Interferometric Digital Elevation Model Research Articles

Terrain analysis in forested areas: consequences of using DSM instead of DTM

Abstract. Relief mapping through dense tropical forest is a challenge, which can be met by processing radar images. Various global digital elevation models (DEMs) are available, either free or paid, the most widely used methods for producing them at global scale being photogrammetry and short wavelength radar interferometry. However, the resulting DEMs do not directly represent the ground surface but rather the canopy or something in between. Since most users need terrain models for a variety of applications in geoscience, water management etc. but use such canopy models for lack of anything better, it was relevant to assess the consequences of this inappropriate but unavoidable choice. This paper presents a study carried out in the Brazilian Amazon, where an airborne P-band radar interferometric DEM was used as a reference based on its accuracy assessed in previous studies. A well-established DEM (SRTM) and newer ones (Copernicus and Fabdem), as well as a DEM obtained from aerial X-bands radar data, were compared to the reference according to different criteria related to elevation (accuracy and a typical application, i.e., dam filling simulation) and to slope at different scales (accuracy and a typical application, i.e., terrain classification). The results highlighted the risks of using short wavelengths to represent the terrain and emphasized the importance of slope in different resolution scales.

Registration of Interferometric DEM by Deep Artificial Neural Networks Using GPS Control Points’ Coordinates as Network Target

The Shuttle Radar Topography Mission (SRTM) satellite’s digital elevation model (DEM) is an important tool for studying topographic features on a medium-spacing scale. Data were collected and processed using the satellite’s orbital and navigation parameters with selected global GPS stations for verification. Distortion may be expressed by surveying measurements, such as position, distance, area, and shape. This study focuses on this distortion and proposes a new registration method to reduce its effect. Because of generality, the purpose shapes were excluded from this study. The proposed registration method depends on precise GPS control points that act as the ground truth for describing the considered surveying measurements. The processing was carried out using deep artificial neural networks (DANN) to produce a new registered DEM. A comparison was made between the original DEM and the new one, focusing on the selected surveying measurements. Another comparison was made between the GPS coordinates and SRTM polynomials to determine the potential of the proposed system. Some statistical investigations were applied to determine the level of significance of the distortion in each surveying measurement. The study shows that the distortion is highly significant; therefore, the proposed registration method is recommended to fix the distortion.

Sensitivity of Enhanced SRTM for Sea-Level Rise Variation on Egyptian Coasts

The accuracy of digital elevation models (DEMs) is very critical to planning adaptation strategies for coastal areas under changing scenarios of global climate and sea-level rise. This research assesses the accuracy of the interferometric DEM from the SRTM mission as it is one of the free available DEMs that have been widely used in many applications. The SRTM model is enhanced using the best fit global geoid model for Egypt instead of EGM96 and by applying a mathematical scale factor formula. This research aims to obtain a higher vertical accuracy of the SRTM model that achieves the requirements for coastal inundation studies with minimum field measurement data. The methodology approach consists of three phases. In the first phase, the enhancement scale factor formulas were derived using uniformly distributed ground control points (GCPs) at two different terrains data in Egypt. The second phase contains the evaluation and validation process. It was observed that the enhanced accuracy achieved ranged from 45% to 60 % based on the type of terrains. In the last phase, the sensitivity of these DEMs to sea-level projections using the recent available local tide gauge data was analyzed. It is recommended to investigate this method approach to determine the optimal size and distribution of reference ground control points needed to adjust various free open DEMs of low vertical accuracy for further studies and other applications.

Interferometric DEM-Assisted High Precision Imaging Method for ArcSAR.

