The Experts below are selected from a list of 43479 Experts worldwide ranked by ideXlab platform
David M. Wolock - One of the best experts on this subject based on the ideXlab platform.
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differences in topographic characteristics computed from 100 and 1000 m resolution Digital Elevation Model data
Hydrological Processes, 2000Co-Authors: David M. Wolock, Gregory J MccabeAbstract:Topographic characteristics computed from 100- and 1000-m resolution Digital Elevation Model (DEM) data are compared for 50 locations representing varied terrain in the conterminous USA. The topographic characteristics are three parameters used extensively in hydrological research and Modelling—slope (S), specific catchment area (As) and a wetness index computed as the logarithm of the specific catchment area divided by slope [ln(As/S)]. Slope values computed from 1000-m DEMs are smaller than those computed from 100-m DEMs; specific catchment area and the wetness index are larger for the 1000-m DEMs compared with the 100-m DEMs. Most of the differences between the 100- and 1000-m resolution DEMs can be attributed to terrain-discretization effects in the computation of the topographic characteristics and are not the result of smoothing or loss of terrain detail in the coarse data. In general, the terrain-discretization effects are greatest on flat terrain with long length-scale features, and the smoothing effects are greatest on steep terrain with short length-scale features. For the most part, the differences in the average values of the topographic characteristics computed from 100- and 1000-m resolution DEMs are predictable; that is, biases in the mean values for the characteristics computed from a 1000-m DEM can be corrected with simple linear equations. Copyright © 2000 John Wiley & Sons, Ltd.
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effects of Digital Elevation Model map scale and data resolution on a topography based watershed Model
Water Resources Research, 1994Co-Authors: David M. Wolock, Curtis V. PriceAbstract:The effects of Digital Elevation Model (DEM) map scale and data resolution on watershed Model predictions of hydrologic characteristics were determined for TOPModel, a topography-based watershed Model. The effects of topography on watershed hydrology are represented in TOPModel as the distribution of ln (a/tan B), where ln is the Napierian logarithm, a is the upslope area per unit contour length, and tan B is the gravitational gradient. The minimum, maximum, mean, variance, and skew values of the ln (a/tan B) distribution were computed from 1:24,000-scale (24K) DEMs at 30- and 90-m resolutions and from 1:250,000-scale (250K) DEMs at 90-m resolution for 71 areas in Pennsylvania, New York, and New Jersey. An analysis of TOPModel showed that Model predictions of the depth to the water table, the ratio of overland flow to total flow, peak flow, and variance and skew of predicted streamflow were affected by both the DEM map scale and data resolution. Further TOPModel analyses showed that the effects of DEM map scale and data resolution on Model predictions were due to the sensitivity of the predictions to the mean of the ln (a/tan B) distribution, which was affected by both DEM map scale and data resolution. DEM map scale affected the mean of the ln (a/tan B) distribution through its influence on the mean of the ln (a) distribution, which characterizes land-surface shape, and the mean of ln (1/tan B) distribution, which characterizes land-surface slope. DEM resolution, in contrast, affected the mean of the ln (a/tan B) distribution primarily by its influence on the mean of the ln (a) distribution.
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Effects of Digital Elevation Model map scale and data resolution on a topography‐based watershed Model
Water Resources Research, 1994Co-Authors: David M. Wolock, Curtis V. PriceAbstract:The effects of Digital Elevation Model (DEM) map scale and data resolution on watershed Model predictions of hydrologic characteristics were determined for TOPModel, a topography-based watershed Model. The effects of topography on watershed hydrology are represented in TOPModel as the distribution of ln (a/tan B), where ln is the Napierian logarithm, a is the upslope area per unit contour length, and tan B is the gravitational gradient. The minimum, maximum, mean, variance, and skew values of the ln (a/tan B) distribution were computed from 1:24,000-scale (24K) DEMs at 30- and 90-m resolutions and from 1:250,000-scale (250K) DEMs at 90-m resolution for 71 areas in Pennsylvania, New York, and New Jersey. An analysis of TOPModel showed that Model predictions of the depth to the water table, the ratio of overland flow to total flow, peak flow, and variance and skew of predicted streamflow were affected by both the DEM map scale and data resolution. Further TOPModel analyses showed that the effects of DEM map scale and data resolution on Model predictions were due to the sensitivity of the predictions to the mean of the ln (a/tan B) distribution, which was affected by both DEM map scale and data resolution. DEM map scale affected the mean of the ln (a/tan B) distribution through its influence on the mean of the ln (a) distribution, which characterizes land-surface shape, and the mean of ln (1/tan B) distribution, which characterizes land-surface slope. DEM resolution, in contrast, affected the mean of the ln (a/tan B) distribution primarily by its influence on the mean of the ln (a) distribution.
