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Error propagation in regional geoid computation using spherical splines, least-squares collocation, and Stokes’s formula / Vegard Ophaug in Journal of geodesy, vol 94 n° 12 (December 2020)  

Public [article]  inJournal of geodesy > vol 94 n° 12 (December 2020) . - n° 120 Titre : Error propagation in regional geoid computation using spherical splines, least-squares collocation, and Stokes’s formula Type de document : Article/Communication Auteurs : Vegard Ophaug, Auteur ; Christian Gerlach, Auteur Année de publication : 2020 Article en page(s) : n° 120 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] altitude [Termes IGN] collocation par moindres carrés [Termes IGN] covariance [Termes IGN] erreur [Termes IGN] fonction spline [Termes IGN] formule de Stokes [Termes IGN] géoïde local [Termes IGN] propagation d'erreur Résumé : (auteur) Current International Association of Geodesy efforts within regional geoid determination include the comparison of different computation methods in the quest for the “1-cm geoid.” Internal (formal) and external (empirical) approaches to evaluate geoid errors exist, and ideally they should agree. Spherical radial base functions using the spline kernel (SK), least-squares collocation (LSC), and Stokes’s formula are three commonly used methods for regional geoid computation. The three methods have been shown to be theoretically equivalent, as well as to numerically agree on the millimeter level in a closed-loop environment using synthetic noise-free data (Ophaug and Gerlach in J Geod 91:1367–1382, 2017. https://doi.org/10.1007/s00190-017-1030-1PANIST). This companion paper extends the closed-loop method comparison using synthetic data, in that we investigate and compare the formal error propagation using the three methods. We use synthetic uncorrelated and correlated noise regimes, both on the 1-mGal (=10−5 ms−2) level, applied to the input data. The estimated formal errors are validated by comparison with empirical errors, as determined from differences of the noisy geoid solutions to the noise-free solutions. We find that the error propagations of the methods are realistic in both uncorrelated and correlated noise regimes, albeit only when subjected to careful tuning, such as spectral band limitation and signal covariance adaptation. For the SKs, different implementations of the L-curve and generalized cross-validation methods did not provide an optimal regularization parameter. Although the obtained values led to a stabilized numerical system, this was not necessarily equivalent to obtaining the best solution. Using a regularization parameter governed by the agreement between formal and empirical error fields provided a solution of similar quality to the other methods. The errors in the uncorrelated regime are on the level of ∼5 mm and the method agreement within 1 mm, while the errors in the correlated regime are on the level of ∼10 mm, and the method agreement within 5 mm. Stokes’s formula generally gives the smallest error, closely followed by LSC and the SKs. To this effect, we note that error estimates from integration and estimation techniques must be interpreted differently, because the latter also take the signal characteristics into account. The high level of agreement gives us confidence in the applicability and comparability of formal errors resulting from the three methods. Finally, we present the error characteristics of geoid height differences derived from the three methods and discuss them qualitatively in relation to GNSS leveling. If applied to real data, this would permit identification of spatial scales for which height information is preferably derived by spirit leveling or GNSS leveling. Numéro de notice : A2020-784 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01443-y date de publication en ligne : 27/11/2020 En ligne : https://doi.org/10.1007/s00190-020-01443-y Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96528 [article]

