Reference Digital Elevation Model Research Articles

InSAR Digital Surface Model Refinement by Block Adjustment with Horizontal Constraints

Abstract. Interferometric Synthetic Aperture Radar (InSAR) technology is an important method to generate digital surface model (DSM). The past studies on space-borne derived DSM most focused on the elevation correction, due to the relative low resolution of DSM product. As a large number of high-resolution satellite data emerge, the horizontal discrepancies are needed to be considered. This paper proposes a DSM block adjustment method with horizontal constraints, aimed at eliminating the horizontal errors that exist between multiple DSM scenes with overlaps, achieving high precision and consistency in both the horizontal and vertical dimensions. Using ICESat-2 ATL08 point clouds as absolute elevation control and a reference DSM for horizontal control, the adjustment equations are constructed based on the constraint of tie points and controls. The experiment selects 7 image pairs of China TH2-01 SAR satellite, corresponding ICESat-2 ATL08 point and AW3D30 as reference DEM. The block adjustment results show that the proposed method improves the absolute vertical accuracy from 3.78 m to 2.56 m and reduces the average horizontal standard deviation between the InSAR derived DSMs and the reference AW3D30 from 15.31 m to 9.08 m.

New approach for satellite DEM accuracy enhancement by combing machine learning, fuzzy majority voting, and weighted interpolation techniques

The digital elevation model (DEM) is crucial in many global and regional scientific studies in civilian and military applications. The aim of this research is to develop and test a new DEM approach for correcting the various errors in the Shuttle Radar Topography Mission (SRTM) digital elevation model. Firstly, the DEMs with the feature attributes from Sentinel-2 multispectral imagery are generated. Secondly, SRTM DEM with one band and attributes of a sentinel-2 image with eight bands are used as input data in supervised max-like hood, an artificial neural network (ANN), and support vector machine (SVM) classification models. Thirdly, ANN, supervised max-like hood, and SVM classification models, which have various properties, are fused by fuzzy majority voting (probability fusion). Finally, the fused probability is assigned for each pixel of the image, which has 12 fixed ground control points (GCPs), which is considered new input data for the inverse probability weighted interpolation (IPWI) approach to create the corrected SRTM elevations. The results were contrasted with a reference DEM (RD) created by image matching with Worldview-1 stereo satellite images, which had a 1-m vertical accuracy. The results of this study demonstrated that the RMSE of the original SRTM DEM was 5.95. On the other hand, the RMSE of the estimated elevations by the IPWI approach has been improved to 1.98 compared with that of the MLR method (3.01). The study shows a series of significant improvements in the SRTM when assessed with the reference DEM, with an RMSE reduction of (66.72%) when compared to the widely utilized multiple linear regression (MLR) method. It can be concluded that the elevation error of the original SRTM DEM is clearly reduced by the suggested approach.

A High-Precision Baseline Calibration Method Based on Estimation of Azimuth Fringe Frequency with THz Interferometry SAR

In this study, repeat-pass synthetic aperture radar interferometry (repeat-pass THz InSAR) is first extended to the terahertz band, and it has tremendous potential in the application of high-resolution three-dimensional (3D) imaging due to its shorter wavelength, larger bandwidth, and greater sensitivity to elevation variation. The super-resolution and high sensitivity of THz InSAR pose greater demands on the baseline calibration for high-precision digital elevation model (DEM) generation. To meet the elevation accuracy requirement of THz InSAR, we propose a baseline calibration method relying on the estimation of the azimuth fringe frequency (EAFF) of the interferometric phase. Initially, a model for non-parallel sampling path errors within the squint SAR repeat-pass interferometry was established, and then, we conducted the theoretical analysis of the phase errors induced by the non-parallel errors. Following this, using a reference DEM, the relationship between the fringe frequency of the error phase and the bias in the repeat-path positioning was established. This allowed the estimation of the position errors to be transformed into the frequency spectrum estimation based on the FFT, which would mitigate the impact of unknown SAR sampling positions. Ultimately, we investigated the accuracy of the proposed EAFF calibration method, and the simulation showed that it can achieve the theoretical accuracy when the correlation coefficient exceeds 0.3. Furthermore, we configured the repeat-pass THz InSAR system with the 0.3 THz stepped-frequency radar. Compared to the conventional calibration based on ground control points (GCPs), the 3D reconstruction of both a knife and a terrain model, calibrated using the proposed EAFF algorithm, demonstrated that the elevation accuracy can achieve millimeter-level precision across the entire image swath. The above results also proved the great potential of THz InSAR in high-precision 3D imaging and remote sensing.