Ground-based arc-scanning synthetic aperture radar (ArcSAR) is the novel ground-based synthetic aperture radar (GBSAR). It scans 360-degree surrounding scenes by the antenna attached to rotating boom. Therefore, compared with linear scanning GBSAR, ArcSAR has larger field of view. Although the feasibility of ArcSAR has been verified in recent years, its imaging algorithm still presents difficulties. The imaging accuracy of ArcSAR is affected by terrain fluctuation. For rotating scanning ArcSAR, even if targets in scenes have the same range and Doppler with antenna, if the heights of targets are different, their range migration will be different. Traditional ArcSAR imaging algorithms achieve imaging on reference plane. The height difference between reference plane and target in scenes will cause the decrease of imaging quality or even image defocusing because the range migration cannot be compensated correctly. For obtaining high-precision ArcSAR image, we propose interferometric DEM (digital elevation model)-assisted high precision imaging method for ArcSAR. The interferometric ArcSAR is utilized to acquire DEM. With the assist of DEM, target in scenes can be imaged on its actual height. In this paper, we analyze the error caused by ArcSAR imaging on reference plane. The method of extracting DEM on ground range for assisted ArcSAR imaging is also given. Besides, DEM accuracy and deformation monitoring accuracy of proposed method are analyzed. The effectiveness of the proposed method was verified by experiments.

VERTICAL ACCURACY ASSESSMENT OF THE PROCESSED SRTM DATA FOR THE BRAZILIAN TERRITORY

Abstract: This research aims to determine the vertical accuracy of the Interferometric Digital Elevation Model (DEM) obtained from the processed Shuttle Radar Topographic Mission (SRTM) data. The research compared the SRTM-GL1 (Shuttle Radar Topographic Mission-Global 1) with 30-meter resolution and the following 90-meter resolution models: (a) EMBRAPA; (b) Hydrological data and maps based on Shuttle Elevation Derivatives at multiple Scales (HydroSHEDS) (HydroSHEDS), provided by the United States Geological Survey (USGS); (c) Consultative Group for International Agricultural Research-Consortium for Spatial Information (CGIAR-CSI); and (d) Jonathan de Ferranti. The accuracy analysis considered the diverse Brazilian regions, adopting 1,087 field points from the Global Navigation Satellite System (GNSS) trackers or topography methods. The Jonathan de Ferranti model achieved the best accuracy with RMSE of 9.61m among the 90-meter resolution models. Most SRTM models at 1:100,000 scale reached Grade A of the Cartographic Accuracy Standard. However, the accuracy at the 1: 50,000 scale did not achieve the same performance. SRTM errors are linearly related to slope and the most significant errors always occur in forest areas. The 30-meter resolution SRTM showed an accuracy of around 10% better (RMSE of 8.52m) than the model of Jonathan de Ferranti with 90-meter resolution (RMSE of 9.61m).

Wetland classification using Radarsat-2 SAR quad-polarization and Landsat-8 OLI spectral response data: a case study in the Hudson Bay Lowlands Ecoregion

ABSTRACTCircumboreal Canadian bogs and fens distinguished by differences in soils, hydrology, vegetation and morphological features were classified using combinations of Radarsat-2 synthetic aperture radar (SAR) quad-polarization data and Landsat-8 Operational Land Imager (OLI) spectral response patterns. Separate classifications were conducted using a traditional pixel-based maximum likelihood classifer and a machine learning algorithm following an object-based image analysis (OBIA). This study focused on two wetland classes with extensive coverage in the area (bog and fen). In the pixel-based maximum likelihood classification, accuracy increased from approximately 69% user’s accuracy and 79% producer’s accuracy using Radarsat-2 SAR data alone to approximately 80% user’s accuracy and 87% producer’s accuracy using Landsat-8 OLI data alone. Use of the Radarsat-2 SAR and Landsat-8 OLI data following principal components analysis (PCA) data fusion did not result in higher pixel-based maximum likelihood classification accuracy. In the object-based machine learning classification, higher bog and fen class accuracies were obtained when using Radarsat-2 and Landsat OLI data individually compared to the equivalent pixel-based classification. Subsequently, a PCA-data fusion product outperformed the individual bands of the Radarsat-2 and Landsat-8 imagery in object-based classification. Greater than 90% producer’s accuracy was obtained. The margin of error (MOE) was less than 5% in all classifications reported here. Further research will examine alternative data fusion techniques and the addition of Radarsat-2 SAR interferometric digital elevation model (DEM)-based geomorphometrics in object-based classification of different morphological types of bogs and fens.

