Digital Elevation Model Products Research Articles

Terrain Induced Biases in Clear-Sky Shortwave Radiation Due to Digital Elevation Model Resolution for Glaciers in Complex Terrain

Advancements in remote sensing, along with greater access to high spatial and temporal resolution imagery, have improved our ability to model glacier surface energy and mass balance in remote regions of complex terrain, such as High-mountain Asia (HMA). In general, net shortwave (SW) radiation accounts for the majority of energy available on a glacier surface during the summer months, suggesting that SW modeling errors can critically impact surface energy balance estimates. In this study, we model the clear-sky SW irradiance for a group of glaciers in the Everest region of HMA using a high-resolution (8-meter) digital elevation model (DEM) composite derived from commercial stereo satellite imagery. We then systematically downsample this DEM and considered the effect on incoming SW irradiance, with a sensitivity analysis for standard terrain attributes. The slope and aspect (combined) and topographic shading have the greatest impact on daily SW irradiance and also introduce a larger SW bias when DEM resolution is downsampled. Our results show that modeled incident SW is overestimated as resolution becomes coarser. For 10 selected glaciers in the Everest region, decreasing spatial resolution from 8 to 30 meters results in a range of average daily biases between +20 to +60 Wm-2 (or ~7 to 20%) at some high and low elevations, and an average bias of more than +100 Wm-2 (~33%) as resolution is coarsened to 500 meters. In order to determine the bearing these results have on surface melt, we explore the diurnal variability of this bias. Additionally, we compare our results with modeled incident SW using several global DEM products (ASTER, SRTM, and ALOS) to evaluate error introduced by lower resolution. Models using the 30-meter products show an overall average daily SW bias of +24 Wm-2 (or ~8%) across elevation with some elevations showing a bias up to +60 Wm-2 (~20%) on multiple glaciers. Taken together, our results demonstrate the value of high-resolution data to correct biases in modeled SW radiation and constrain uncertainties for glacier energy balance modeling in regions of complex terrain.

Visual and statistical comparison of ASTER, SRTM, and Cartosat digital elevation models for watershed

Accurate delineation of watershed and drainage networks is crucial for hydrological and geomorphological models, water resource management, change of floodplains, flood risk management, and surface water mapping. Since high-resolution digital elevation models (DEMs) are often not available, it is necessary to evaluate open source products. Various statistical measures were used to estimate the vertical accuracy of these freely available DEMs. Moreover, DEM products from Shuttle Radar Topography Mission (SRTM), Advanced Thermal Emission and Reflection Radiometer (ASTER), and Cartosat data were also compared. The study areas are located in the Vadodara district of Gujarat State of India. A comparison of SRTM-, ASTER-, and Cartosat-derived DEMs allowed a qualitative assessment of the vertical component of the error, whereas statistical measurements were used to estimate their vertical accuracy. In order to compare the frequency histograms of the elevation distributions in the DEMs in the study area, skewness and kurtosis were determined. Further, to obtain the degree of relationship between the DEMs, scatterplots, as well as correlation coefficients, were used. The results showed that all DEMs have imperfections in the delineation of a small river like Vishwamitri, and the comparison showed that SRTM 30 m and ASTER 30 m failed to delineate proper main drainage for the river. Cartosat 30 m DEM exhibited better results. The root mean square error (RMSE) was calculated as 7.21 m for ASTER and 3.24 m for SRTM. The correlation value of 0.94 indicates the existence of a strong positive linear correlation between SRTM and Cartosat. The study shows that for the study area ASTER elevation data were highly underestimated, whereas SRTM elevation data were slightly overestimated.

