ALOS World 3D Research Articles

Comparison of machine learning and statistical approaches for Digital Elevation Model (DEM) correction: interim results

Abstract. The correction of digital elevation models (DEMs) can be achieved using a variety of techniques. Machine learning and statistical methods are broadly applicable to a variety of DEM correction case studies in different landscapes. However, a literature survey did not reveal any research that compared the effectiveness or performance of both methods. In this study, we comparatively evaluate three gradient boosted decision trees (XGBoost, LightGBM and CatBoost) and multiple linear regression for the correction of two publicly available global DEMs: Copernicus GLO-30 and ALOS World 3D (AW3D) in Cape Town, South Africa. The training datasets are comprised of eleven predictor variables including elevation, slope, aspect, surface roughness, topographic position index, terrain ruggedness index, terrain surface texture, vector ruggedness measure, percentage bare ground, urban footprints and percentage forest cover as an indicator of the overland forest distribution. The target variable (elevation error) was derived with respect to highly accurate airborne LiDAR. The results presented in this study represent urban/industrial and grassland/shrubland/dense bush landscapes. Although the accuracy of the original DEMs had been degraded by several anomalies, the corrections improved the vertical accuracy across vast areas of the landscape. In the urban/industrial and grassland/shrubland landscapes, the reduction in the root mean square error (RMSE) of the original AW3D DEM was greater than 70%, after correction. The corrections improved the accuracy of Copernicus DEM, e.g., > 44% RMSE reduction in the urban area and >32% RMSE reduction in the grassland/shrubland landscape. Generally, the gradient boosted decision trees outperformed multiple linear regression in most of the tests.

DIGITAL ELEVATION MODEL CORRECTION IN URBAN AREAS USING EXTREME GRADIENT BOOSTING, LAND COVER AND TERRAIN PARAMETERS

Abstract. The accuracy of digital elevation models (DEMs) in urban areas is influenced by numerous factors including land cover and terrain irregularities. Moreover, building artefacts in global DEMs cause artificial blocking of surface flow pathways. This compromises their quality and adequacy for hydrological and environmental modelling in urban landscapes where precise and accurate terrain information is needed. In this study, the extreme gradient boosting (XGBoost) ensemble algorithm is adopted for enhancing the accuracy of two medium-resolution 30-metre DEMs over Cape Town, South Africa: Copernicus GLO-30 and ALOS World 3D (AW3D). XGBoost is a scalable, portable and versatile gradient boosting library that can solve many environmental modelling problems. The training datasets are comprised of eleven predictor variables including elevation, urban footprints, slope, aspect, surface roughness, topographic position index, terrain ruggedness index, terrain surface texture, vector roughness measure, forest cover and bare ground cover. The target variable (elevation error) was calculated with respect to highly accurate airborne LiDAR. After training and testing, the model was applied for correcting the DEMs at two implementation sites. The corrections achieved significant accuracy gains which are competitive with other proposed methods. There was a 46–53% reduction in the root mean square error (RMSE) of Copernicus DEM, and a 72–73% reduction in the RMSE of AW3D DEM. These results showcase the potential of gradient-boosted decision trees for enhancing the quality of global DEMs, especially in urban areas.

Assessment of the global Copernicus, NASADEM, ASTER and AW3D digital elevation models in Central and Southern Africa

ABSTRACT Validation studies of global Digital Elevation Models (DEMs) in the existing literature are limited by the diversity and spread of landscapes, terrain types considered and sparseness of groundtruth. Moreover, there are knowledge gaps on the accuracy variations in rugged and complex landscapes, and previous studies have often not relied on robust internal and external validation measures. Thus, there is still only partial understanding and limited perspective of the reliability and adequacy of global DEMs for several applications. In this study, we utilize a dense spread of LiDAR groundtruth to assess the vertical accuracies of four medium-resolution, readily available, free-access and global coverage 1 arc-second (30 m) DEMs: NASADEM, ASTER GDEM, Copernicus GLO-30, and ALOS World 3D (AW3D). The assessment is carried out at landscapes spread across Cape Town, Southern Africa (urban/industrial, agricultural, mountain, peninsula and grassland/shrubland) and forested national parks in Gabon, Central Africa (low-relief tropical rainforest and high-relief tropical rainforest). The statistical analysis is based on robust accuracy metrics that cater for normal and non-normal elevation error distribution, and error ranking. In Cape Town, Copernicus DEM generally had the least vertical error with an overall Mean Error (ME) of 0.82 m and Root Mean Square Error (RMSE) of 2.34 m while ASTER DEM had the poorest performance. However, ASTER GDEM and NASADEM performed better in the low-relief and high-relief tropical forests of Gabon. Generally, the DEM errors have a moderate to high positive correlation in forests, and a low to moderate positive correlation in mountains and urban areas. Copernicus DEM showed superior vertical accuracy in forests with less than 40% tree cover, while ASTER and NASADEM performed better in denser forests with tree cover greater than 70%. This study is a robust regional assessment of these global DEMs.