Evaluation of TanDEM-X elevation data for geomorphological mapping and interpretation in high mountain environments — A case study from SE Tibet, China

Digital elevation models (DEMs) are a prerequisite for many different applications in the field of geomorphology. In this context, the two near-global medium resolution DEMs originating from the SRTM and ASTER missions are widely used. For detailed geomorphological studies, particularly in high mountain environments, these datasets are, however, known to have substantial disadvantages beyond their posting, i.e., data gaps and miscellaneous artifacts. The upcoming TanDEM-X DEM is a promising candidate to improve this situation by application of state-of-the-art radar technology, exhibiting a posting of 12m and less proneness to errors. In this study, we present a DEM processed from a single TanDEM-X CoSSC scene, covering a study area in the extreme relief of the eastern Nyainqêntanglha Range, southeastern Tibet. The potential of the resulting experimental TanDEM-X DEM for geomorphological applications was evaluated by geomorphometric analyses and an assessment of landform cognoscibility and artifacts in comparison to the ASTER GDEM and the recently released SRTM 1″ DEM. Detailed geomorphological mapping was conducted for four selected core study areas in a manual approach, based exclusively on the TanDEM-X DEM and its basic derivates. The results show that the self-processed TanDEM-X DEM yields a detailed and widely consistent landscape representation. It thus fosters geomorphological analysis by visual and quantitative means, allowing delineation of landforms down to footprints of ~30m. Even in this premature state, the TanDEM-X elevation data are widely superior to the ASTER and SRTM datasets, primarily owing to its significantly higher resolution and its lower susceptibility to artifacts that hamper landform interpretation. Conversely, challenges toward interferometric DEM generation were identified, including (i) triangulation facets and missing topographic information resulting from radar layover on steep slopes facing toward the radar sensor, (ii) low coherence values on leeward slopes, (iii) decorrelation effects over water bodies, and (iv) challenges for phase unwrapping in settings of strong topographic contrasts. There is, however, a high probability that these drawbacks can be overcome by applying multiple interferograms exhibiting different perpendicular baselines as planned for the generation of the final TanDEM-X DEM product.

Phase Offset Calculation for Airborne InSAR DEM Generation Without Corner Reflectors

Digital elevation model (DEM) generation through interferometric processing of synthetic aperture radar (SAR) data requires the calculation of a constant phase offset present in the unwrapped interferograms. This operation is usually carried out by exploiting the external information provided by GPS measurements in correspondence of corner reflectors (CRs) properly deployed over the illuminated area. This is, however, expensive in terms of cost and time. Moreover, deployment of CRs along with the corresponding in situ GPS measurements can be difficult (if not impossible) in unfriendly areas or in natural disaster scenarios. To circumvent these limitations, we address in this work the estimation of the required phase offset by exploiting a low-accuracy external DEM, without using CRs. More specifically, a two-step approach is proposed. The first step exploits the synthetic phase computed by means of the external DEM and represents a straightforward extension of the procedure that is usually applied in the presence of CRs. Subsequently, in order to refine the achieved solution, a second step is introduced. It is based on a least squares approach that properly exploits the difference between the available low-accuracy DEM and the interferometric DEM generated by means of the phase offset value roughly estimated through the first step. The presented approach is very easy to implement and allows us to achieve an accurate and fast estimate of the needed phase offset, even in the presence of an external DEM affected by a vertical bias and/or a planar shift. The algorithm performances improve in the presence of a large variation of the look angle, as it generally happens in airborne systems. On the other side, the effectiveness of the algorithm may be impaired by the possible presence of artifacts in the unwrapped interferograms, such as those due to the residual motion errors typical of repeat-pass airborne SAR scenarios. Accordingly, the proposed solution is particularly suitable for single-pass interferometric airborne SAR systems, as demonstrated through the presented experimental results achieved on real data.