Comparison of Point Accuracies on Digital Elevation Model Obtained from Digital Air Photographs with Different Specifications

Photogrammetry is a map production technique or science applied by measurements made from terrestrial images with terrestrial cameras or more commonly used images taken with airborne cameras. With the development of technology, digital photogrammetry has been widely adopted in almost all areas of mapping. Especially digital orthophotos and digital elevation models, which are photogrammetric products, are being intensively utilized by the private sector due to their easy interpretability. Digital photogrammetry is also a good method to automatically collect digital elevation models. Digital elevation model production is an important process in photogrammetry. A digital elevation model is an important product by itself as well as plays an important role in creating products such as orthophoto. The geometrical accuracy of digital elevation model used in geomatics applications is of even greater importance. In this study, three different digital elevation models were produced using digital aerial photographs of 7 cm, 15 cm and 25 cm ground sample distance taken in 2011 of Aksaray University campus area. Then, by using the heights measured by GPS and read the same heights from the digital elevation model, root mean square errors of ground control points, check points and tie points were calculated and compared with recommended standards. When the results are examined, it is seen that the values were close to and below the recommended values. Therefore, it can be seen that the digital elevation models produced with the aerial photographs taken at 7, 15 and 25 cm ground sample distances can be used for studies that do not require.

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

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

Evaluating the suitability of different terrains for sustaining human settlements according to the local elevation range in China using the ASTER GDEM

The topographical suitability assessment of human settlements (SAHS) creates a solid foundation for regional population distribution and socio-economic development. Local elevation range (LER) is an important factor that can be used to assess the suitability of different terrains for sustaining human settlements. However, current digital elevation model (DEM)-based LER products suffer from some challenges typically because of their subjectively selected neighborhood scales and coarser spatial resolution. In this study, we initially determined the optimal statistical window and then calculated the appropriate LER with the finer resolution data of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global DEM (ASTER GDEM) products for China. Then, the appropriate LER was used to evaluate the topographical SAHS and its correlations with the national gridded population distribution (1 km × 1 km) in 2010. The results show that the optimal statistical window for calculating a 1 arc-second (about 30 m) resolution GDEM LER for China can be determined using a 51 × 51 grid unit (width × height) within a rectangular neighborhood, corresponding to an area of about 2.34 km2. Secondly, the LER values in the southern and western China were greater than those of the north and east, showing a trend which consistently reflects the general spatial features of landforms. Finally, the relationship between GDEM LER and population density was highly correlated with the R2 value of 0.81. It showed that 85.22% of the Chinese population was located in areas where the LER is lower than 500 m. The topographically suitable area within China decreased from the southeastern coastal zone towards the northwestern inland areas due to transition from plains and basins to plateaus and mountains. The total area of moderate to high suitable level was 423.84 × 104 km2, or 44.15% of the total land area, with 88.17% of the national population. Our study demonstrates the usefulness of appropriate LER in evaluating the topographical SAHS as well as its significant impact on population distribution.

Landcover-Dependent Assessment of the Relative Height Accuracy in TanDEM-X DEM Products

Digital elevation models (DEMs) are extensively used for a variety of scientific and commercial applications. For the global TanDEM-X DEM, one of the main performance parameters is the relative height accuracy, which is specified to be under 2 m for flat terrain. Land cover types where the radar signal penetrates into a volume, as forest and ice, are excluded from this specification. Knowing the accuracy of the DEM for a specific land cover type is essential for applications relying on it, such as navigation applications, gradient and aspect estimations, and others. This letter is meant to be as add-on the global relative analysis presented in [1] . Here, we present a characterization of the relative height accuracy based on the interferometric coherence assessing the performance for every class defined by the CCI Land Cover Maps at a continental and global basis. This characterization raises the awareness of the advantages and limitations of the DEM for each specific application and helps scientists using the TanDEM-X DEM to interpret their results. In addition, an estimation of the relative height accuracy for acquisitions where volume decorrelation is present is locally performed using the high-frequency component of repeat-pass DEMs differences. For two particular land cover types, both methods are compared. The main source of errors in the DEM generation is clearly associated with strong inhomogeneous signal returns, becoming a driving factor on the actual accuracy of the estimated mean phase center height.