A review of assessment methods for cellular automata models of land-use change and urban growth / Xiaohua Tong in International journal of geographical information science IJGIS, vol 34 n° 5 (May 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 5 (May 2020) . - pp 866 - 898 Titre : A review of assessment methods for cellular automata models of land-use change and urban growth Type de document : Article/Communication Auteurs : Xiaohua Tong, Auteur ; Yongjiu Feng, Auteur Année de publication : 2020 Article en page(s) : pp 866 - 898 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de sensibilité [Termes IGN] analyse du paysage [Termes IGN] automate cellulaire [Termes IGN] changement d'occupation du sol [Termes IGN] croissance urbaine [Termes IGN] dynamique de la végétation [Termes IGN] dynamique spatiale [Termes IGN] Kappa de Cohen [Termes IGN] matrice [Termes IGN] modèle de simulation [Termes IGN] population urbaine [Termes IGN] propagation d'erreur Résumé : (auteur) Cellular automata (CA) models are in growing use for land-use change simulation and future scenario prediction. It is necessary to conduct model assessment that reports the quality of simulation results and how well the models reproduce reliable spatial patterns. Here, we review 347 CA articles published during 1999–2018 identified by a Scholar Google search using ‘cellular automata’, ‘land’ and ‘urban’ as keywords. Our review demonstrates that, during the past two decades, 89% of the publications include model assessment related to dataset, procedure and result using more than ten different methods. Among all methods, cell-by-cell comparison and landscape analysis were most frequently applied in the CA model assessment; specifically, overall accuracy and standard Kappa coefficient respectively rank first and second among all metrics. The end-state assessment is often criticized by modelers because it cannot adequately reflect the modeling ability of CA models. We provide five suggestions to the method selection, aiming to offer a background framework for future method choices as well as urging to focus on the assessment of input data and error propagation, procedure, quantitative and spatial change, and the impact of driving factors. Numéro de notice : A2020-809 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1684499 date de publication en ligne : 05/11/2019 En ligne : https://doi.org/10.1080/13658816.2019.1684499 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94880 [article]

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Progress towards a rigorous error propagation for total least-squares estimates / Burkhard Schaffrin in Journal of applied geodesy, vol 14 n° 2 (April 2020)  

Public [article]  inJournal of applied geodesy > vol 14 n° 2 (April 2020) . - pp 159 – 166 Titre : Progress towards a rigorous error propagation for total least-squares estimates Type de document : Article/Communication Auteurs : Burkhard Schaffrin, Auteur ; Kyle Snow, Auteur Année de publication : 2020 Article en page(s) : pp 159 – 166 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] équation non linéaire [Termes IGN] itération [Termes IGN] linéarisation [Termes IGN] matrice [Termes IGN] mesure de précision [Termes IGN] méthode des moindres carrés [Termes IGN] modèle d'erreur [Termes IGN] propagation d'erreur Résumé : (auteur) After several attempts at a formal derivation of the dispersion matrix for Total Least-Squares (TLS) estimates within an Errors-In-Variables (EIV) Model, here a refined approach is presented that makes rigorous use of the nonlinear normal equations, though assuming a Kronecker product structure for both observational dispersion matrices at this point. In this way, iterative linearization of a model (that can be established as being equivalent to the original EIV-Model) is avoided, which might be preferred since such techniques are based on the last iteration step only and, therefore, produce dispersion matrices for the estimated parameters that are generally too optimistic. Here, the error propagation is based on the (linearized total differential of the) exact nonlinear normal equations, which should lead to more trustworthy measures of precision. Numéro de notice : A2020-216 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2019-0062 date de publication en ligne : 03/04/2020 En ligne : https://doi.org/10.1515/jag-2019-0062 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94909 [article]

Error propagation for the Molodensky G1 term / Jack C. McCubbine in Journal of geodesy, vol 93 n°6 (June 2019)  

Public [article]  inJournal of geodesy > vol 93 n°6 (June 2019) . - pp 889 - 898 Titre : Error propagation for the Molodensky G1 term Type de document : Article/Communication Auteurs : Jack C. McCubbine, Auteur ; Will E. Featherstone, Auteur ; Nicholas J. Brown, Auteur Année de publication : 2019 Article en page(s) : pp 889 - 898 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] anomalie de pesanteur [Termes IGN] Australie [Termes IGN] géoïde gravimétrique [Termes IGN] géoïde local [Termes IGN] hauteur ellipsoïdale [Termes IGN] incertitude de position [Termes IGN] intégrale de Stokes [Termes IGN] modèle numérique de surface [Termes IGN] problème des valeurs limites [Termes IGN] propagation d'erreur [Termes IGN] quasi-géoïde [Termes IGN] transformation de coordonnées Résumé : (auteur) Molodensky G terms are used in the computation of the quasigeoid. We derive error propagation formulas that take into account uncertainties in both the free air gravity anomaly and a digital elevation model. These are applied to generate G1 terms and their errors on a 1″ × 1″ grid over Australia. We use these to produce Molodensky gravity anomaly and accompanying uncertainty grids. These uncertainties have average value of 2 mGal with maximum of 54 mGal. We further calculate a gravimetric quasigeoid model by the remove–compute–restore technique. These Molodensky gravity anomaly uncertainties lead to quasigeoid uncertainties with a mean of 4 mm and maximum of 80 mm when propagated through a deterministically modified Stokes’s integral over an integration cap radius of 0.5°. Numéro de notice : A2019-351 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-1211-6 date de publication en ligne : 09/11/2018 En ligne : https://doi.org/10.1007/s00190-018-1211-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93395 [article]