Identification of river basins within northwestern slope of Crimean Mountains using various digital elevation models (ASTER GDEM, ALOS World 3D, Copernicus DEM, and SRTM DEM)

Since the end of the 20th century, the use of geographic information systems and digital elevation models has reduced the time required for and improved the quality of morphometric analysis of the relief within river basins. However, researchers are constantly faced with the problem of choosing the most accurate and suitable digital terrain model for their task. Many global, regional, and local digital elevation models are available. In this study, we comparatively analyzed the accuracy of the ASTER GDEM, ALOS World 3D, Copernicus DEM, and SRTM DEM spatial datasets for the purpose of catchment basin modeling for the river basins of the northwestern slope of the Crimean Mountains (Zapadnyy Bulganak, Alma, Kacha, Belbek, and Chernaya Rivers) as an example. For each river basin, we calculated the systematic, root mean square, mean absolute, standard root mean square (Bessel’s correction), and centered mean absolute errors by comparing ASTER GDEM, ALOS World 3D, Copernicus DEM, and SRTM DEM data with a 1:100,000 topographic map within the considered river basins. We found the smallest error values for the Copernicus DEM and ALOS World 3D datasets; furthermore, we used the Copernicus DEM dataset to model the river basins and sub-basins of the northwestern slope of the Crimean Mountains. As a result, we identified these river basins and sub-basins for the Zapadnyy Bulganak, Alma, Kacha, Belbek, and Chernaya Rivers, which are represented by stream basins, valleys, gullies, and ravine systems.

Сравнение цифровых моделей рельефа

Introduction. GIS technologies make it possible to analyze large amounts of spatial data, which include digital elevation models derived from remote sensing data. They are an important source of data for calculating and mapping various phenomena and processes that are closely interrelated with the relief, and cover vast areas. The article presents the results of the accuracy assessment of the three most popular global digital elevation models: ALOS World 3D, SRTM, and ASTER. Materials and research methods. The evaluation of digital elevation models was carried out on the territory of Budennovsky urban district of Stavropol Krai. Error analysis of morphometric indicators was performed based on the comparison of the studied digital elevation models and the data of the State Research and Development Center of Geoformation Systems and Technologies – GosGisCenter, which were presented in the form of topographic maps. The analysis of the results of the study was carried out based on mathematical and statistical methods. The total sample of compared points equals 5322. Research results and their discussion. Based on the obtained dataset of each of the digital terrain models, a comparative analysis of the samples was carried out. As a result, it was determined that the ASTER model showed the lowest accuracy. SRTM project data showed insignificant deviations. The digital terrain model based on ALOS W3D data has the highest accuracy. Conclusions. Despite its popularity and at first glance similarity of the data, a number of features of each of the digital terrain models were identified. The data obtained will simplify the selection of a digital terrain model, taking into account the requirements needed to perform various tasks, as well as improve the accuracy of the results obtained.

Vertical Accuracy of Freely Available Global Digital Elevation Models: A Case Study in Karaman Water Reservoir Territory

Nowadays, Uzbekistan pays great attention to the construction of reservoirs for irrigation and energy purposes. Identification of potential sites for the construction of reservoirs and obtaining initial data (the geographical location, storage volume and water surface area, profile of the dam site and others) imposes a great task on project institutes that develop design and survey and pilot work on water engineering. The use of GIS and RS technologies in human life has made it possible to accomplish many tasks quickly, cheaply and accurately. In this research, the main scope of the work is to assess the accuracy of the tested ALOS World 3D - 30m (AW3D30), ASTER GDEM v3, SRTM Plus, COP-30 and NASADEM products for the Karaman water reservoir (recommended for construction in Jizzakh region, Uzbekistan) territory by comparison with 36 Ground elevation points taken from topographic maps (1:25000). Results of statistics values calculated over the geodetic ground elevation points and the DEM data show that NASADEM and AWED30 DEM data are more accurate than other DEMs. The study found that the use of AWED30 and NASADEM data in the design of the proposed Karaman water reservoir for construction leads to a more accurate result. The results obtained using AWED30 data in determining the storage volume (W=780 mln.m3) and area (F=41.4 sq.km) of the water reservoir.