3D GEO-REFERNECING OF FREE MODEL THROUGH 3D-TO-2D ALIGNMENTS AT THE CE-5 LANDING SITE

Abstract. The descent camera mounted on the CE-5 lander captured abundant images during the landing, which can be used to generate local terrain models with details from sub-meter to millimetre scales. But unlike Earth, high-precision control data are unavailable on the Moon especially for small regions like the landing sites, making it hard to define exact geo-reference of the local terrain models, which is essential for topographic and geomorphological mapping and analyses. To tackle this problem, this paper proposes a method for geo-referencing free 3D models generated from the CE-5 descent images based on low-resolution geo-referenced orbiter data. On account to the large discrepancy between the accuracies in the horizontal and vertical directions of orbiter data, the proposed method used two independent alignments in 3D and 2D spaces respectively to reduce the impacts of accuracy unevenness of the reference data. The 3D alignment is performed based on mass features to align the base-plane of the free model, and the 2D alignment is performed based on matched point features projected on the base-plane to define the scale and orientation of the model. After these the alignments, the free model is ultimately enriched with geo-reference information and used to generate fine-scale DEM and DOM of the CE-5 landing site. The average horizontal distance between the referenced data and the geo-referenced data is 2.19 m with a small standard deviation of 1.48 m, and the average height difference between the generated DEM and the reference DEM is 2.78 m, indicating a reliable 3D geo-referencing result.

Evaluation of multiple digital elevation models for hypsometric analysis in the watersheds affected by the opening of the Red Sea

Climate change is increasingly affecting the Red Sea-related terrains in Egypt and Saudi Arabia with a notable increase in heavy precipitation events. This highly vulnerable region to flashfloods and other climate change-driven hazards encompasses rough terrains with more than 11,000 basins/subbasins, which necessitates the accurate estimation of their hydrological and geomorphological parameters among which the hypsometric analysis. In this regard, The study examines the accuracy of the hypsometric analysis extracted using open source SRTM-1, ASTER-GDEM, Copernicus-GLO30, ALOS-DEM against high-resolution Topo-1 m and Topo-2.8 m DEMs for Talat Hamdh basin in Egypt and Wadi El-Salwely basin in Saudi Arabia, respectively. Copernicus-GLO30 shows the highest accuracy among all DEMs with the root-mean-squared–error (RMSE), mean elevation error, standard deviation, maximum and minimum absolute errors of 3.03, 2.0, 2.3, 11.7 and 0.1 m, respectively for Talat Hamdh basin. The findings also show that, regardless of the geology and geomorphic evolution of the basin, the hypsometric analysis is sensitive to the DEM type rather than the spatial resolution as Copernicus DEM yields similar basin numbers (a single basin) and area (1.366 and 141.9 km2) compared to the reference DEMs (1.408 and 154.4 km2) for Talat Hamdh and Wadi El-Salwely basins, respectively. Contrariwise, other open source DEMs yield multiple basins and thus significantly smaller basin area. Given the DEM-type dependence of the hypsometric analysis, the study recommends that large-scale hydrological and geomorphological analyses should consider using a high-resolution reference DEM on a local-scale basin to examine the accuracy of open source DEMs prior to conducting the analysis.

