scholarly journals IMPROVEMENT OF DEM GENERATION FROM ASTER IMAGES USING SATELLITE JITTER ESTIMATION AND OPEN SOURCE IMPLEMENTATION

2015 ◽  
Vol XL-1-W5 ◽  
pp. 249-253 ◽  
Author(s):  
L. Girod ◽  
C. Nuth ◽  
A. Kääb
Keyword(s):  
Open Source ◽  
Thermal Emission ◽  
Ground Truth ◽  
Three Dimensions ◽  
Glacier Mass Balance ◽  
Mountain Glacier ◽  
Ground Control Points ◽  
Rational Polynomial ◽  
Cross Track

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system embarked on the Terra (EOS AM-1) satellite has been a source of stereoscopic images covering the whole globe at a 15m resolution at a consistent quality for over 15 years. The potential of this data in terms of geomorphological analysis and change detection in three dimensions is unrivaled and needs to be exploited. However, the quality of the DEMs and ortho-images currently delivered by NASA (ASTER DMO products) is often of insufficient quality for a number of applications such as mountain glacier mass balance. For this study, the use of Ground Control Points (GCPs) or of other ground truth was rejected due to the global “big data” type of processing that we hope to perform on the ASTER archive. We have therefore developed a tool to compute Rational Polynomial Coefficient (RPC) models from the ASTER metadata and a method improving the quality of the matching by identifying and correcting jitter induced cross-track parallax errors. Our method outputs more accurate DEMs with less unmatched areas and reduced overall noise. The algorithms were implemented in the open source photogrammetric library and software suite MicMac.

scholarly journals GLACIER VOLUME CHANGE ESTIMATION USING TIME SERIES OF IMPROVED ASTER DEMS

2016 ◽  
Vol XLI-B8 ◽  
pp. 489-494 ◽  
Author(s):  
Luc Girod ◽  
Christopher Nuth ◽  
Andreas Kääb
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Volume Change ◽  
Thermal Emission ◽  
Aster Data ◽  
Rational Polynomial ◽  
The Cross ◽  
Cross Track ◽  
Along Track

Volume change data is critical to the understanding of glacier response to climate change. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system embarked on the Terra (EOS AM-1) satellite has been a unique source of systematic stereoscopic images covering the whole globe at 15m resolution and at a consistent quality for over 15 years. While satellite stereo sensors with significantly improved radiometric and spatial resolution are available to date, the potential of ASTER data lies in its long consistent time series that is unrivaled, though not fully exploited for change analysis due to lack of data accuracy and precision. Here, we developed an improved method for ASTER DEM generation and implemented it in the open source photogrammetric library and software suite MicMac. The method relies on the computation of a rational polynomial coefficients (RPC) model and the detection and correction of cross-track sensor jitter in order to compute DEMs. ASTER data are strongly affected by attitude jitter, mainly of approximately 4 km and 30 km wavelength, and improving the generation of ASTER DEMs requires removal of this effect. Our sensor modeling does not require ground control points and allows thus potentially for the automatic processing of large data volumes. <br><br> As a proof of concept, we chose a set of glaciers with reference DEMs available to assess the quality of our measurements. We use time series of ASTER scenes from which we extracted DEMs with a ground sampling distance of 15m. Our method directly measures and accounts for the cross-track component of jitter so that the resulting DEMs are not contaminated by this process. Since the along-track component of jitter has the same direction as the stereo parallaxes, the two cannot be separated and the elevations extracted are thus contaminated by along-track jitter. Initial tests reveal no clear relation between the cross-track and along-track components so that the latter seems not to be easily modeled analytically from the first one. We thus remove the remaining along-track jitter effects in the DEMs statistically through temporal DEM stacks to finally compute the glacier volume changes over time. Our method yields cleaner and spatially more complete elevation data, which also proved to be more in accordance to reference DEMs, compared to NASA’s AST14DMO DEM standard products. <br><br> The quality of the demonstrated measurements promises to further unlock the underused potential of ASTER DEMs for glacier volume change time series on a global scale. The data produced by our method will help to better understand the response of glaciers to climate change and their influence on runoff and sea level.

