (N00°, N45°, N90° and N135°) in order to highlight linear structures, then trace the detected lineaments. The synthetic maps of structural lineaments are developed by the two techniques. They are validated by using the lithologic maps extracted from Landsat Operational Land Imager (OLI), the previous researches in the study area, shaded relief extracted from ASTER Global Digital Elevation Model (GDEM), and field investigation data. The results present a good correlation between the direction of structural lineaments extracted from the satellite images and the field measurements. Therefore, the directions of lineaments extracted are N-S and E-W, NE-SW and NW-SE, especially the abundance of the direction N-S. This last one is perpendicular with the major faults. The density of structural lineaments in the study area is controlled particularly by the lithological nature and dynamic evolution, where the concentration is high in the Liassic carbonates. The geostatistical and spatial distribution of the structural lineaments led us to conclude that different tectonic factors are responsible for the distribution of lineaments in the surface of the study area. The comparison of two types of radar data shows that Envisat data is more efficient in the manual extraction than Sentinel 1B data. However, Sentinel 1B data is more efficient in the automatic extraction than Envisat data. This work identifies several families of structural lineaments which can be determined the tectonic phases of the Alpine orogeny affected the intracontinental Atlas basin.

Spatial Estimates of Flood Damage and Risk Are Influenced by the Underpinning DEM Resolution: A Case Study in Kuala Lumpur, Malaysia

The sensitivity of simulated flood depth and area to DEM resolution are acknowledged, but their effects on flood damage and risk estimates are less well understood. This study sought to analyse the relative benefits of using global DEMs of different resolution sizes, 5 m AW3D Standard, 12.5 m ALOS PALSAR and 30 m SRTM, to simulate flood inundation, damage and risk. The HEC-RAS 2D model was adopted for flood simulations, and the Toba River in the Klang River Basin in Malaysia was chosen for the case study. Simulated inundation areas from AW3D coincide the most with reported flooded areas, but the coarser-resolution DEMs did capture some of the reported flooded areas. The inundation area increased as the resolution got finer. As a result, AW3D returned almost double flood damage and risk estimates compared to ALOS PALSAR, and almost quadruple compared to SRTM for building-level damage and risk analysis. The findings indicate that a finer-resolution DEM improves inundation modelling and could provide greater flood damage and risk estimates compared to a coarser DEM. However, DEMs of coarser resolution remain useful in data-scarce regions or for large-scale assessments in efforts to manage flood risk.

Accuracy assessment of open-source global digital elevation models (GDEMs) with global navigation satellite system (GNSS) levelling

Shuttle Radar Topography Mission (SRTM), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER ), Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010), Advanced Land Observing Satellite World-3D (ALOSW3D), and TerraSAR-X Digital Elevation Measurement (TanDEM-X) are open-source Digital Elevation Model (DEM) datasets for environmental modelling and studies. The spatial resolution and vertical accuracy of DEM data sources play a significant role, particularly in dealing with land inundation, periodic flooding, and coastal erosion. In this study, the comparison between orthometric height, H from Global Navigation Satellite System (GNSS) observation, and DEM is performed to evaluate the accuracy of each DEM in terms of their Root Mean Square Error (RMSE) and correlation coefficient, R2 for monitoring the coastline. The result has indicated that TanDEM-X shows the smallest RMSE of 2.574 m compared to SRTM30, SRTM90, ASTER, GMTED10, and ALOSW3D with RMSE of 2.968 m, 3.006 m, 3.217 m, 2.975 m, and 2.876 m respectively. Furthermore, TanDEM-X illustrates the largest correlation coefficients, R2 of 0.959 m, compared to SRTM30, SRTM90, ASTER, GMTED10, and ALOSW3D at 0.891 m, 0.899 m, 0.590 m, 0.888 m 0.913 m respectively. Hence, the result has indicated that TanDEM-X is the best option among all DEMs for any topographic applications.