Mine Subsidence Monitoring Integrating DS-InSAR with UAV Photogrammetry Products: Case Studies on Hebei and Inner Mongolia

Frequent mining activities create a series of geological and environmental problems resulting in an immeasurable loss of life and property. Adopting effective technologies that monitor the surface subsidence of mining areas reliably and accurately is necessary. Targeting problems associated with conventional distributed scatterers interferometric synthetic aperture radar (DS-InSAR) technology, we propose a DS-InSAR technology integrating unmanned aerial vehicle (UAV) photogrammetry products divided into two key technical contents: generating an external reference digital elevation model (DEM) fused with UAV DEM and refining distributed scatterers candidates (DSCs) fused with an UAV digital orthophoto map (DOM). We selected two mining areas, one in Wu’an, Hebei, and the other in Inner Mongolia, with different surface cover types, mining depths, and topographies as the research area. We used Sentinel-1A SAR images covering a mine in Wu’an from 4 November 2018 to 4 March 2019 and a mining area in Inner Mongolia from 11 June 2018 to 21 October 2018 to compare and analyze the subsidence results. We also combined these results with data from their respective field observation stations to assess accuracy. We could apply DS-InSAR technology integrated with UAV photogrammetry products to the subsidence monitoring of two mining areas with different landforms and mining characteristics. Comparing with the leveling and total station, the experimental results show that the RMSE was reduced by about 2 mm in both mining areas, and accuracy for the Wu’an region improved to a higher degree than Inner Mongolia did. Furthermore, the refinement method of DS eliminated 965 and 2948 lower-quality DSCs in the two mining areas. These demonstrate that our proposed method can effectively improve the accuracy and reliability of subsidence results from two mining areas.

The impact of selection of reference samples and DEM on the accuracy of land cover classification based on Sentinel-2 data

Up-to-date and reliable information on land cover and land use status is important in many aspects of human activities. Knowledge about the reference dataset, its coverage, nomenclature, thematic and geometric accuracy, spatial resolution is crucial for appropriate selection of reference samples used in the classification process. In this study, we examined the impact of the selection and pre-processing of reference samples for the classification accuracy. The classification based on Random Forest algorithm was performed using firstly the automatically selected reference samples derived directly from the national databases, and secondly using the pre-processed and verified reference samples. The verification procedures involved the iterative analysis of histogram of spectral features derived from the Sentinel-2 data for individual land cover classes. The verification of the reference samples improved the accuracy of delineation of all land cover classes. The highest improvement was achieved for the woodland broadleaved and non- and sparce vegetation classes, with the overall accuracy increasing from 51% to 73%, and from 33% to 74%, respectively. The second objective of this study was to derive the best possible land cover classification over the mountain area in Norway, therefore we examined whether the use of the Digital Elevation Model (DEM) can improve the classification results. Classifications were carried out based on Sentinel-2 data and a combination of Sentinel-2 and DEM. Using the DEM the accuracy for nine out of ten land cover classes was improved. The highest improvement was achieved for classes located at higher altitudes: low vegetation and non- and sparse vegetation.

Topographic Mapping Capability Analysis of Moderate Resolution Imaging Camera (MoRIC) Imagery of Tianwen-1 Mars Mission

The Moderate Resolution Imaging Camera (MoRIC) onboard the orbiter of China’s Tianwen-1 Mars mission aims to map the surface of Mars globally and to explore its topography and geomorphology. This camera’s wide field of view can be used to overlap adjacent images sufficiently for topographic reconstruction. This study aimed to assess the topographic mapping potential of MoRIC images via a systematic accuracy analysis of MoRIC stereo mapping based on theoretical calculation and experimental validation. Experimental analyses were conducted using digital elevation models (DEMs) based on MoRIC images covering the Zhurong rover landing area and Mars Chart 11 region. Comparisons between these DEMs and reference DEMs revealed that the elevation accuracy of the former was approximately one ground sampling distance of the MoRIC image, which is consistent with the theoretical accuracy. Based on these results, MoRIC can be used to effectively map the Martian surface via stereo photogrammetry. These results serve as a useful guideline for topographic mapping based on MoRIC images and their application in various streams of research.