Seasonal dynamic thinning at Helheim Glacier

We investigate three annual mass-balance cycles on Helheim Glacier in south-east Greenland using TanDEM-X interferometric digital elevation models (DEMs), bedrock GPS measurements, and ice velocity from feature-tracking. The DEMs exhibit seasonal surface elevation cycles at elevations up to 800 m.a.s.l. with amplitudes of up to 19 m, from a maximum in July to a minimum in October or November, concentrated on the fast-flowing areas of the glacier indicating that the elevation changes have a mostly dynamic origin. By modelling the detrended bedrock loading/unloading signal we estimate a mean density for the loss of 671±70 kgm−3 and calculate that total water equivalent volume loss from the active part of the glacier (surface flow speeds >1 m day−1) ranges from 0.5 km3 in 2011 to 1.6 km3 in 2013. A rough ice-flux divergence analysis shows that at lower elevations (<200 m) mass loss by dynamic thinning fully explains seasonal elevation changes. In addition, surface elevations decrease by a greater amount than field observations of surface ablation or surface-energy-balance modelling predict, emphasising the dynamic nature of the mass loss. We conclude, on the basis of ice-front position observations through the time series, that melt-induced acceleration is most likely the main driver of the seasonal dynamic thinning, as opposed to changes triggered by retreat.

Sentinel-1 for Monitoring Reservoirs: A Performance Analysis

In this paper we explore the performances and the opportunities provided by the European satellite Sentinel-1 for water resource management applications in low-income countries. The analysis is supported by a synthetic aperture radar (SAR) simulator, which allowed the quantification of the expected characteristics of Sentinel-1 products in three applications: interferometric digital elevation models (DEMs) generation, land cover mapping and estimation of water volumes retained by small reservoirs. The obtained results quantitatively show that Sentinel-1 data characteristics are fully suitable for most of the application already explored in the recent SAR literature.

On the use of COSMO/SkyMed data and Weather Models for interferometric DEM generation

This work experiments the potentialities of COSMO/SkyMed (CSK) data in providing interferometric Digital Elevation Model (DEM). We processed a stack of CSK data for measuring with meter accuracy the ground elevation on the available coherent targets, and used these values to check the accuracy of DEMs derived from 5 tandem-like CSK pairs. In order to suppress the atmospheric signal we experimented a classical spatial filtering of the differential phase as well as the use of numerical weather prediction (NWP) model RAMS. Tandem-like pairs with normal baselines higher than 300 m allows to derive DEMs fulfilling the HRTI Level 3 specifications on the relative vertical accuracy, while the use of NWP models still seems unfeasible especially for X-band.

Operational TanDEM-X DEM calibration and first validation results

In June 2010, the German TanDEM-X satellite was launched. Together with its twin satellite TerraSAR-X it flies in a close formation enabling single-pass SAR interferometry. The primary goal of the TanDEM-X mission is the derivation of a global digital elevation model (DEM) with unprecedented global accuracies of 10m in absolute and 2m in relative height. A significant calibration effort is required to achieve this high quality world-wide. In spite of an intensive instrument calibration and a highly accurate orbit and baseline determination, some systematic height errors like offsets and tilts in the order of some meters remain in the interferometric DEMs and have to be determined and removed during the TanDEM-X DEM calibration. The objective of this article is the presentation of an approach for the estimation of correction parameters for remaining systematic height errors applicable to interferometric height models. The approach is based on a least-squares block adjustment using the elevation of ICESat GLA14 data as ground control points and connecting points of adjacent, overlapping DEMs as tie-points. In the first part its implementation in DLR’s ground segment is outlined. In the second part the approach is applied and validated for two of the first TanDEM-X DEM test sites. Therefore, independent reference data, in particular high resolution reference DEMs and GPS tracks, are used. The results show that the absolute height errors of the TanDEM-X DEM are small in these cases, mostly in the order of 1–2m. An additional benefit of the proposed block adjustment method is that it improves the relative accuracy of adjacent DEMs.