Global DEMs vary from one to another: an evaluation of newly released Copernicus, NASA and AW3D30 DEM on selected terrains of China using ICESat-2 altimetry data

ABSTRACT A good understanding of the quality of digital elevation model (DEM) is a perquisite for various applications. This study investigates the accuracy of three most recently released 1-arcsec global DEMs (GDEMs, Copernicus, NASA and AW3D30) in five selected terrains of China, using more than 240,000 high-quality ICESat-2 (Ice, Cloud and land Elevation Satellite) ALT08 points. The results indicate the three GDEMs have similar overall vertical accuracy, with RMSE of 6.73 (Copernicus), 6.59 (NASA) and 6.63 m (AW3D30). While the accuracy varies considerably over study areas and among GDEMs. The results show a clear correlation between the accuracy and terrain slopes, and some relationship between the accuracy and land covers. Our analysis reveals the land cover exerts a greater impact on the accuracy than that of the terrain slope for the study area. Visual inspections of terrain representation indicate Copernicus DEM exhibits the greatest detail of terrain, followed by AW3D30, and then by NASADEM. This study has demonstrated that ICESat-2 altimetry offers an important tool for DEM assessment. The findings provide a timely and comprehensive understanding of the quality of newly released GDEMs, which are informative for the selection of suitable DEMs, and for the improvement of GDEM in future studies.

Prediction of Wildfires Based on the Spatio-Temporal Variability of Fire Danger Factors

Most methods in the field of wildfire prevention are based on expert assessment of fire danger factors. However, their weights are usually assumed constant for the entire application area despite the geographical and seasonal changes of factors. This study aimed to develop a wildfire prevention method based on partial and general fire danger ratings taking into account their spatio-temporal variability. The study was conducted for Krasnoyarsk territory, Orenburg region and the Meschera lowland as the most forest, steppe and peat fire dangerous regions of Russia respectively. Surface temperature, moisture, vegetation structure, anthropogenic load, topography and their variation over subzones and in time were used as fire danger factors. They were evaluated by measuring parameters such as radiobrightness temperature, Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), distance to settlements and roads, elevation, slope and aspect. Materials from the Terra/Aqua, Sentinel-3, Landsat-8, Sentinel-2 satellites, ASTER Global Digital Elevation Model and Open Street Maps vector layers were used in the study. Correlation between these parameters and the actual fires in 2016-2018 was analyzed. Linear relationships were established, and correlation coefficients, equations of partial ratings and prevention 90%-threshold values were identified. On their basis, the parameter weights were computed to integrate them into the general fire danger rating. The developed method was validated using data over 2019. The results showed 67% confidence and 61% reliability of fire prevention along with the spatio-temporal patterns of fire danger factors. The method is recommended for preventing wildfires within the study areas and can be extend to similar regions.

ASTER GLOBAL DEM (GDEM) VERSION 3

Abstract. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a 14-channel imaging instrument operating on NASA’s Terra satellite since 1999. ASTER’s visible–near infrared (VNIR) instrument, with three bands and a 15 m Instantaneous field of view (IFOV), is accompanied by an additional VNIR band using a second, backward-looking telescope. Collecting along-track stereo pairs, the geometry produces a base-to-height ratio of 0.6. In 2009, the ASTER Science Team released Version 1 of the global DEM (GDEM) based on stereo correlation of 1.2 million ASTER scenes. The DEM has 1 arc-second latitude and longitude postings (∼30 m) and employed cloud masking to avoid cloud-contaminated pixels. The GDEM covers all of the Earth’s land surface from 83 degrees north to 83 degrees south latitude. Version 2 was released in 2011, with notable improvements in coverage and accuracy. In 2019, the final, Version 3, was released; again improving on coverage and removing almost all artifacts. Th GDEM is a unique, global high spatial resolution digital elevation dataset available to all users at no cost. In addition, a second unique dataset was produced and released. The raster-based ASTER Global Water Body Dataset (ASTWBD) identifies the presence of permanent water bodies, and marks them as ocean, lake, or river. An accompanying DEM file indicates the elevation for each water pixel. To date, over 110+ million 1×1 degree GDEM tiles have been distributed.