Preliminary Study on the Use of Digital Surface Models for Estimating Vegetation Cover Density in Mountainous Area

Digital surface model (DSM) has been widely available for mapping and was also sometimes used for mapping vegetation height. The authors conducted a preliminary study to evaluate the potential use of DSMs derived from ASTER, ALOS, and SRTM for estimating vegetation cover density in mountainous area. This study used NDVI and SAVI vegetation indices, in addition to forest cover density (FCD) model as references for evaluation. A DSM-based volume index (Volindex) concept is introduced, which is the product of the canopy height model (CHM) and the pixel area. CHM was derived from the value difference between the DSM and the reference DEM. The Volindex model was then compared with the NDVI, SAVI and FCD. We found that all DSM-based Volindex models are not accurate enough to represent the vegetation cover density, although the ALOS Palsar-based Volindex could reach 41.53% accuracy and was finally used to predict the vegetation cover density.

Tracking the evolution of the summit lava dome of Merapi volcano between 2018 and 2019 using DEMs derived from TanDEM-X and Pléiades data

At andesitic volcanoes, effusive lava flows and dome emplacement alternate with explosive, sometimes very destructive events. It is thus crucial to obtain quantitative information on the dome volume emplaced as well as on the extrusion rate. However, steep slopes and continuous activity make it difficult to install field instruments near many volcano summits. In this study, we take advantage of two high resolution remote-sensing datasets, Pléiades (optical acquisitions in tri-stereo mode) and TanDEM-X (radar acquisitions in bistatic mode), to produce twenty Digital Elevation Models (DEMs) over the summit area of Merapi volcano, Indonesia, between July 2018 and December 2019. We calculate the difference in elevation between each DEM and a reference DEM derived from Pléiades images acquired in 2013, in order to track the evolution of the dome in the crater. Uncertainties are quantified for each dataset by a statistical analysis of areas with no change in elevation. We show that the DEMs derived from Pléiades and TanDEM-X data are consistent with each other and provide good spatio-temporal constraints on the evolution of the dome. Furthermore, the remote-sensing estimate of the lava volume is consistent with local drone measurements carried out by BPPTKG at the time of dome growth. From our DEMs, we show that the dome growth was sustained by a relatively small effusion rate of about 0.0336 ± 0.0067 m3.s−1(2900 ± 580 m3/day) from August 2018 to February 2019, when it reached a height of 40 m (± 5 m) and a volume of 0.64 Mm3 (± 0.03 Mm3). The lava dome initially grew radially, and then extended asymmetrically to the northwest and southeast starting in October 2018. From February 2019 onwards, the dome elevation remained constant, but lava was continuously emitted. Lava supply was balanced by destabilization southwards downhill producing an accumulation zone of 400 m long and maximum 15 m (± 5 m) high with a volume of 0.37 Mm3 (± 0.29 Mm3). The measured accumulation rate between February and September 2019 is 0.0094 ± 0.001 m3.s−1(810 ± 90 m3/day). In late 2019, several minor explosions partially destroyed the center of the dome. This study highlights the strong potential of the joint use of TanDEM-X and Pléiades DEMs to quantitatively monitor domes at andesitic stratovolcanoes.

Historical Structure from Motion (HSfM): Automated processing of historical aerial photographs for long-term topographic change analysis

Precisely measuring the Earth’s changing surface on decadal to centennial time scales is critical for many science and engineering applications, yet long-term records of quantitative landscape change are often temporally and geographically sparse. Archives of scanned historical aerial photographs provide an opportunity to augment these records with accurate elevation measurements that capture the historical state of the Earth surface. Structure from Motion (SfM) photogrammetry workflows produce high-quality digital elevation models (DEMs) and orthoimage mosaics from these historical images, but time-intensive tasks like manual image preprocessing (e.g., fiducial marker identification) and ground control point (GCP) selection impede processing at scale. We developed an automated method to process historical images and generate self-consistent time series of high-resolution (0.5–2 m) DEMs and orthomosaics, without manual GCP selection. The method relies on SfM to correct camera interior and exterior orientation and a robust multi-stage co-registration approach using modern reference terrain datasets for geolocation refinement. We demonstrate the method using scanned images from the North American Glacier Aerial Photography (NAGAP) archive collected between 1967 and 1997. We present results for two sites with variable photo acquisition geometry and overlap — Mount Baker and South Cascade Glacier in Washington State, USA. The automated method corrects initial camera position errors of several kilometers and produces accurately georeferenced, high-resolution DEMs and orthoimages, regardless of camera configuration, acquisition geometry, terrain characteristics, and reference DEM properties. The average RMS reprojection error following bundle adjustment optimization was 0.67 px (0.15 m) for the 261 images contributing to 10 final DEM mosaics between 1970 and 1992 at Mount Baker, and 0.65 px (0.13 m) for the 243 images contributing to 18 individual DEMs between 1967 and 1997 at South Cascade Glacier. The relative accuracy of elevation values in the historical time series stacks was 0.68 m at Mount Baker and 0.37 m at South Cascade Glacier. Our products have reduced systematic error and improved accuracy compared to DEM products generated using SfM with manual GCP selection. Final elevation change measurement precision was ∼0.7–1.0 m over a 30-year period, enabling the study of processes with rates as low as ∼1-3 cm/yr. Our results demonstrate the potential of this scalable method to rapidly process archives of historical imagery and deliver new quantitative insights on long-term geodetic change and Earth surface processes.