Demarcation of Coastal Dune Morphology and Dune Patterns using Geospatial Models: A Case Study from Manapad Coastal Stretch, Tamil Nadu, South India

Abstract Coastal sand dunes are the dynamic depositional landform which are formed near the coast, due to aeolian activity. Coastal sand dune acts as a natural barrier against coastal erosion hence its periodic monitoring is essential. Modification of this landform due to anthropogenic activities was observed in the coastal stretch towards the south of Tamil Nadu, even though these dune ecosystems were meant to be conserved and preserved in the coastal zone regulation notification. Present study, focuses on finding key techniques required to demarcate the morphological parameters such as ridge line, crest portion, toe, dune orientation, and its pattern from the open source ALOS World 3D (AW3D) DEM for periodic monitoring of coastal dune ecosystems. Topographic models such as hill shading, slope, aspect, curvature, and hybrid techniques were performed. The outcomes obtained from topographic models were validated with spatial profiling and field survey. From the study it is observed that, hybrid techniques particularly slope overlaid on hill shade, slope, gaussian stretched hill shade image, and spatial profiling are the key techniques to bring out the morphological variations and the parabolic dune patterns, which were hitherto not reported in earlier literatures. Gaussian stretched hill shade image enhanced the micro landforms which were difficult to extract from normal hill shading. The slope image of the study is found to be more informative in exhibiting the minor dunes and patterns compared to shaded relief image. The ridge portion of the dune, crest and limb portion and coastal plains were differentiated based on the slope value ranges. The hybrid image formed by overlaying slope and curvature data on hill-shaded image is more informative in providing most of the parabolic patterns formed by micro and meso scale dunes. Spatial profile could be used as an additional tool to validate the information’s derived from topographic models, wherever there is limitation in field accessibility.

Large-scale geomorphological mapping of the Malaya Sosva
 state nature reserve

The Malaya Sosva State Nature Reserve is situated in the west of the Khanty-Mansiysk Au-tonomous Region — Ugra. Lake-alluvial, lake-glacial and moraine plains are the prevalent relief’s types on that territory. The main specificity of the reserve’s relief in the central and southern parts is a chain of hilly watersheds — the Malososvinsky Amphitheater. The central, western, and southern parts of the reserve are distinguished by the greatest depth of dissection, while in the northern and south-western regions, a finely divided relief prevails. To study natural conditions and resources of the reserve, a complex mapping was carried out. Based on the results of field researches organized in the summer of 2017, as well as on the data obtained during the processing of topographic maps of scale 1 : 100 000, a Sentinel-2A satellite image, digital terrain models ASTER GDEM, ALOS World 3D and ArcticDEM, the following large-scale maps were constructed for the area under study: hypsometric, the range of dissection and horizontal dissection of the relief, steepness of slopes, as well as a map of «red relief» (Red Relief Image Map). According to those local maps and taking into consideration all the previously issued maps of a smaller scale, a general geomorphological map of the territory of a scale of 1 : 100 000 has been created.

Vertical accuracy assessment of open source digital elevation models under varying elevation and land cover in Western Ghats of India

The selection of suitable DEM from available open-source DEMs like SRTM, ALOS World 3D, CARTOSAT-1, ASTER-GDEM, TanDEM-X which are acquired through different techniques is difficult without prior guidelines, especially on the rugged mountainous terrain. Therefore, this article aimed to evaluate the role of land cover and altitude on the vertical accuracy of open-source DEMs with near to ground measurements taken by Ice Cloud and Land Elevation (ICESat) Geoscience Laser Altimetry System (GLAS) in and around Western Ghats (WG) of India. The SRTM (30 m) DEM outperformed other DEMs at the scale of WG and in the dense vegetation cover with least performance by ASTER DEM (30 m). The vertical accuracy of DEM is varying with different elevation ranges and land cover conditions and is found to be better than the vertical accuracy specified by the mission. The overestimation of elevation in low terrain relief area, and underestimation on higher elevation with steep terrain is substantive in all the DEMs. The role of land cover and altitude is significant on the elevation and slope more than the aspect and roughness. Good performance by 90-m resolution DEM over 30-m resolution DEMs proves the potential of InSAR in elevation measurement in vegetated areas with low cost and high accuracy. These results help in the selection of pertinent DEM for any geo-climatical applications and in development of merged DEM based on the terrain relief and land cover of the region.