scholarly journals GLACIER VOLUME CHANGE ESTIMATION USING TIME SERIES OF IMPROVED ASTER DEMS

2016 ◽  
Vol XLI-B8 ◽  
pp. 489-494
Author(s):  
Luc Girod ◽  
Christopher Nuth ◽  
Andreas Kääb
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Volume Change ◽  
Thermal Emission ◽  
Aster Data ◽  
Rational Polynomial ◽  
The Cross ◽  
Cross Track ◽  
Along Track

Volume change data is critical to the understanding of glacier response to climate change. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system embarked on the Terra (EOS AM-1) satellite has been a unique source of systematic stereoscopic images covering the whole globe at 15m resolution and at a consistent quality for over 15 years. While satellite stereo sensors with significantly improved radiometric and spatial resolution are available to date, the potential of ASTER data lies in its long consistent time series that is unrivaled, though not fully exploited for change analysis due to lack of data accuracy and precision. Here, we developed an improved method for ASTER DEM generation and implemented it in the open source photogrammetric library and software suite MicMac. The method relies on the computation of a rational polynomial coefficients (RPC) model and the detection and correction of cross-track sensor jitter in order to compute DEMs. ASTER data are strongly affected by attitude jitter, mainly of approximately 4 km and 30 km wavelength, and improving the generation of ASTER DEMs requires removal of this effect. Our sensor modeling does not require ground control points and allows thus potentially for the automatic processing of large data volumes. <br><br> As a proof of concept, we chose a set of glaciers with reference DEMs available to assess the quality of our measurements. We use time series of ASTER scenes from which we extracted DEMs with a ground sampling distance of 15m. Our method directly measures and accounts for the cross-track component of jitter so that the resulting DEMs are not contaminated by this process. Since the along-track component of jitter has the same direction as the stereo parallaxes, the two cannot be separated and the elevations extracted are thus contaminated by along-track jitter. Initial tests reveal no clear relation between the cross-track and along-track components so that the latter seems not to be easily modeled analytically from the first one. We thus remove the remaining along-track jitter effects in the DEMs statistically through temporal DEM stacks to finally compute the glacier volume changes over time. Our method yields cleaner and spatially more complete elevation data, which also proved to be more in accordance to reference DEMs, compared to NASA’s AST14DMO DEM standard products. <br><br> The quality of the demonstrated measurements promises to further unlock the underused potential of ASTER DEMs for glacier volume change time series on a global scale. The data produced by our method will help to better understand the response of glaciers to climate change and their influence on runoff and sea level.

scholarly journals Performance Assessment of TanDEM-X DEM for Mountain Glacier Elevation Change Detection

2019 ◽  
Vol 11 (2) ◽  
pp. 187 ◽  
Author(s):  
Julian Podgórski ◽  
Christophe Kinnard ◽  
Michał Pętlicki ◽  
Roberto Urrutia
Keyword(s):  
Change Detection ◽  
Mass Balance ◽  
Laser Scanning ◽  
Thermal Emission ◽  
Ground Truth ◽  
Slope Aspect ◽  
Glacier Mass Balance ◽  
Mountain Glacier ◽  
German Aerospace ◽  
Terrain Elevation