Monitoring glacier thinning rate in Rongbuk Catchment on the northern slope of Mt. Qomolangma from 1974 to 2021

Glacier melting in the Himalayas provides indispensable water resources for downstream inhabitants. Glacier mass balance (MB) studies have important implications for hazard management of glacial lake outburst floods (GLOFs). However, Himalayan glacier MB results vary considerably among different studies with large uncertainties in satellite-based geodetic measurements, highlighting the necessity for further independent investigations and validation from multiple satellite platforms. Based on InSAR, photogrammetry, and laser altimetry techniques, we generate nine data sets of surface elevation differences (Dh) to study glacier geodetic MB in Rongbuk Catchment at the northern slope of Mt. Qomolangma. The data sets include five consecutive time periods over the last 48 years, i.e., 1974–2000, 2000–2006, 2006–2012, 2012–2015, and 2015–2021, and four overlapping periods of 1974–2012, 1974–2015, 2000–2015, and 1974–2021. The main results are summarized as follows. 1) Based on common reference DEM, geodetic MB was −0.21 ± 0.11 m w.e.a–1 in 1974–2000, −0.22 ± 0.05 m w.e. a–1 in 1974–2015, and −0.20 ± 0.03 m w.e. a–1 in 1974–2021. Geodetic MB presented negative twice since 2000 as measured by ordinary, consecutive short-term analysis, which was −0.41 ± 0.11 m w.e.a–1 in 2000–2006, −0.50 ± 0.54 m w.e.a–1 in 2006–2012, and −0.45 ± 0.11 m w.e.a–1 in 2015–2021. 2) Data validation by in-situ stake-observations at 5350, 5450, and 5500 m a.s.l in 1959–1960 and the 2000s, our results demonstrated convincing altitude effects on glacier change. Between 5150 m a.s.l. and 5800 m a.s.l., Dh presented a more downwasting rate with increasing altitude. While above 5800 m a.s.l., Dh became less negative with increasing altitude, and glaciers presented thickening trend above 6200 m a.s.l. 3) With the difference of Dh by 10 m altitude intervals (DDh), we located a sharp surface lowering zone on the debris-covered glacier tongue at 5240 ± 20 m in the 1970s. We postulated that it could be the glacier terminus under debris cover, which moved upward by 190 ± 20 m in the past five decades. With DDh, we also defined the turning point altitude at 5800 m ± 20 m, where Dh began to increase to be less negative with altitude. Moreover, summer temperature change and the number of melting days clearly explained the Dh change with altitude. 4) Glacier contribution to runoff was estimated by 30 ± 16 % from 1974 to 2021, however, our data also showed that approximately 70 % of runoff was from melting glaciers in 2015–2021, implying an amplifying effect of recent global warming on glacier contributions. In summary, our findings proved that DDh was an effective indicator for exploring mountain glacier change. The varying results revealed here indicates that more studies would be helpful to define and predict glacier, climatic and hydrological changes in the Himalayas with multiple techniques and observations based on a common reference over long term.