Problems of spatially distributed quantitative evaluation of soil erosion losses

Formulation of the problem. Water erosion of soils is the most widespread and dangerous soil degradation process in Ukraine. The development of an effective system of soil protection measures requires the use of spatially distributed mathematical models of soil erosion losses. This, in turn, highlights the problem of spatially distributed source data, which adequately reflect the spatial differentiation of factors of the erosion process, among which the main one is the relief. The purpose of the article. Assessing the adequacy of available spatially distributed source data, including cartographic and freely distributed global digital elevation models (DEMs), for spatially distributed quantitative assessment of soil erosion losses at the local level of territorial coverage is the aim of the article. Assessing from this point of view the scale of the original cartographic data, different global DEMs and their spatial resolution, as well as the degree of spatial generalization of the original data. Materials and methods. The solution of the set tasks was performed by the method of simulation modeling with the use of physical-statistical GIS-realized mathematical model of soil erosion-accumulation, developed at Odessa I. I. Mechnikov National University. Source data arrays were tested with DEMs SRTM90 and SRTM30 with a spatial resolution of 3 and 1 angular seconds, respectively, and AW3D30 with a spatial resolution of 1 angular second, as well as with cartographic DEMs based on topographic maps of scale 1:10000 and 1:25000. For testing the initial data, three test plots with an area of 2.67, 0.59 and 0.21 km2 were selected. The plots are located in the Balta district of Odessa region on the southern spurs of the Podolska upland. Results. It is established that freely distributed global digital elevation models SRTM and AW3D30 in the conditions of flat terrain do not always allow to adequately display the structure of slope runoff and, accordingly, to correctly perform calculations of soil erosion losses. The maximum deviation of the average soil erosion losses calculated for the test plots using global DEMs from the soil losses calculated using the reference DEM for SRTM30 and AW3D30 was 27%, for SRTM90 – almost 70%. The distribution of soil losses over the area of test plots obtained using different global DEMs differs even more. When using DEM based on topographic maps, reducing the scale of the original maps from 1: 10000 to 1: 25000 leads to a decrease in the average value of soil erosion losses by about 20% due mainly to reducing the magnitude and area of distribution of maximum soil losses, and on slopes of complex shape also due to changes in the area of accumulation zones. The degree of spatial generalization of the initial data significantly affects the results of the assessment of soil erosion losses both in relation to the average values and their distribution over the area. For small areas, the use of raster cells larger than 50 m is impractical. Scientific novelty and practical significance. It has been shown for the first time that in the conditions of flat terrain at the local level of spatial coverage, the freely distributed global DEM SRTM and AW3D30 are not always hydrologically correct. The reasons and conditions of violation of this correctness are specified. It has been established that the global DEM AW3D30 has local instrumental errors that may make it impossible to use it. The most realistic values of soil erosion losses are provided by DEM SRTM with a spatial resolution of 1 angular second.

Vertical accuracy comparison of multi-source Digital Elevation Model (DEM) with Airborne Light Detection and Ranging (LiDAR)

Digital Elevation Model (DEM) is a digital representation of ground surface topography or terrain. There are many freely available DEM data with a spatial resolution of 30 m to 90 m. Nevertheless, their vertical accuracy may vary, depending on the vegetation cover and terrain characteristics. This study examined the vertical accuracy of open-access global DEMs (ALOS PALSAR, ASTER GDEM3, SRTM, TanDEM-X) and fused DEM (EarthEnv-DEM90, MERIT DEM). Their performances were assessed using a Digital Terrain Model (DTM) generated using airborne LiDAR data that had an outstanding absolute vertical accuracy (mean error (ME) = 0.24 m; root mean square error (RMSEz) = 1.20 m). Height differences between the global DEMs and the LiDAR DTM were calculated and examined their performances by forested vs. non-forested, slope, and elevation classes. The results showed the MERIT DEM was superior to other DEMs in most of the testing methods. It outperformed other DEMs with an RMSEz value of 3.02 m in the forested areas, followed by ALOS PALSAR (9.29 m), EarthEnv-DEM90 (9.40 m), SRTM (9.80 m), TanDEM-X (10.41 m), and ASTER GDEM3 (12.57 m). The MERIT DEM also had the best accuracy in the higher elevation areas. Overall, the ASTER GDEM3 had the worst accuracies, with relatively large over-estimations compared to other DEMs. Despite its low spatial resolution, the MERIT DEM was the best for representing terrain elevation for applications over a large area.