Evaluation of ASTER GDEM2, SRTMv3.0, ALOS AW3D30 and TanDEM-X DEMs for the Peruvian Andes against highly accurate GNSS ground control points and geomorphological-hydrological metrics

We present an analysis for Peru of the vertical accuracy and derived geomorphological parameters of three, freely available Digital Elevation Models (DEMs) with 30-m grid sizes and one commercially available 12-m DEM: ASTER GDEM2, SRTMv3.0 (hereafter called SRTM3), ALOS World 3D (AW3D30) and 12-m TanDEM-X. Their elevation values were compared against values measured with a dual-frequency Trimble 5800 Global Navigation Satellite Systems (GNSS) receiver with two antennas in static relative positioning. A total of 139 ground control points (GCPs) with elevations of up to 4334 m above sea level (asl). were obtained from four topographically contrasting regions along the flat, arid coast, the semi-dry Andes and the Amazon rainforest. The combined results of the four areas showed that the residuals of ASTER GDEM2 had a root mean square error (RMSE) of 6.907 m, SRTM3 5.113 m and AW3D30 6.246 m. For the two areas where TanDEM-X was investigated, a RMSE of 1.666 m was obtained. When considering each area individually, of the three 30-m DEMs, SRTM3 performed best in all areas, while ASTER GDEM2 was always performing worst. The standard deviation (SD) of the residuals of ASTER GDEM2 and AW3D30 varied much more between the four study areas than the SD of SRTM3 and TanDEM-X. It was possible to establish linear correlations with R2 > 0.95 between the GNSS-measured and DEM-derived elevation values for all areas and all DEMs, which can be used to correct ASTER GDEM2 and AW3D30 for Peru. No relationship was found between absolute elevation and residuals. Slope angle of >15°, however, correlated to much higher residuals for SRTM3 and AW3D30, whereas a constant increase in residual correlated to a constant increase in slope angle for TanDEM-X. In general, the highest residuals corresponded to the highest slope classes. A comparison of absolute elevation values and slope angles of selected areas between ASTER GDEM2 and SRTM3, as well as between AW3D30 and SRTM3, showed in all cases more deviation from true values in areas with steeper slopes. This effect seems independent of vegetation. The presence of buildings however, severely affected performance of ASTER GDEM2. For some areas, AW3D30 suffered from mismatch between adjacent scenes and horizontal and oblique stripping. An analysis of drainage networks showed that all three 30-m DEMs were capable of producing a similar number of Strahler orders, total number of channels, minimum and maximum channel length and accumulative channel length. All DEMs produced accurate networks in the upper reaches of the catchments, but suffered in flat areas such as wide fluvial valleys and sink-filled areas. ASTER GDEM2 in particular produced parallel river channels and unnatural short cuts. Our results agreed well with those of other studies elsewhere around the world and showed that i) the vertical error is much less than those officially reported for all DEMs; ii) slope is the most determinant factor in DEM accuracy. We conclude that SRTM3 delivers the most stable performance in almost all tests and is therefore the DEM of choice for landscape analysis in Peru. TanDEM-X 12 m performed very well in our elevation accuracy test and could become a worthy successor to SRTM3.

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

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

Best Practices for Elevation-Based Assessments of Sea-Level Rise and Coastal Flooding Exposure