Martin Huber - One of the best experts on this subject based on the ideXlab platform.
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accuracy assessment of the global tandem x Digital Elevation Model with gps data
Isprs Journal of Photogrammetry and Remote Sensing, 2018Co-Authors: Birgit Wessel, Martin Huber, Christian Wohlfart, Ursula Marschalk, Detlev Kosmann, Achim RothAbstract:Abstract The primary goal of the German TanDEM-X mission is the generation of a highly accurate and global Digital Elevation Model (DEM) with global accuracies of at least 10 m absolute height error (linear 90% error). The global TanDEM-X DEM acquired with single-pass SAR interferometry was finished in September 2016. This paper provides a unique accuracy assessment of the final TanDEM-X global DEM using two different GPS point reference data sets, which are distributed across all continents, to fully characterize the absolute height error. Firstly, the absolute vertical accuracy is examined by about three million globally distributed kinematic GPS (KGPS) points derived from 19 KGPS tracks covering a total length of about 66,000 km. Secondly, a comparison is performed with more than 23,000 “GPS on Bench Marks” (GPS-on-BM) points provided by the US National Geodetic Survey (NGS) scattered across 14 different land cover types of the US National Land Cover Data base (NLCD). Both GPS comparisons prove an absolute vertical mean error of TanDEM-X DEM smaller than ±0.20 m, a Root Means Square Error (RMSE) smaller than 1.4 m and an excellent absolute 90% linear height error below 2 m. The RMSE values are sensitive to land cover types. For low vegetation the RMSE is ±1.1 m, whereas it is slightly higher for developed areas (±1.4 m) and for forests (±1.8 m). This validation confirms an outstanding absolute height error at 90% confidence level of the global TanDEM-X DEM outperforming the requirement by a factor of five. Due to its extensive and globally distributed reference data sets, this study is of considerable interests for scientific and commercial applications.
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generation and performance assessment of the global tandem x Digital Elevation Model
Isprs Journal of Photogrammetry and Remote Sensing, 2017Co-Authors: Paola Rizzoli, Markus Bachmann, Michele Martone, Carolina Gonzalez, Christopher Wecklich, Daniela Borla Tridon, Benjamin Brautigam, Daniel Schulze, Thomas Fritz, Martin HuberAbstract:Abstract The primary objective of the TanDEM-X mission is the generation of a global, consistent, and high-resolution Digital Elevation Model (DEM) with unprecedented global accuracy. The goal is achieved by exploiting the interferometric capabilities of the two twin SAR satellites TerraSAR-X and TanDEM-X, which fly in a close orbit formation, acting as an X-band single-pass interferometer. Between December 2010 and early 2015 all land surfaces have been acquired at least twice, difficult terrain up to seven or eight times. The acquisition strategy, data processing, and DEM calibration and mosaicking have been systematically monitored and optimized throughout the entire mission duration, in order to fulfill the specification. The processing of all data has finally been completed in September 2016 and this paper reports on the final performance of the TanDEM-X global DEM and presents the acquisition and processing strategy which allowed to obtain the final DEM quality. The results confirm the outstanding global accuracy of the delivered product, which can be now utilized for both scientific and commercial applications.
Achim Roth - One of the best experts on this subject based on the ideXlab platform.
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accuracy assessment of the global tandem x Digital Elevation Model with gps data
Isprs Journal of Photogrammetry and Remote Sensing, 2018Co-Authors: Birgit Wessel, Martin Huber, Christian Wohlfart, Ursula Marschalk, Detlev Kosmann, Achim RothAbstract:Abstract The primary goal of the German TanDEM-X mission is the generation of a highly accurate and global Digital Elevation Model (DEM) with global accuracies of at least 10 m absolute height error (linear 90% error). The global TanDEM-X DEM acquired with single-pass SAR interferometry was finished in September 2016. This paper provides a unique accuracy assessment of the final TanDEM-X global DEM using two different GPS point reference data sets, which are distributed across all continents, to fully characterize the absolute height error. Firstly, the absolute vertical accuracy is examined by about three million globally distributed kinematic GPS (KGPS) points derived from 19 KGPS tracks covering a total length of about 66,000 km. Secondly, a comparison is performed with more than 23,000 “GPS on Bench Marks” (GPS-on-BM) points provided by the US National Geodetic Survey (NGS) scattered across 14 different land cover types of the US National Land Cover Data base (NLCD). Both GPS comparisons prove an absolute vertical mean error of TanDEM-X DEM smaller than ±0.20 m, a Root Means Square Error (RMSE) smaller than 1.4 m and an excellent absolute 90% linear height error below 2 m. The RMSE values are sensitive to land cover types. For low vegetation the RMSE is ±1.1 m, whereas it is slightly higher for developed areas (±1.4 m) and for forests (±1.8 m). This validation confirms an outstanding absolute height error at 90% confidence level of the global TanDEM-X DEM outperforming the requirement by a factor of five. Due to its extensive and globally distributed reference data sets, this study is of considerable interests for scientific and commercial applications.