Influence of Block Geometry Configuration on Multi-Image Dense Matching

Digital photogrammetry is a widespread surveying technique in different fields of application due to its flexibility, versatility and cost-effectiveness. Despite its increasing automation and simplicity, a proper image block design is crucial to ensure high standards of performance and accuracy. Studies on camera network design have been largely dealt with in the scientific literature with reference to image orientation process, while they are still poor on dense matching. This paper investigates the influence of different block geometry configurations on multi-image dense matching. Starting from the same orientation solution, dense matching was performed considering different combinations of number of images and base length distance between the first and the last image within a strip. The raster Digital Elevation Models (DEM) resulting from each sequence of images were compared with a reference DEM to assess accuracy and completeness. The tests were conducted using different cameras and at various test sites to assess different survey conditions and generalize the findings. The presented results provide some operational guidance on block geometry optimization to maximize the accuracy and completeness.

A Novel Topography Retrieval Algorithm Based on Single-Pass Polarimetric SAR Data and Terrain Dependent Error Analysis

Polarimetric synthetic aperture radar (PolSAR) data provide an alternative way for topography retrieval, especially when limited PolSAR data are available. This article proposes a novel topography retrieval algorithm based on the Lambertian backscatter model that further improves the vertical precision of digital elevation model (DEM) generation and requires only one flight. The key idea of the proposed algorithm is to avoid data fluctuations caused by the ratio of the azimuth slope angle to the polarimetric orientation angle (POA). The previous research has confirmed the feasibility of generating a DEM based on single-pass PolSAR data, but its effect on the quality of reference DEM has not been well-explained. To analyze this effect, a large number of experiments on DEM with different resolutions are conducted. In addition, an in-depth analysis of non-linear and terrain-dependent errors is performed. The L-band PolSAR data of NASA/JPL TOPSAR and ALOS-2 PALSAR-2 and interferometric SAR (InSAR) DEM data are used to verify the proposed algorithm. The experimental results show that PolSAR data can be used as an additional reliable information source for DEM fusion under certain conditions to improve the quality of public DEM.

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.

Application of Multi-Channel Convolutional Neural Network to Improve DEM Data in Urban Cities

A digital elevation model (DEM) represents the topographic surface of the Earth and is an indispensable source of data in many applications, such as flood modeling, infrastructure design and land management. DEM data at high spatial resolution and high accuracy of elevation data are not only costly and time-consuming to acquire but also often confidential. In this paper, we explore a cost-effective approach to derive good quality DEM data by applying a multi-channel convolutional neural network (CNN) to enhance free resources of available DEM data. Shuttle Radar Topography Mission (SRTM) data, multi-spectral imaging Sentinel-2, as well as Google satellite imagery were used as inputs to the CNN model. The CNN model was first trained using high-quality reference DEM data in a dense urban city—Nice, France—then validated on another site in Nice and finally tested in the Orchard Road area (Singapore), which is also an equally dense urban area in Singapore. The CNN model not only shows an impressive reduction in the root mean square error (RMSE) of 50% at validation site in Nice and 30% at the test site in Singapore, but also results in much clearer profiles of the land surface than input SRTM data. A comparison between CNN performance and that of an earlier conducted study using artificial neural networks (ANN) was conducted as well. The comparison within this limited study shows that CNN yields a more accurate DEM.

Automatic selection of permanent scatterers-based GCPs for refinement and reflattening in InSAR DEM generation

ABSTRACT In DEM generation using interferometric synthetic aperture radar (InSAR), the ground control points (GCPs) for refinement and reflattening are usually selected by manual selection, field surveying, GPS points and existing basemaps, which may not be completely suitable for consequent processes. We proposed a new method (auto-PS-GCP) of GCP selection based on permanent scatterers, which automatically defines the thresholds for the coherence, amplitude, and amplitude dispersion index to select permanent scatterer as the GCPs. The GCP thinning (auto-PS-GCP-Thin) was further conducted considering the point density, distances among points and terrain conditions. We used a three-stage assessment that includes: (1) phase stability and intensity of the GCPs, (2) RMSEs of the elevations between GCPs and homonymous points in the reference DEM, and (3) generated DEM accuracy. Three areas respectively in the plain, hilly and mountainous regions were selected to verify the proposed methods. The assessment using both SRTM DEM andICESat-2 points shows that the DEM accuracy of auto-PS-GCP-Thin was improved by 20%∼30% for different areas compared to the manual, where the best DEM accuracy of 4.71 m was found in the plain area. It is concluded that the proposed methods are effective and reliable in various areas with different terrain conditions.