Uncertainty modeling and analysis of surface area calculation based on a regular grid digital elevation model (DEM) / Chang Li in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 32 n° 9-10 (September - October 2018) . - pp 1837 - 1859 Titre : Uncertainty modeling and analysis of surface area calculation based on a regular grid digital elevation model (DEM) Type de document : Article/Communication Auteurs : Chang Li, Auteur ; Sisi Zhao, Auteur ; Qing Wang, Auteur ; Wenzhong Shi, Auteur Année de publication : 2018 Article en page(s) : pp 1837 - 1859 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] autocorrélation spatiale [Termes IGN] incertitude des données [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle numérique de surface [Termes IGN] propagation d'erreur Résumé : (Auteur) In the field of digital terrain analysis (DTA), the principle and method of uncertainty in surface area calculation (SAC) have not been deeply developed and need to be further studied. This paper considers the uncertainty of data sources from the digital elevation model (DEM) and SAC in DTA to perform the following investigations: (a) truncation error (TE) modeling and analysis, (b) modeling and analysis of SAC propagation error (PE) by using Monte-Carlo simulation techniques and spatial autocorrelation error to simulate DEM uncertainty. The simulation experiments show that (a) without the introduction of the DEM error, higher DEM resolution and lower terrain complexity lead to smaller TE and absolute error (AE); (b) with the introduction of the DEM error, the DEM resolution and terrain complexity influence the AE and standard deviation (SD) of the SAC, but the trends by which the two values change may be not consistent; and (c) the spatial distribution of the introduced random error determines the size and degree of the deviation between the calculated result and the true value of the surface area. This study provides insights regarding the principle and method of uncertainty in SACs in geographic information science (GIScience) and provides guidance to quantify SAC uncertainty. Numéro de notice : A2018-305 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1469136 date de publication en ligne : 04/05/2018 En ligne : https://doi.org/10.1080/13658816.2018.1469136 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90448 [article]

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The effect of acquisition error and level of detail on the accuracy of spatial analyses / Filip Biljecki in Cartography and Geographic Information Science, Vol 45 n° 2 (March 2018)  

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The first Australian gravimetric quasigeoid model with location-specific uncertainty estimates / Will E. Featherstone in Journal of geodesy, vol 92 n° 2 (February 2018)  

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Bayesian statistics and Monte Carlo methods / Karl Rudolf Koch in Journal of geodetic science, vol 8 n° 1 (January 2018)  

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Level of detail in 3D city models / Filip Biljecki (2017)  

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Vision stéréoscopique temps-réel pour la navigation autonome d'un robot en environnement dynamique / Maxime Derome (2017)  

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A measure of average error variance of line features / Eryong Liu in Cartography and Geographic Information Science, Vol 43 n° 4 (September 2016)  

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Propagating uncertainty through individual tree volume model predictions to large-area volume estimates / Ronald E. McRoberts in Annals of Forest Science [en ligne], vol 73 n° 3 (September 2016)  

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Qualité des données géographiques : à propos de la propagation des incertitudes / Gilles Troispoux in Signature, n° 59 (janvier 2016)

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Geometric accuracy analysis model of the ZiYuan-3 satellite without GCPs / Xinming Tang in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 12 (December 2015)

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A novel negative abundance‐oriented hyperspectral unmixing algorithm / Rubén Marrero in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)

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