An ecological assessment process based on integrated remote sensing model: A case from Kaikukang-Walagan District, Greater Khingan Range, China

As the impacts of global climate change, rapid economic development, and anthropogenic activities on the environment are intensifying, it is becoming increasingly apparent that we need to understand ecological conditions and their responses to climate change and human disturbances. The objective of this study was to present an ecological assessment of the Kaikukang–Walagan District using the remotely sensed ecological index (RSEI) and the newly introduced integrated ecological environment index (IEEI). This assessment will reveal the ecological responses to disturbances, and place-specific emphasis on ecological conservation. Various data such as Landsat images, advanced spaceborne thermal emission and reflection radiometer global digital elevation model (ASTER GDEM), moderate-resolution imaging spectroradiometer (MODIS) water vapor products, meteorological records, soil thickness, and soil N content data were collected and sampled. First, land surface temperature (LST), normalized difference vegetation index (NDVI), brightness, and wetness were obtained. Second, the RSEI was determined using LST, NDVI, brightness, and wetness via principal component analysis (PCA). Subsequently, IEEI was derived from the band operation between the standardized RSEI (RSEIS) and slope, soil thickness, and soil N content data. The results show that the mean RSEIS for 2000, 2002, 2007, 2011, and 2017 ranged from 0.26 to 0.48, and the coefficient of variation was 0.22. The number of areas with very good or excellent ecological conditions increased between 2000 and 2002, then fluctuated between 2002 and 2011, and reached a peak in 2017. The influence of climate change in the study area was not evident. The standardized IEEI (IEEIS) revealed that most of the study areas possessed excellent or very good ecological conditions; areas with good or fair ecological conditions were primarily located and bare land surrounded by vegetation, and areas with poor ecological conditions were primarily distributed in the urban areas of Walagan and Xiufeng. It was also shown that the IEEI is suitable for a comprehensive ecological assessment incorporating multiple ecological factors.

EVALUATION OF DEM DERIVED BY REPEAT-PASS X-BAND STRIPMAP MODE PAZ DATA

Abstract. This paper, presents the initial results of digital elevation model (DEM) extraction from PAZ Synthetic Aperture Radar (SAR) satellite images using repeat-pass interferometric analysis. We used a multi-temporal high-resolution strip-map mode X-band satellite image that has a single polarization. Five main classes, i.e., volcanic structures, agriculture, settlement, sand dune and plain bareland are considered depending on the structure of the region. Within the category, the coherence value and DEM value are evaluated. In the accuracy assessment analysis, a reference map produced from aerial photogrammetry is used. Additionally, global DEM TanDEM-X data is also tested in the study region. In the analysis, quality metrics, mean error (ME), root means square error (RMSE), standard deviation (STD), and the normalized median absolute deviation (NMAD) are used. The results showed that as the temporal baseline increases the coherence values and the quality of the DEM product decrease. The RMSE values range between 2.36 m to 7.09 m in different classes. The TanDEM-X data provided high accuracies over each class range from 0.88 m to 2.40 m. Since the study area is vulnerable to sinkhole formation, sinkhole-like signals were also observed in the interferograms obtained from different and sequential pairs. The high-resolution repeat-pass PAZ data pointed out its potential for interferometric products generation.

Spatiotemporal heterogeneity and driving mechanisms of Himalayan glacier mass change in the early 21st century

Glaciers in the Himalayan mountain ranges contain huge amounts of water and are essential for the water security of their downstream basins. Due to the spatiotemporal heterogeneity and uncertainty of the glacier mass change (GMC) in the Himalayas, more refined and deeper investigations on the GMC and its driving forces are needed to complement the current research. We present the mass balance of Himalayan glaciers during 2000 to 2013 using the latest global digital elevation models; this method focuses on establishing a high-coverage result of the GMC and resolving the problems of timestamps and penetration uncertainties. The GMC of the entire Himalayas is −0.32 ± 0.15 m w.e.yr − 1; most of the lost mass drains into the Indus and Ganges river basins. Glacier mass loss gradually decreases from east to west, with the East and Central Himalayas exhibiting the highest heterogeneity in the vertical and horizontal directions, respectively. We propose two multivariate regression models with 12 potential driving factors that explain 63% to 89% of the GMC across different regions of the Himalayas. Precipitation significantly influences changes in glacier mass throughout the Himalayas, whereas debris coverage and glacier size have insignificant effects on changing the glacier mass. Our analysis reveals that seasonal climate-driven changes in the glacier mass of the Himalayas may threaten the downstream water supply.