TanDEM-X digital elevation model (DEM) is a global DEM released by the German Aerospace Center (DLR) at outstanding resolution of 12 m. However, the procedure for its creation involves the combination of several DEMs from acquisitions spread between 2011 and 2014, which casts doubt on its value for precise glaciological change detection studies. In this work we present TanDEM-X DEM as a high-quality product ready for use in glaciological studies. We compare it to Aerial Laser Scanning (ALS)-based dataset from April 2013 (1 m), used as the ground-truth reference, and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) V003 DEM and SRTM v3 DEM (both 30 m), serving as representations of past glacier states. We use a method of sub-pixel coregistration of DEMs by Nuth and Kääb (2011) to determine the geometric accuracy of the products. In addition, we propose a slope-aspect heatmap-based workflow to remove the errors resulting from radar shadowing over steep terrain. Elevation difference maps obtained by subtraction of DEMs are analyzed to obtain accuracy assessments and glacier mass balance reconstructions. The vertical accuracy (± standard deviation) of TanDEM-X DEM over non-glacierized area is very good at 0.02 ± 3.48 m. Nevertheless, steep areas introduce large errors and their filtering is required for reliable results. The 30 m version of TanDEM-X DEM performs worse than the finer product, but its accuracy, −0.08 ± 7.57 m, is better than that of SRTM and ASTER. The ASTER DEM contains errors, possibly resulting from imperfect DEM creation from stereopairs over uniform ice surface. Universidad Glacier has been losing mass at a rate of −0.44 ± 0.08 m of water equivalent per year between 2000 and 2013. This value is in general agreement with previously reported mass balance estimated with the glaciological method for 2012–2014.

Model to Estimate the Human Factor Quality in FLOSS Development

2015 ◽  
pp. 219-236
Author(s):  
Zulaima Chiquin ◽  
Kenyer Domínguez ◽  
Luis E. Mendoza ◽  
Edumilis Méndez
Keyword(s):  
Decision Making ◽  
Human Resources ◽  
Open Source ◽  
Open Source Software ◽  
Human Factor ◽  
Three Dimensions ◽  
Decision Making Process ◽  
Self Evaluation ◽  
Systemic Quality

This chapter presents a Model to Estimate the Human Factor Quality in Free/Libre Open Source Software (FLOSS) Development, or EHFQ-FLOSS. The model consists of three dimensions: Levels (individual, community, and foundation), Aspects (internal or contextual), and Forms of Evaluation (self-evaluation, co-evaluation, and hetero-evaluation). Furthermore, this model provides 145 metrics applicable to all three levels, as well as an algorithm that guides their proper application to estimate the systemic quality of human resources involved in the development of FLOSS, guide the decision-making process, and take possible corrective actions.

scholarly journals DEM quality assessment for quantification of glacier surface change

2007 ◽  
Vol 46 ◽  
pp. 189-194 ◽  
Author(s):  
Addy Pope ◽  
Tavi Murray ◽  
Adrian Luckman
Keyword(s):  
Quality Assessment ◽  
Control Points ◽  
Glacier Surface ◽  
Mountain Glacier ◽  
Ground Control Points ◽  
Data Quality Assessment ◽  
Digital Elevation ◽  
Multiple Input ◽  
Warning Model

AbstractPhotogrammetric digital elevation models (DEMs) are often used to derive and monitor surfaces in inaccessible areas. They have been used to monitor the spatial and temporal change of glacier surfaces in order to assess glacier response to climate change. However, deriving photogrammetric DEMs of steep mountainous topography where the surface is often obscured by regions of deep shadow and snow is particularly difficult. Assessing the quality of the derived surface can also be problematic, as high-accuracy ground-control points may be limited and poorly distributed throughout the modelled area. We present a method of assessing the quality of a derived surface through a detailed sensitivity analysis of the DEM collection parameters through a multiple input failure warning model (MIFWM). The variance of a DEM cell elevation is taken as an indicator of surface reliability allowing potentially unreliable areas to be excluded from further analysis. This analysis allows the user to place greater confidence in the remaining DEM. An example of this method is presented for a small mountain glacier in Svalbard, and the MIFWM is shown to label as unreliable more DEM cells over the entire DEM area, but fewer over the glacier surface, than other methods of data quality assessment. The MIFWM is shown to be an effective and easily used method for assessing DEM surface quality.