Joining multi-epoch archival aerial images in a single SfM block allows 3-D change detection with almost exclusively image information

Archival aerial imagery is a worldwide resource for documenting past 3-D change at very high-resolution. However, external information is normally required so that accurate 3-D models can be computed from archival aerial imagery. In this research, we propose and test a new method which joins multi-epoch images in a single block in the first steps of the structure from motion (SfM) processing. It allows for computing coherent multi-temporal digital elevation models (DEMs) using just image information. This method is based on the invariance properties of the feature detection procedures that are at the root of the SfM algorithms.On a test site covering 170 km2, we applied SfM algorithms to a single image block consisting of all images captured at four different epochs and spanning a forty year period. We compared this approach to the more classical methods which imply a separation of epochs in different processing blocks. We tested different densities of ground control points derived simply and cheaply from a recent orthophoto and DEM, different ways of image preprocessing and different autocalibration procedures. By determining which choice most affected the final result through this extensive testing procedure, we evaluated the potential of the proposed method for detecting 3-D change.Our study showed that the proposed method resolves the problem of registration between epochs, so allowing the production of informative DEMs of difference using almost exclusively image information and limited photogrammetric expertise and human intervention. As the proposed method can be automatically applied using just image information, our results pave the way to more systematic processing of archival aerial imagery with very large spatio-temporal windows, which should greatly help document of past 3-D change.

Challenges and Opportunities for UAV-Based Digital Elevation Model Generation for Flood-Risk Management: A Case of Princeville, North Carolina.

Among the different types of natural disasters, floods are the most devastating, widespread, and frequent. Floods account for approximately 30% of the total loss caused by natural disasters. Accurate flood-risk mapping is critical in reducing such damages by correctly predicting the extent of a flood when coupled with rain and stage gage data, supporting emergency-response planning, developing land use plans and regulations with regard to the construction of structures and infrastructures, and providing damage assessment in both spatial and temporal measurements. The reliability and accuracy of such flood assessment maps is dependent on the quality of the digital elevation model (DEM) in flood conditions. This study investigates the quality of an Unmanned Aerial Vehicle (UAV)-based DEM for spatial flood assessment mapping and evaluating the extent of a flood event in Princeville, North Carolina during Hurricane Matthew. The challenges and problems of on-demand DEM production during a flooding event were discussed. An accuracy analysis was performed by comparing the water surface extracted from the UAV-derived DEM with the water surface/stage obtained using the nearby US Geologic Survey (USGS) stream gauge station and LiDAR data.

Defining Dunes: Evaluating How Dune Feature Definitions Affect Dune Interpretations from Remote Sensing

Wernette, P.; Thompson, S.; Eyler, R.; Taylor, H.; Taube, C.; Medlin, A.; Decuir, C., and Houser, C., 2018. Defining dunes: Evaluating how dune feature definitions affect dune interpretations from remote sensing.Coastal resiliency is the ability of a beach–dune system to recover to a previous state after a storm, and this resiliency is affected by prestorm beach and dune morphology and storm climate (i.e. storm frequency and intensity). Improvements in remote sensing technology such as LIDAR and structure from motion have enabled rapid collection and production of digital elevation models used to assess storm impact and recovery. Although rapid poststorm assessment requires a consistent approach for extracting dune morphology, relatively little attention has focused on defining the different parts of a dune. The goals of this paper are to examine how the definition of a dune feature drives the methodology used to extract dunes and to synthesize a comprehensive definition of dune features. An analysis of existing approaches for extracting beach and dune morphology demonstrates that there is considerable variation in how the beach–dune transition (i.e. dune toe) is defined. Many definitions are recursive or include ambiguous terminology, resulting in a dune toe or crest line position dependent on user interpretation of the definition. Other definitions rely heavily on user interpretation of dune features at varying stages in the feature extraction process. Reliance on visual interpretation can result in substantially different feature locations across different interpreters. Given the impact of varying definitions on dune resiliency assessments and legal implications for dune features location, this study proposes a series of semantic models for dune features. Semantic modelling of coastal morphology is vital for consistently and accurately assessing coastal recovery and predicting future coastal assessments on the basis of a consistent set of criteria.