Elevation data are critical for assessments of sea-level rise and coastal flooding exposure. Previous research has demonstrated that the quality of data used in elevation-based assessments must be well understood and applied to properly model potential impacts. The cumulative vertical uncertainty of the input elevation data substantially controls the minimum increments of sea-level rise and the minimum planning horizons that can be effectively used in assessments. For regional, continental, or global assessments, several digital elevation models (DEMs) are available for the required topographic information to project potential impacts of increased coastal water levels, whether a simple inundation model is used or a more complex process-based or probabilistic model is employed. When properly characterized, the vertical accuracy of the DEM can be used to report assessment results with the uncertainty stated in terms of a specific confidence level or likelihood category. An accuracy evaluation has been conducted of global DEMs to quantify their inherent vertical uncertainty to demonstrate how accuracy information should be considered when planning and implementing a sea-level rise or coastal flooding assessment. The evaluation approach includes comparison of the DEMs with high-accuracy geodetic control points as the independent reference data over a variety of coastal relief settings. The global DEMs evaluated include SRTM, ASTER GDEM, ALOS World 3D, TanDEM-X, NASADEM, and MERIT. High-resolution, high-accuracy DEM sources, such as airborne lidar and stereo imagery, are also included to give context to the results from the global DEMs. The accuracy characterization results show that current global DEMs are not adequate for high confidence mapping of exposure to fine increments (< 1 m) of sea-level rise or with shorter planning horizons (< 100 years), but they are suitable for general delineation of low elevation coastal zones. In addition to the best practice of rigorous accounting for vertical uncertainty, other recommended procedures are presented for delineation of different types of impact areas (marine and groundwater inundation) and use of regional relative sea-level rise scenarios. The requirement remains for a freely available, high-accuracy, high-resolution global elevation model that supports quantitative sea-level rise and coastal inundation assessments at high confidence levels.

ACCURACY EVALUATION OF VARIOUS SATELLITE IMAGERY PRODUCTS FOR LARGE SCALE TOPOGRAPHIC MAPPING

Abstract. DEM and ortho-imageries are building blocks for topographic mapping and satellite imageries are prime source of data for inaccessible terrain. When the required mapping scale is of the order 10k or higher, the accuracy needed is also of higher order. It becomes imperative to evaluate the accuracy of available high resolution DEMs and corresponding imageries to provide quality products for mapping. The present study is encouraged by the fact that not every place of our earth is accessible, so an assessment of satellite data products is required for precise mapping. Here, the accuracy assessment has been carried out in terms of RMSE, SD, CE90 and LE90 of various products viz. Carosat-1, Cartosat-2E, Worldview-2 (WV), Vricon, Pleiades, ALOS-World-3D (AW3D) ASTER, SRTM with Yahoo image. GCPs acquired by DGPS field survey were used to evaluate the products. The results have demonstrated that Vricon 0.5 m ortho-image provides the best RMSE (3.42) and CE90 (4.65); however, WV and Vricon DEM turns out to be best with RMSE of 2.20 m and 2.90 m respectively. Both products are suitable for large scale topographic mapping. The data can be used for inaccessible terrain where GCPs are not available. However, Cartosat-1 and Cartosat-2E can be used where good GCPs are available. The outcome of study can be used for planning of data suitability for scale variant mapping and inaccessible terrain mapping.

Алгоритм адаптивной коррекции структурных форм глобальных цифровых моделей высот

Due to various factors, such as the interpolation step or automatic correlators specifics, global digital elevation models (DEM) often have an effect of understating the heights, which leads to inaccurate display of structural landforms e.g. ridges. The algorithm of adaptive correction of structural landforms elevation on DEM is proposed in this article. The algorithm consists of two stages. In the first stage, an automatic classification of structural forms is performed based on height difference between neighboring DEM elements. In the second stage, the DEM elements are corrected based on the assigned classes. Adaptivity of the algorithm allows to use it for any kind of terrain and elevation ranges. The algorithm was tested on the global DEM ALOS World 3D (ALOS W3D30); the accuracy was assessed by geodetic reference network and ICESat mission data. The developed algorithm shows an improvement of DEM accuracy, especially in high-altitude areas, and it also helps to reveal areas requiring additional verification.

Which DEM is best for analyzing fluvial landscape development in mountainous terrains?