Eucalyptus Biomass and Volume Estimation Using Interferometric and Polarimetric SAR Data

This work aims to establish a relationship between volume and biomass with interferometric and radiometric SAR (Synthetic Aperture Radar) response from planted Eucalyptus saligna forest stands, using multi-variable regression techniques. X and P band SAR images from the airborne OrbiSAR-1 sensor, were acquired at the study area in the southeast region of Brazil. The interferometric height (Hint = difference between interferometric digital elevation model in X and P bands), contributed to the models developed due to fact that Eucalyptus forest is composed of individuals whose structure is predominantly cylindrical and vertically oriented, and whose tree heights have great correlation with volume and biomass. The volume model showed that the stand volume was highly correlated with the interferometric height logarithm (Log10Hint), since Eucalyptus tree volume has a linear relationship with the vegetation height. The biomass model showed that the combination of both Hint2 and Canopy Scattering Index—CSI (relation of s°VV by the sum of s°VV and s°HH, which represents to the canopy interaction) were used in this model, due to the fact that the Eucalyptus biomass and the trees height relationship is not linear. Both models showed a prediction error of around 10% to estimate the Eucalyptus biomass and volume, which represents a great potential to use this kind of technology to help establish Eucalyptus forest inventory for large areas.

Remote sensing of floodplain geomorphology as a surrogate for biodiversity in a tropical river system (Madre de Dios, Peru)

The complex floodplains of large rivers offer a striking example of how geomorphology, by dictating patterns in the frequency and duration of soil saturation and surface flooding, influences ecosystem structure and function. This study draws on multiple sources of data from remote sensing, together with ground observations and water sampling, to distinguish floodplain ecosystems in the Madre de Dios River, a tributary of the Amazon River in Perú. This remote tropical river meanders across sub-Andean alluvial deposits in a tectonically active region and creates floodplain surfaces of varying ages, including terraces that are above the reach of present-day river floods. Data from Landsat ETM+ (optical multispectral), JERS-1 (L-band radar), and the Shuttle Radar Topography Mission (C-band interferometric Digital Elevation Models) were integrated in an object-oriented image analysis approach to distinguish five classes of floodplain vegetation. Vegetation classes generally correspond with successional age and reflect the activity of the riverine meander belt. Stage data for the river show erratic fluctuations and an annual range exceeding 8 m, but the maximum depth of floodplain inundation varied from > 1 m close to the river to approximately 0.1 m on more elevated terraces. The major ion composition of standing waters on the floodplain during the dry season indicated the importance of emergence of local groundwater in maintaining saturated soils, particularly further from the river, where backswamp vegetation is distinct and includes palm swamps. Thus, a hydrological continuum exists from deep but sporadic river inundation near the river to constant soil saturation by groundwater emergence in distal backswamps, reflecting the geomorphological origin and age of the floodplain deposits. This hydrogeomorphic continuum results in fundamental ecological differences. The exceptionally rich biodiversity of the sub-Andean region may be ascribed in part to the enhanced biodiversity associated with fluvial geomorphological features, and, thus, conservation planning must account for the diverse landforms created by fluvial dynamics.

Spot Revisited: Accuracy Assessment, Dem Generation and Validation from Stereo Spot 5 Hrg Images

AbstractSPOT 5 HRG Level 1A and 1B stereo scenes covering Zonguldak testfield in north‐west Turkey have been analysed. They comprise the left and right image components with base to height ratio of 0·54. The pixel size on the ground is 5 m. The bundle orientation was executed by the PCI Geomatica V9.1.4 software package and resulted in 3D geopositioning to sub‐pixel accuracies in each axis provided that at least six control points were used in the computation. Root mean square error (rmse) values and vectors of residual errors for Levels 1A and 1B are similar, even for different control and check point configurations. Based on the scene orientation, Level 1A and 1B digital elevation models (DEMs) of the testfield have been determined by automatic matching and validated by the reference DEM digitised from the 1:25 000 scale topographic maps, interferometric DEMs from Shuttle Radar Topography Mission (SRTM) X‐ and C‐band SAR data and the GPS profiles measured along the main roads in the testfield. Although the accuracies of reference data‐sets are too similar to the generated SPOT DEMs, these are the only high quality reference materials available in this area. Sub‐pixel height accuracy was indicated by the comparison with profile points. However, they are in favourable locations where matching is always successful, so such a result may give a biased measure of the accuracy of the corresponding DEMs.