scholarly journals EVALUATION OF ASTER GDEM V3 USING ICESAT LASER ALTIMETRY

2016 ◽  
Vol XLI-B4 ◽  
pp. 117-124
Author(s):  
C. C. Carabajal ◽  
J.-P. Boy
Keyword(s):  
Thermal Emission ◽  
Ground Control ◽  
Control Points ◽  
Ice Cloud ◽  
Aster Gdem ◽  
Ground Control Points ◽  
Digital Elevation ◽  
Elevation Model ◽  
Globally Distributed

We have used a set of Ground Control Points (GCPs) derived from altimetry measurements from the Ice, Cloud and land Elevation Satellite (ICESat) to evaluate the quality of the 30 m posting ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) Global Digital Elevation Model (GDEM) V3 elevation products produced by NASA/METI for Greenland and Antarctica. These data represent the highest quality globally distributed altimetry measurements that can be used for geodetic ground control, selected by applying rigorous editing criteria, useful at high latitudes, where other topographic control is scarce. Even if large outliers still remain in all ASTER GDEM V3 data for both, Greenland and Antarctica, they are significantly reduced when editing ASTER by number of scenes (N≥5) included in the elevation processing. For 667,354 GCPs in Greenland, differences show a mean of 13.74 m, a median of -6.37 m, with an RMSE of 109.65 m. For Antarctica, 6,976,703 GCPs show a mean of 0.41 m, with a median of -4.66 m, and a 54.85 m RMSE, displaying smaller means, similar medians, and less scatter than GDEM V2. Mean and median differences between ASTER and ICESat are lower than 10 m, and RMSEs lower than 10 m for Greenland, and 20 m for Antarctica when only 9 to 31 scenes are included.

scholarly journals EVALUATING SURFACE MESH RECONSTRUCTION OF OPEN SCENES

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 369-376
Author(s):  
Y. Marchand ◽  
B. Vallet ◽  
L. Caraffa
Keyword(s):  
Open Source ◽  
Surface Reconstruction ◽  
Point Cloud ◽  
Synthetic Data ◽  
Ground Truth ◽  
Surface Mesh ◽  
Rigorous Evaluation ◽  
Quality Metric ◽  
Mesh Reconstruction

Abstract. This paper addresses the evaluation of algorithms reconstructing a watertight surface from a point cloud acquired on an open scene. The objective is to set a rigorous protocol measuring the quality of the reconstruction and to propose a quality metric that is informative with respect to the various qualities that such an algorithm should have, and in particular its capacity to interpolate and extrapolate accurately. Our approach aims at being more informative and rigorous than previous works on this topic. In addition, we use publicly available data and our implementation is open-source. We argue that a rigorous evaluation of surface reconstruction of open scenes needs to be performed on synthetic data where a perfect continuous ground truth surface is available, so we developed our own LiDAR simulator of which we give a description in the present paper.

scholarly journals Novel Techniques for Void Filling in Glacier Elevation Change Data Sets

2020 ◽  
Vol 12 (23) ◽  
pp. 3917
Author(s):  
Thorsten Seehaus ◽  
Veniamin I. Morgenshtern ◽  
Fabian Hübner ◽  
Eberhard Bänsch ◽  
Matthias H. Braun
Keyword(s):  
Volume Change ◽  
Thermal Emission ◽  
Ground Truth ◽  
Reproducible Research ◽  
Navier Stokes ◽  
Glacier Mass Balance ◽  
Data Sets ◽  
Mass Balances ◽  
Elevation Change ◽  
Ground Truth Data