Regional studies of fluvial landforms and long-term (Quaternary) landscape development in remote mountain landscapes routinely use satellite-derived DEM data sets. The SRTM and ASTER DEMs are the most commonly utilised because of their longer availability, free cost, and ease of access. However, rapid technological developments mean that newer and higher resolution DEM data sets such as ALOS World 3D (AW3D) and TanDEM-X are being released to the scientific community. Geomorphologists are thus faced with an increasingly problematic challenge of selecting an appropriate DEM for their landscape analyses. Here, we test the application of four medium resolution DEM products (30m=SRTM, ASTER, AW3D; 12m=TanDEM-X) for qualitative and quantitative analysis of a fluvial mountain landscape using the Dades River catchment (High Atlas Mountains, Morocco). This landscape comprises significant DEM remote sensing challenges, notably a high mountain relief, steep slopes, and a deeply incised high sinuosity drainage network with narrow canyon/gorge reaches. Our goal was to see which DEM produced the most representative best fit drainage network and meaningful quantification. To achieve this, we used ArcGIS and Stream Profiler platforms to generate catchment hillshade and slope rasters and to extract drainage network, channel long profile and channel slope, and area data. TanDEM-X produces the clearest landscape representation but with channel routing errors in localised high relief areas. Thirty-metre DEMs are smoother and less detailed, but the AW3D shows the closest fit to the real drainage network configuration. The TanDEM-X elevation values are the closest to field-derived GPS measurements. Long profiles exhibit similar shapes but with minor differences in length, elevation, and the degree of noise/smoothing, with AW3D producing the best representation. Slope-area plots display similarly positioned slope-break knickpoints with modest differences in steepness and concavity indices, but again best represented by AW3D. Collectively, our study shows that despite the higher effective resolution of TanDEM-X (12m), the AW3D (30m) data performs strongly across all analyses suggesting that it currently offers the greatest potential for regional mountain geomorphological analyses.

PROBLEMS AND LIMITATIONS OF SATELLITE IMAGE ORIENTATION FOR DETERMINATION OF HEIGHT MODELS

Abstract. The usual satellite image orientation is based on bias corrected rational polynomial coefficients (RPC). The RPC are describing the direct sensor orientation of the satellite images. The locations of the projection centres today are without problems, but an accuracy limit is caused by the attitudes. Very high resolution satellites today are very agile, able to change the pointed area over 200km within 10 to 11 seconds. The corresponding fast attitude acceleration of the satellite may cause a jitter which cannot be expressed by the third order RPC, even if it is recorded by the gyros. Only a correction of the image geometry may help, but usually this will not be done. The first indication of jitter problems is shown by systematic errors of the y-parallaxes (py) for the intersection of corresponding points during the computation of ground coordinates. These y-parallaxes have a limited influence to the ground coordinates, but similar problems can be expected for the x-parallaxes, determining directly the object height. Systematic y-parallaxes are shown for Ziyuan-3 (ZY3), WorldView-2 (WV2), Pleiades, Cartosat-1, IKONOS and GeoEye. Some of them have clear jitter effects. In addition linear trends of py can be seen. Linear trends in py and tilts in of computed height models may be caused by limited accuracy of the attitude registration, but also by bias correction with affinity transformation. The bias correction is based on ground control points (GCPs). The accuracy of the GCPs usually does not cause some limitations but the identification of the GCPs in the images may be difficult. With 2-dimensional bias corrected RPC-orientation by affinity transformation tilts of the generated height models may be caused, but due to large affine image deformations some satellites, as Cartosat-1, have to be handled with bias correction by affinity transformation. Instead of a 2-dimensional RPC-orientation also a 3-dimensional orientation is possible, respecting the object height more as by 2-dimensional orientation. The 3-dimensional orientation showed advantages for orientation based on a limited number of GCPs, but in case of poor GCP distribution it may cause also negative effects. For some of the used satellites the bias correction by affinity transformation showed advantages, but for some other the bias correction by shift was leading to a better levelling of the generated height models, even if the root mean square (RMS) differences at the GCPs were larger as for bias correction by affinity transformation. The generated height models can be analyzed and corrected with reference height models. For the used data sets accurate reference height models are available, but an analysis and correction with the free of charge available SRTM digital surface model (DSM) or ALOS World 3D (AW3D30) is also possible and leads to similar results. The comparison of the generated height models with the reference DSM shows some height undulations, but the major accuracy influence is caused by tilts of the height models. Some height model undulations reach up to 50 % of the ground sampling distance (GSD), this is not negligible but it cannot be seen not so much at the standard deviations of the height. In any case an improvement of the generated height models is possible with reference height models. If such corrections are applied it compensates possible negative effects of the type of bias correction or 2-dimensional orientations against 3-dimensional handling.