TANDEM-X MISSION STATUS, PRODUCTS AND PERSPECTIVES

Abstract. TanDEM-X is an innovative single-pass interferometric radar mission, which is comprised of two formation flying satellites. The TerraSAR-X (TSX) satellite was launched on June 15th 2007, and its almost identically constructed twin satellite TanDEM-X (TDX) was launched on 21st of June 2010. Together they supply high-quality radar data in order to serve two main mission goals: Scientific observation of the Earth and provision of remote sensing data for the commercial market (TerraSAR-X mission), and the generation of a global digital elevation model (DEM) of the Earth’s surface (TanDEM-X mission). Between December 2010 and early 2015, radar data of all land surfaces has been acquired and as of September 2016 the final TanDEM-X DEM dataset has been available. This paper provides a final quality assessment of the TanDEM-X global DEM products with respect to the relative and absolute height accuracy and data coverage both at the global and geocell level. In addition, an overview on current mission status is given and new DEM products, which are currently in the scope of the TanDEM-X mission, are described.

A Beginner's Guide to Mesoscale Survey with Quadrotor-UAV Systems

ABSTRACTQuadrotor-UAV (unmanned aerial vehicle) systems are becoming increasingly ubiquitous in archaeological field research for the production of digital elevation models and orthophoto mosaics of sites, monuments, and landscapes. In order to make up for the lack of suitable imagery to use in a larger project on the landscapes surrounding Bronze Age tell sites in the Murghab delta of eastern Turkmenistan, we developed a protocol for the deployment of out-of-the-box UAV systems to document sites and their immediate environs. This article discusses the fundamentals of aerial survey based on our experience deploying a quadrotor UAV, using examples from our case study of the site of Togolok 1. We argue that the approach we developed is particularly useful for mesoscale survey, between 1 and 5 km2, and is particularly useful for producing technical quality outputs, even by relative newcomers to UAV-based aerial survey.

InSAR Baseline Estimation for Gaofen-3 Real-Time DEM Generation.

For Interferometry Synthetic Aperture Radar (InSAR), the normal baseline is one of the main factors that affects the accuracy of the ground elevation. For Gaofen-3 (GF-3) InSAR processing, the poor accuracy of the real-time orbit determination results in a large baseline error, leads to a modulation error in azimuth and a slope error in the range for timely Digital Elevation Model (DEM) generation. In order to address this problem, a novel baseline estimation approach based on Shuttle Radar Topography Mission (SRTM) DEM is proposed in this paper. Firstly, the orbit fitting is executed to remove the non-linear error factor, which is different from traditional methods. Secondly, the height errors are obtained in a slant-range plane between SRTM DEM and the GF-3 generated DEM, which can be used to estimate the baseline error with a linear variation. Then, the real-time orbit can be calibrated by the baseline error. Finally, the DEM generation is performed by using the modified baseline and orbit. This approach has the merit of spatial and precise orbital free ability. Based on the results of GF-3 interferometric SAR data for Hebei, the effectiveness of the proposed algorithm is verified and the accuracy of GF-3 real-time DEM products can be improved extensively.

Combination of satellite imagery with meteorological data for estimating reference evapotranspiration

<p>The Food and Agriculture Organization of the United Nations (FAO) in its publication No. 56 of the Irrigation and Drainage Series presents the FAO Penman-Monteith procedure for the estimation of reference evapotranspiration from meteorological data, however, its calculation may be complicated in areas where there are no weather stations. This paper presents an evaluation of the potential of the Land Surface Temperature and Digital Elevation Models products derived from the MODIS and ASTER sensors, both on board the Terra EOS AM-1 satellite, for the estimation of reference evapotranspiration using the Penman-Monteith FAO-56, Hargreaves, Thornthwaite and Blaney-Criddle models. The four models were compared with the method proposed by FAO calculated with the observed data of a ground based meteorological station, finding a significant relation with the models Penman-Monteith FAO-56 and Hargreaves.</p>