A new approach for 2-D and 3-D precise measurements of ground deformation from optimized registration and correlation of optical images and ICA-based filtering of image geometry artifacts

High resolution satellite images with improved spatial and temporal resolution provide unprecedented opportunities to monitor Earth Surface changes in 2D and 3D due, for example, to earthquakes, sand dune migration, ice flow, or landslides. The volume of imagery available for such measurements is rapidly growing but the exploitation of these data is challenging due to the various sources of geometric distortions of the satellite imagery. Here we propose a new approach to extract high-quality surface displacement in 3D based on the correlation of multi-date and multi-platform high resolution optical imagery. We additionally show that when a large enough volume of data is available, it is possible to separate the deformation signal from the artifacts due to the satellite jitter and misalignment of the CCDs, which, together with topographic artifacts, are the main source of noise in the measurements. Our method makes use of a reference DEM, but the outcome is independent of the characteristics of the chosen DEM. We use the case-example of the ground deformation caused by the Ridgecrest earthquake sequence to assess the performance of our proposed approach. We show that it outperforms the more standard approach which combines 2-D correlation and DEM differencing. With our technique, we were able to generate high quality measurements of coseismic ground displacement with GSD of 2.4 m, and uncertainties at the 90% confidence level on the NS, EW and vertical displacement measurements of 0.6 m, 0.7 m, and 0.6 m respectively.

Assessment of ICESat-2’s Horizontal Accuracy Using Precisely Surveyed Terrains in McMurdo Dry Valleys, Antarctica

This article presents an assessment of the horizontal accuracy and precision of the laser altimetry observations collected by NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission. We selected the terrain-matching method to determine the position of laser altimeter profiles within a precisely known surface, represented by a digital elevation model (DEM). We took this classical approach a step further, approximated the DEM by planar surfaces, and calculated the optimal position of the laser profile by minimizing the square sum of the elevation differences between reference DEMs and ICESat-2 profiles. We found the highly accurate DEMs of the McMurdo Dry Valleys (DV), Antarctica, ideal for this research because of their stable landscape and rugged topography. We computed the 3-D shift parameters of 379 different laser altimeter profiles along two reference ground tracks collected within the first two years of the mission. Analyzing these results revealed a total geolocation error (mean +1 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma $ </tex-math></inline-formula> ) of 4.93 m for version 3 and 4.66 m for version 4 data. These numbers are the averages of the six beams, expressed as mean +1 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma $ </tex-math></inline-formula> and lie well within the mission requirement of 6.5 m.

Horizontal accuracy assessment of a novel algorithm for approximate a surface to a DEM

Abstract. This study evaluates the horizontal positional accuracy of a new algorithm that defines a surface that approximates DEM data by means of a spline function. This algorithm allows evaluating the surface at any point in its definition domain and allows analytically estimating other parameters of interest, such as slopes, orientations, etc. To evaluate the accuracy achieved with the algorithm, we use a reference DEM 2 m × 2 m (DEMref) from which the derived DEMs are obtained at 4 m × 4 m, 8 m × 8 m and 16 m × 16 m (DEMder). For each DEMder its spline approximant is calculated, which is evaluated at the same points occupied by the DEMref cells, getting a resampled DEM 2 × 2 m (DEMrem). The horizontal accuracy is obtained by computing the area amongs the homologous contour lines derived from DEMref and DEMrem, respectively. It has been observed that the planimetric errors of the proposed algorithm are very small, even in flat areas, where you could expect major differences. Therefore, this algorithm could be used when an evaluation of the horizontal positional accuracy of a DEM product at lower resolution (DEMpro) and a different producing source than the higher resolution DEMref is wanted.