Validation of digital elevation models (DEMs) and comparison of geomorphic metrics on the southern Central Andean Plateau

Abstract. In this study, we validate and compare elevation accuracy and geomorphic metrics of satellite-derived digital elevation models (DEMs) on the southern Central Andean Plateau. The plateau has an average elevation of 3.7 km and is characterized by diverse topography and relief, lack of vegetation, and clear skies that create ideal conditions for remote sensing. At 30 m resolution, SRTM-C, ASTER GDEM2, stacked ASTER L1A stereopair DEM, ALOS World 3D, and TanDEM-X have been analyzed. The higher-resolution datasets include 12 m TanDEM-X, 10 m single-CoSSC TerraSAR-X/TanDEM-X DEMs, and 5 m ALOS World 3D. These DEMs are state of the art for optical (ASTER and ALOS) and radar (SRTM-C and TanDEM-X) spaceborne sensors. We assessed vertical accuracy by comparing standard deviations of the DEM elevation versus 307 509 differential GPS measurements across 4000 m of elevation. For the 30 m DEMs, the ASTER datasets had the highest vertical standard deviation at &gt; 6.5 m, whereas the SRTM-C, ALOS World 3D, and TanDEM-X were all &lt; 3.5 m. Higher-resolution DEMs generally had lower uncertainty, with both the 12 m TanDEM-X and 5 m ALOS World 3D having &lt; 2 m vertical standard deviation. Analysis of vertical uncertainty with respect to terrain elevation, slope, and aspect revealed the low uncertainty across these attributes for SRTM-C (30 m), TanDEM-X (12–30 m), and ALOS World 3D (5–30 m). Single-CoSSC TerraSAR-X/TanDEM-X 10 m DEMs and the 30 m ASTER GDEM2 displayed slight aspect biases, which were removed in their stacked counterparts (TanDEM-X and ASTER Stack). Based on low vertical standard deviations and visual inspection alongside optical satellite data, we selected the 30 m SRTM-C, 12–30 m TanDEM-X, 10 m single-CoSSC TerraSAR-X/TanDEM-X, and 5 m ALOS World 3D for geomorphic metric comparison in a 66 km2 catchment with a distinct river knickpoint. Consistent m∕n values were found using chi plot channel profile analysis, regardless of DEM type and spatial resolution. Slope, curvature, and drainage area were calculated and plotting schemes were used to assess basin-wide differences in the hillslope-to-valley transition related to the knickpoint. While slope and hillslope length measurements vary little between datasets, curvature displays higher magnitude measurements with fining resolution. This is especially true for the optical 5 m ALOS World 3D DEM, which demonstrated high-frequency noise in 2–8 pixel steps through a Fourier frequency analysis. The improvements in accurate space-radar DEMs (e.g., TanDEM-X) for geomorphometry are promising, but airborne or terrestrial data are still necessary for meter-scale analysis.

Large-scale Landscape Mapping for Environmental Risk Assessment in the Arctic of Western Siberia (Russia)

Landscape mapping is widely used for the implementation of oil and gas development projects in the Russian Arctic, in particular for environmental impact and risk assessment. Large-scale landscape maps (1:25,000 – 1:100,000) have already been developed within these types of studies for the Yamal project and Tambey group of fields, and for fields in the southern Gydan Peninsula and Nadym-Pur-Taz interfluve. In this study, methods of large-scale inventory landscape mapping were developed and evaluation and advisory maps were generated. Modern research and mapping methods were applied in the preparation of a landscape map of Bely Island (in the Kara Sea). The final data processing included the correction of the planimetric part of the landscape map, and adding information about terrain types and types of landscape units to the database. The configuration of the map was complemented by images and data about areas of the main map units. The morphometric analysis of the research areas was carried out using ALOS World 3D and AsterDEM in the program SAGA.

VERTICAL ACCURACY ASSESSMENT OF 30-M RESOLUTION ALOS, ASTER, AND SRTM GLOBAL DEMS OVER NORTHEASTERN MINDANAO, PHILIPPINES