Generation of digital elevation model through aerial technique

Unmanned Aerial Vehicle (UAV) system, nowadays, is highly utilized to solve problems in various applications across different fields due to its low-cost, safety, and its low flying altitude. With photogrammetric techniques and latest available aerial technology, it is possible to utilize UAV for generation of Digital Elevation Model (DEM) and subsequently, determination of elevation on various geomorphology. Previously, this is only possible through deployment of manned aircraft and metric camera which requires monumental cost. This paper reviews the applications and developments of DEM generation. Three main components are presented in this review: (a) a summary of conventional surveying methods to determine elevation, subsequently generate a DEM, (b) a summary of remote sensing methods to generate DEM; namely satellites, and airborne platforms, and (c) findings and future possibilities for further studies. The review reveals that traditionally, DEM is produced through ground surveying methods, traditional photogrammetry methods, and derivation of contours and elevation points from hardcopy topographic maps. The chapters discuss each of the methods and common DEM products derived from them. Most of the studies reviewed herein articulate the mechanism of triangulation which is a method to rectify the DEM to its local geographical and elevation coordinates. So far, only a relatively small number of detailed studies have been conducted on the DEM produced by UAV. From the findings of flying the UAV at 4 different altitudes of 50 m, 80 m, 110 m and 140 m; much more research on the identification of elevation through UAV-based imagery is required from different altitude of flight. Hence, it is possible to use UAV to identify elevation in small areas which has limited project budget and time constraints.

AN IMPROVED INTERFEROMETRIC CALIBRATION METHOD BASED ON INDEPENDENT PARAMETER DECOMPOSITION

Abstract. Interferometric SAR is sensitive to earth surface undulation. The accuracy of interferometric parameters plays a significant role in precise digital elevation model (DEM). The interferometric calibration is to obtain high-precision global DEM by calculating the interferometric parameters using ground control points (GCPs). However, interferometric parameters are always calculated jointly, making them difficult to decompose precisely. In this paper, we propose an interferometric calibration method based on independent parameter decomposition (IPD). Firstly, the parameters related to the interferometric SAR measurement are determined based on the three-dimensional reconstruction model. Secondly, the sensitivity of interferometric parameters is quantitatively analyzed after the geometric parameters are completely decomposed. Finally, each interferometric parameter is calculated based on IPD and interferometric calibration model is established. We take Weinan of Shanxi province as an example and choose 4 TerraDEM-X image pairs to carry out interferometric calibration experiment. The results show that the elevation accuracy of all SAR images is better than 2.54 m after interferometric calibration. Furthermore, the proposed method can obtain the accuracy of DEM products better than 2.43 m in the flat area and 6.97 m in the mountainous area, which can prove the correctness and effectiveness of the proposed IPD based interferometric calibration method. The results provide a technical basis for topographic mapping of 1 : 50000 and even larger scale in the flat area and mountainous area.

Use of DEMs Derived from TLS and HRSI Data for Landslide Feature Recognition

This paper addresses the problems arising from the use of data acquired with two different remote sensing techniques—high-resolution satellite imagery (HRSI) and terrestrial laser scanning (TLS)—for the extraction of digital elevation models (DEMs) used in the geomorphological analysis and recognition of landslides, taking into account the uncertainties associated with DEM production. In order to obtain a georeferenced and edited point cloud, the two data sets require quite different processes, which are more complex for satellite images than for TLS data. The differences between the two processes are highlighted. The point clouds are interpolated on a DEM with a 1 m grid size using kriging. Starting from these DEMs, a number of contour, slope, and aspect maps are extracted, together with their associated uncertainty maps. Comparative analysis of selected landslide features drawn from the two data sources allows recognition and classification of hierarchical and multiscale landslide components. Taking into account the uncertainty related to the map enables areas to be located for which one data source was able to give more reliable results than another. Our case study is located in Southern Italy, in an area known for active landslides.