Kacem Chehdi - One of the best experts on this subject based on the ideXlab platform.
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Estimation of Variance and Spatial Correlation Width for Fine-Scale Measurement Error in Digital Elevation Model
IEEE Transactions on Geoscience and Remote Sensing, 2020Co-Authors: Mikhail Uss, Benoit Vozel, Vladimir Lukin, Kacem ChehdiAbstract:In this article, we borrow from the blind noise parameter estimation (BNPE) methodology early developed in the image processing field an original and innovative no-reference approach to estimate Digital Elevation Model (DEM) vertical error parameters without resorting to a reference DEM. The challenges associated with the proposed approach related to the physical nature of the error and its multifactor structure in DEM are discussed in detail. A suitable multivariate method is then developed for estimating the error in gridded DEM. It is built on a recently proposed vectorial BNPE method for estimating spatially correlated noise using noise informative areas and fractal Brownian motion. The new multivariate method is derived to estimate the effect of the stacking procedure and that of the epipolar line error on local (fine-scale) standard deviation and autocorrelation function width of photogrammetric DEM measurement error. Applying the new estimator to Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) GDEM2 and Advanced Land Observing Satellite (ALOS) World 3D DEMs, good agreement of derived estimates with results available in the literature is evidenced. Adopted for TanDEM-X-DEM, estimates obtained agree well with the values provided in the height error map. In future works, the proposed no-reference method for analyzing DEM error can be extended to a larger number of predictors for accounting for other factors influencing remote sensing (RS) DEM accuracy.
J A Ruizarias - One of the best experts on this subject based on the ideXlab platform.
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spatial disaggregation of satellite derived irradiance using a high resolution Digital Elevation Model
Solar Energy, 2010Co-Authors: J A Ruizarias, Tomas Cebecauer, J Tovarpescador, Marcel SuriAbstract:Downscaling of the Meteosat-derived solar radiation (∼5 km grid resolution) is based on decomposing the global irradiance and correcting the systematic bias of its components using the Elevation and horizon shadowing that are derived from the SRTM-3 Digital Elevation Model (3 arc sec resolution). The procedure first applies the Elevation correction based on the difference between coarse and high spatial resolution. Global irradiance is split into direct, diffuse circumsolar and diffuse isotropic components using statistical Models, and then corrections due to terrain shading and sky-view fraction are applied. The effect of reflected irradiance is analysed only in the theoretical section. The method was applied in the eastern Andalusia, Spain, and the validation was carried out for 22 days on April, July and December 2006 comparing 15-min estimates of the satellite-derived solar irradiance and observations from nine ground stations. Overall, the corrections of the satellite estimates in the studied region strongly reduced the mean bias of the estimates for clear and cloudy days from roughly 2.3% to 0.4%.
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on the use of the Digital Elevation Model to estimate the solar radiation in areas of complex topography
Meteorological Applications, 2006Co-Authors: J Tovarpescador, J A Ruizarias, D Pozovazquez, J Batlles, G Lopez, J L BoschAbstract:The development of solar energy as a power source in the next few years requires reliable estimation of available solar energy resources. At local scales, topography is the most important factor in determining the distribution of solar radiation at the surface. Interpolation techniques are usually employed to estimate solar radiation where stations are not available, but their usefulness is limited where topography is an important source of variability. The use of satellite data and more recently of Models based on techniques GIS, have contributed to solve this difficulty. In this work the usefulness of a Digital Elevation Model (DEM) in providing topographic information for the estimation of solar radiation in areas of complex topography is analysed. Daily global radiation values were generated using the Solar Analyst software, which uses topographic information to generate radiation data. The generated data were compared with the experimental data obtained from 14 radiometric stations located within the Sierra Nevada Natural Park (southern Spain), an area of complex topography. Results show the usefulness of the topographic information derived from a DEM to estimate the solar radiation in areas of complex topography. Nevertheless, results depend on the DEM resolution and it is important that other factors, such as the albedo, should also be taken into account to obtain better estimates. Copyright © 2006 John Wiley & Sons, Ltd.