The increasing availability of digital elevation models (DEMs) facilitates the monitoring of glacier mass balances on local and regional scales. Geodetic glacier mass balances are obtained by differentiating DEMs. However, these computations are usually affected by voids in the derived elevation change data sets. Different approaches, using spatial statistics or interpolation techniques, were developed to account for these voids in glacier mass balance estimations. In this study, we apply novel void filling techniques, which are typically used for the reconstruction and retouche of images and photos, for the first time on elevation change maps. We selected 6210 km2 of glacier area in southeast Alaska, USA, covered by two void-free DEMs as the study site to test different inpainting methods. Different artificially voided setups were generated using manually defined voids and a correlation mask based on stereoscopic processing of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) acquisition. Three “novel” (Telea, Navier–Stokes and shearlet) as well as three “classical” (bilinear interpolation, local and global hypsometric methods) void filling approaches for glacier elevation data sets were implemented and evaluated. The hypsometric approaches showed, in general, the worst performance, leading to high average and local offsets. Telea and Navier–Stokes void filling showed an overall stable and reasonable quality. The best results are obtained for shearlet and bilinear void filling, if certain criteria are met. Considering also computational costs and feasibility, we recommend using the bilinear void filling method in glacier volume change analyses. Moreover, we propose and validate a formula to estimate the uncertainties caused by void filling in glacier volume change computations. The formula is transferable to other study sites, where no ground truth data on the void areas exist, and leads to higher accuracy of the error estimates on void-filled areas. In the spirit of reproducible research, we publish a software repository with the implementation of the novel void filling algorithms and the code reproducing the statistical analysis of the data, along with the data sets themselves.

scholarly journals Cross-Compiler Bipartite Vulnerability Search

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1356
Author(s):  
Paul Black ◽  
Iqbal Gondal
Keyword(s):  
Open Source ◽  
Ground Truth ◽  
Security Vulnerabilities ◽  
Bipartite Matching ◽  
Software Products ◽  
Svm Model ◽  
Wide Range ◽  
A New Technique ◽  
Function Similarity

Open-source libraries are widely used in software development, and the functions from these libraries may contain security vulnerabilities that can provide gateways for attackers. This paper provides a function similarity technique to identify vulnerable functions in compiled programs and proposes a new technique called Cross-Compiler Bipartite Vulnerability Search (CCBVS). CCBVS uses a novel training process, and bipartite matching to filter SVM model false positives to improve the quality of similar function identification. This research uses debug symbols in programs compiled from open-source software products to generate the ground truth. This automatic extraction of ground truth allows experimentation with a wide range of programs. The results presented in the paper show that an SVM model trained on a wide variety of programs compiled for Windows and Linux, x86 and Intel 64 architectures can be used to predict function similarity and that the use of bipartite matching substantially improves the function similarity matching performance.

scholarly journals EVALUATION OF ASTER GDEM V3 USING ICESAT LASER ALTIMETRY

2016 ◽  
Vol XLI-B4 ◽  
pp. 117-124 ◽  
Author(s):  
C. C. Carabajal ◽  
J.-P. Boy
Keyword(s):  
Thermal Emission ◽  
Ground Control ◽  
Control Points ◽  
Ice Cloud ◽  
Aster Gdem ◽  
Ground Control Points ◽  
Digital Elevation ◽  
Elevation Model ◽  
Globally Distributed

We have used a set of Ground Control Points (GCPs) derived from altimetry measurements from the Ice, Cloud and land Elevation Satellite (ICESat) to evaluate the quality of the 30 m posting ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) Global Digital Elevation Model (GDEM) V3 elevation products produced by NASA/METI for Greenland and Antarctica. These data represent the highest quality globally distributed altimetry measurements that can be used for geodetic ground control, selected by applying rigorous editing criteria, useful at high latitudes, where other topographic control is scarce. Even if large outliers still remain in all ASTER GDEM V3 data for both, Greenland and Antarctica, they are significantly reduced when editing ASTER by number of scenes (N≥5) included in the elevation processing. For 667,354 GCPs in Greenland, differences show a mean of 13.74 m, a median of -6.37 m, with an RMSE of 109.65 m. For Antarctica, 6,976,703 GCPs show a mean of 0.41 m, with a median of -4.66 m, and a 54.85 m RMSE, displaying smaller means, similar medians, and less scatter than GDEM V2. Mean and median differences between ASTER and ICESat are lower than 10 m, and RMSEs lower than 10 m for Greenland, and 20 m for Antarctica when only 9 to 31 scenes are included.

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