DEM generation using Ziyuan-3 mapping satellite imagery without ground control points

ABSTRACTThis article proposes a digital elevation model (DEM) generation approach using the Shuttle Radar Topography Mission (SRTM) DEM as the elevation constraint without ground control points. First, during the process of image block adjustment, we took advantage of the relatively high vertical accuracy of the SRTM-DEM in flat terrain regions and applied effective constraints on the object-space elevation-corrected value of tie points using the SRTM-DEM, achieving improved vertical accuracy for large-scale block adjustments. Subsequently, for the DEM matching process, multiple two-linear array stereo image pairs were obtained from along-track and across-track images with different look angles over the same region after the block adjustment. Then, the matching result of each stereo image pair underwent weighted fusion, before being used to generate the final DEM product. This approach can effectively enhance the matching quality and grid density of the final DEM product. The DEM generation experiment, using Ziyuan-3 images covering 186,000 km2 of Hubei Province, China, showed that the matching quality of the 10 m grid DEM was excellent. The vertical root mean square errors were 1.5 m in the flat regions and 2.96 m in the mountainous regions, thus achieving China’s 1:25,000 scale specification requirement for DEM products.

A suite of global, cross-scale topographic variables for environmental and biodiversity modeling

Topographic variation underpins a myriad of patterns and processes in hydrology, climatology, geography and ecology and is key to understanding the variation of life on the planet. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale research applications, however to date, such datasets are unavailable. Here we used the digital elevation model products of global 250 m GMTED2010 and near-global 90 m SRTM4.1dev to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile/tangential curvature, first/second order partial derivative, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches. While a cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at Data Citation 1 and for download and visualization at http://www.earthenv.org/topography.

Modeling variations in soil salinity in the oasis of Junggar Basin, China

AbstractSoil salinization leads to a significant degradation for oasis land. Variations in soil salinity are controlled by geologic, geomorphic, climatic, and hydrologic factors that are scale dependent. Many factors characterize soil salinity and its variations. Empirical mode decomposition (EMD) and correlation analysis are usually applied to examine the variations of soil salinity at different scales. However, few researches have been conducted on the modeling of these variations among different scales that requires further development and refinement. This paper investigates the potential of assessing scale‐specific variations in soil salinity via EMD using 2 modeling approaches (random forest and linear models). The remotely sensed environmental factors including land surface temperature, evapotranspiration, Tropical Rainfall Measuring Mission precipitation, and digital elevation model products were used as inputs for the models. The Junggar Basin in Xinjiang Province of China was selected as study area because the oasis was quite typical in the whole country and even in mid‐Asia. Soil salinity data and environmental factors were first decomposed using the EMD algorithm. Then, the decomposed components of the remotely sensed environmental factors were evaluated, and the most important components of each factor were selected to model the salinity variations that were represented by the decomposed components of soil salinity. The salinity variations estimated from the environmental factors were favorably consistent with the decomposed components of the soil salinity data, with coefficients of determination (R2) ranging from 0.24–0.52 and 0.73–0.98 for the linear and random forest models, respectively. In addition, land surface temperature and salinity were coupled well at the 326‐ and 334‐km scale. Our results showed that reasonably accurate results can be obtained using the proposed approach.

A global corrected SRTM DEM product for vegetated areas

ABSTRACTIt has been found that the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) is systematically higher than the actual land surface in vegetated areas. This study developed a new globally corrected SRTM DEM through reducing its systematic bias in vegetated areas. Over 150, 000 km2 airborne light detection and ranging (LiDAR) data along with spaceborne LiDAR, global canopy height data, global canopy cover data and global land cover data were collected to correct the SRTM DEM. A linear regression based method was used to estimate the original SRTM DEM error and therefore correct the SRTM DEM data. The results show that the original SRTM DEM data is around 6 m higher than the actual land surfaces on average across all vegetation types. Our corrected SRTM DEM data can significantly reduce the significant bias to near zero, and can also reduce the root-mean-square error by 1 m.