Accuracy assessment of interferometric digital elevation models derived from the Shuttle Radar Topography Mission X- and C-band data in a test area with rolling topography and moderate forest cover

In February 2000, the Shuttle Radar Topography Mission (SRTM) mapped large areas of the global landmass using two radar systems operating simultaneously in X and C band. The radar mapping instrument consisted of modified versions of the SIR-C C-band and X-band radars flown on the shuttle in 1994. Modifications included a 60-m retractable boom, with C-band and X-band receive-only antennas attached to the boom's end. High-accuracy metrology systems were added to measure position and attitude of the shuttle and the positions of the boom antennas. The dual apertures at each band form radar interferometers suitable for making high-accuracy topographic maps of the Earth. The C-band data set is being processed by JPL for the archives of the National Imagery and Mapping Agency and the National Aeronautics and Space Administration. The X-band data set is processed and distributed at DLR, Germany. This paper deals with the accuracy assessments of the interferometric DEMs derived from the X- and C-band synthetic aperture radar systems over a testfield with rolling topography and moderate forest cover using the reference DEM digitized from the topographic maps of 1:25,000 scale. Obtained results for the two interferometric DEMs are similar and lie in the range of 10–11 m. The accuracy of SRTM X- and C-band DEMs was also checked against ground control points measured by differential GPS, and the rms height errors were found to be about 9 m, which confirms the results based on the reference DEM.

Radar stereo- and interferometry-derived digital elevation models: comparison and combination using Radarsat and ERS-2 imagery

In this experiment, we derive and compare radar stereo and interferometric digital elevation models (DEMs) of a study site in Djibouti, East Africa. A Radarsat stereo pair, as well as Radarsat and ERS-2 interferometric data, comprise the test images. The primary objective of the study was to analyse and compare the results obtained by the two techniques and explore possible synergisms between them. We find that in regions of high coherence, the DEMs produced by interferometry are of much better quality than the stereo result. However, the corresponding error histograms also show some pronounced errors due to decorrelation and phase-unwrapping problems on forested mountain slopes. On the other hand, the more robust stereo reconstruction, with an error standard deviation of 45 m, is able to capture the general terrain shape, although finer surface details are lost. In the second part of our experiment, we demonstrate that merging the stereoscopic and interferometric DEMs by applying a user-defined weighting function to a filtered coherence map can significantly improve the accuracy of the computed elevation maps.

Application of high-resolution, interferometric DEMs to geomorphic studies of fault scarps, Fish Lake Valley, Nevada–California, USA

Recent developments in interferometric radar remote sensing provide a method for deriving detailed topographic and slope information for fault-scarp detection. In October 1996, the airborne TOPSAR instrument [IEEE Trans. Geosci. Remote Sens., 30 (1992) 933] was flown over southwest Nevada and east-central California. Topography calculated from TOPSAR data are in the form of a high-resolution (5-m spatial grid) digital elevation model (DEM). In this study, we focus upon the large, steep fault scarps that cut alluvium and alluvial fans in Fish Lake Valley, east of the White Mountains of Nevada–California. A series of topographic profiles extracted from the DEM reveal that the larger fault scarps are greater than 40 m in height and that the average midsection slope angle for all measured scarps is approximately 23°. These large scarps are the product of multiple offsets rather than a single event. Other relevant geomorphic features present in the digital topography include splays and benches along the main fault, levees, cutbanks, gullies incising fault scarp slopes, shutterridges, offset drainage, and small normal faults with scarp heights of only 4–6 m. Field work corroborated general geomorphologic landforms, confirmed fault-scarp morphometry, and aided the evaluation of the accuracy of the DEM. We are also able to assess fault segmentation models that divide the Fish Lake Valley fault zone (FLVFZ) into discrete segments based upon surface-rupture characteristics.