Abstract. The ALOS World 3D – 30 m (AW3D30), ASTER Global DEM Version 2 (GDEM2), and SRTM-30 m are Digital Elevation Models (DEMs) that have been made available to the general public free of charge. An important feature of these DEMs is their unprecedented horizontal resolution of 30-m and almost global coverage. The very recent release of these DEMs, particularly AW3D30 and SRTM- 30 m, calls for opportunities for the conduct of localized assessment of the DEM’s quality and accuracy to verify their suitability for a wide range of applications in hydrology, geomorphology, archaelogy, and many others. In this study, we conducted a vertical accuracy assessment of these DEMs by comparing the elevation of 274 control points scattered over various sites in northeastern Mindanao, Philippines. The elevations of these control points (referred to the Mean Sea Level, MSL) were obtained through 3rd order differential levelling using a high precision digital level, and their horizontal positions measured using a global positioning system (GPS) receiver. These control points are representative of five (5) land-cover classes namely brushland (45 points), built-up (32), cultivated areas (97), dense vegetation (74), and grassland (26). Results showed that AW3D30 has the lowest Root Mean Square Error (RMSE) of 5.68 m, followed by SRTM-30 m (RMSE = 8.28 m), and ASTER GDEM2 (RMSE = 11.98 m). While all the three DEMs overestimated the true ground elevations, the mean and standard deviations of the differences in elevations were found to be lower in AW3D30 compared to SRTM-30 m and ASTER GDEM2. The superiority of AW3D30 over the other two DEMS was also found to be consistent even under different landcover types, with AW3D30's RMSEs ranging from 4.29 m (built-up) to 6.75 m (dense vegetation). For SRTM-30 m, the RMSE ranges from 5.91 m (built-up) to 10.42 m (brushland); for ASTER GDEM2, the RMSE ranges from 9.27 m (brushland) to 14.88 m (dense vegetation). The results of the vertical accuracy assessment suggest that the AW3D30 is more accurate than SRTM-30 m and ASTER GDEM2, at least for the areas considered in this study. On the other hand, the tendencies of the three DEMs to overestimate true ground elevation can be considered an important finding that users of the DEMs in the Philippines should be aware of, and must be considered into decisions regarding use of these data products in various applications.

VERTICAL ACCURACY ASSESSMENT OF 30-M RESOLUTION ALOS, ASTER, AND SRTM GLOBAL DEMS OVER NORTHEASTERN MINDANAO, PHILIPPINES

The ALOS World 3D &amp;ndash; 30&amp;thinsp;m (AW3D30), ASTER Global DEM Version 2 (GDEM2), and SRTM-30&amp;thinsp;m are Digital Elevation Models (DEMs) that have been made available to the general public free of charge. An important feature of these DEMs is their unprecedented horizontal resolution of 30-m and almost global coverage. The very recent release of these DEMs, particularly AW3D30 and SRTM- 30&amp;thinsp;m, calls for opportunities for the conduct of localized assessment of the DEM’s quality and accuracy to verify their suitability for a wide range of applications in hydrology, geomorphology, archaelogy, and many others. In this study, we conducted a vertical accuracy assessment of these DEMs by comparing the elevation of 274 control points scattered over various sites in northeastern Mindanao, Philippines. The elevations of these control points (referred to the Mean Sea Level, MSL) were obtained through 3rd order differential levelling using a high precision digital level, and their horizontal positions measured using a global positioning system (GPS) receiver. These control points are representative of five (5) land-cover classes namely brushland (45 points), built-up (32), cultivated areas (97), dense vegetation (74), and grassland (26). Results showed that AW3D30 has the lowest Root Mean Square Error (RMSE) of 5.68&amp;thinsp;m, followed by SRTM-30&amp;thinsp;m (RMSE&amp;thinsp;=&amp;thinsp;8.28&amp;thinsp;m), and ASTER GDEM2 (RMSE&amp;thinsp;=&amp;thinsp;11.98&amp;thinsp;m). While all the three DEMs overestimated the true ground elevations, the mean and standard deviations of the differences in elevations were found to be lower in AW3D30 compared to SRTM-30&amp;thinsp;m and ASTER GDEM2. The superiority of AW3D30 over the other two DEMS was also found to be consistent even under different landcover types, with AW3D30's RMSEs ranging from 4.29&amp;thinsp;m (built-up) to 6.75&amp;thinsp;m (dense vegetation). For SRTM-30&amp;thinsp;m, the RMSE ranges from 5.91&amp;thinsp;m (built-up) to 10.42&amp;thinsp;m (brushland); for ASTER GDEM2, the RMSE ranges from 9.27&amp;thinsp;m (brushland) to 14.88&amp;thinsp;m (dense vegetation). The results of the vertical accuracy assessment suggest that the AW3D30 is more accurate than SRTM-30&amp;thinsp;m and ASTER GDEM2, at least for the areas considered in this study. On the other hand, the tendencies of the three DEMs to overestimate true ground elevation can be considered an important finding that users of the DEMs in the Philippines should be aware of, and must be considered into decisions regarding use of these data products in various applications.