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A novel nonlinear hyperspectral unmixing approach for images of oil spills at sea / Ying Li in International Journal of Remote Sensing IJRS, vol 41 n°12 (20 - 30 March 2020)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 41 n°12 (20 - 30 March 2020) . - pp 4684 - 4701 Titre : A novel nonlinear hyperspectral unmixing approach for images of oil spills at sea Type de document : Article/Communication Auteurs : Ying Li, Auteur ; Huimin Lu, Auteur ; Zhenduo Zhang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 4684 - 4701 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse des mélanges spectraux [Termes descripteurs IGN] équation polynomiale [Termes descripteurs IGN] hydrocarbure [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] marée noire [Termes descripteurs IGN] modèle non linéaire [Termes descripteurs IGN] pollution des mers [Termes descripteurs IGN] trigonométrie Résumé : (auteur) Hyperspectral remote sensing is currently being used to detect and monitor marine oil spills that cause damage to the environment. However, nonlinear interactions of oil and water make it difficult to extract their fractional abundances from the spectral response. Improving the modelling of nonlinear hyperspectral mixtures, which is required for a thorough and reliable characterization of the materials in an image, remains a challenging yet fundamental task. This study proposes a new model that combines polynomial and trigonometric systems to understand the nonlinear effects of oil and water spectral response. Although the model is nonlinear, unmixing is performed by solving a linear problem, thus allowing fast computation. Compared to classic polynomial models, the details of nonlinear interactions are better expressed and quantified, and the reconstruction accuracy and endmember abundance estimation are improved for both synthetic and real datasets. Both the polynomial and trigonometric parts of the model play important roles in characterizing nonlinearities, with statistically linear dependence areas covering more than 90% and 30%, respectively, in oil spill images sampled after the Deepwater Horizon explosion. Analysis of the experimental results suggests that the proposed model provides an efficient and accurate unmixing method that can be used to help design oil spill response plans. Numéro de notice : A2020-452 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431161.2020.1723179 date de publication en ligne : 27/02/2020 En ligne : https://doi.org/10.1080/01431161.2020.1723179 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95540 [article]

Estimating wheat yields in Australia using climate records, satellite image time series and machine learning methods / Elisa Kamir in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 160 (February 2020) . - pp 124 - 135 Titre : Estimating wheat yields in Australia using climate records, satellite image time series and machine learning methods Type de document : Article/Communication Auteurs : Elisa Kamir, Auteur ; François Waldner, Auteur ; Zvi Hochman, Auteur Année de publication : 2020 Article en page(s) : pp 124 - 135 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] Australie [Termes descripteurs IGN] blé (céréale) [Termes descripteurs IGN] carte agricole [Termes descripteurs IGN] climat [Termes descripteurs IGN] estimation de précision [Termes descripteurs IGN] fonction de base radiale [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] modèle non linéaire [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] régression [Termes descripteurs IGN] rendement agricole [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] variation saisonnière Résumé : (Auteur) Closing the yield gap between actual and potential wheat yields in Australia is important to meet the growing global demand for food. The identification of hotspots of the yield gap, where the potential for improvement is the greatest, is a necessary step towards this goal. While crop growth models are well suited to quantify potential yields, they lack the ability to provide accurate large-scale estimates of actual yields, owing to the sheer quantity of data they require for parameterisation. In this context, we sought to provide accurate estimates of actual wheat yields across the Australian wheat belt based on machine-learning regression methods, climate records and satellite image time series. Out of nine base learners and two ensembles, support vector regression with radial basis function emerged as the single best learner (root mean square error of 0.55 t ha−1 and R2 of 0.77 at the pixel level). At national scale, this model explained 73% of the yield variability observed across statistical units. Benchmark approaches based on peak Normalised Difference Vegetation Index (NDVI) and on a harvest index were largely outperformed by the machine-learning regression models (R2  Numéro de notice : A2020-046 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.11.008 date de publication en ligne : 20/12/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.11.008 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94556 [article]

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Innovative techniques of photogrammetry for 3D modeling / Vicenzo Barrile in Applied geomatics, Vol 11 n° 4 (December 2019)  

Public [article]  inApplied geomatics > Vol 11 n° 4 (December 2019) . - pp 353–369 Titre : Innovative techniques of photogrammetry for 3D modeling Type de document : Article/Communication Auteurs : Vicenzo Barrile, Auteur ; Alice Pozzoli, Auteur ; Giuliana Bilotta, Auteur ; Antonino Fotia, Auteur Année de publication : 2019 Article en page(s) : pp 353–369 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie analytique [Termes descripteurs IGN] Italie [Termes descripteurs IGN] modèle non linéaire [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] orientation absolue [Termes descripteurs IGN] orientation automatique [Termes descripteurs IGN] orientation relative [Termes descripteurs IGN] Raspberry Pi [Termes descripteurs IGN] reconstruction d'image [Termes descripteurs IGN] structure-from-motion [Termes descripteurs IGN] vision par ordinateur Résumé : (auteur) This note presents the experimental results deriving from the application of two innovative photogrammetric techniques (with particular reference to non-conventional photogrammetric applications) for the production of time-space 3D models of the marine surface. Moreover, the first method (automatic three images processing (ATIP)) proposes some easy procedures to solve typical non-linear problems of analytical photogrammetry. In particular, once validated the technique of orientation of two images (two-step procedure based on two phases: relative orientation and absolute orientation, both characterized by non-linear functions), we propose a procedure for the automatic orientation of three images (the introduction of a third image allows avoiding human decision to find the final solution). The second method (Computer Vision Raspberry Pi—CVR) refers to the use of the “prompt” technique of computer vision (structure from motion) using five appropriately synchronized cameras to acquire simultaneously the various frames, thanks to the use of an acquisition system based on the use of Raspberry Pi. The experimentation was conducted both in the laboratory (on a model that allows to study a typical phenomenon of the Alpine Valtellina region, in the North of Italy) that directly at sea (on a portion of marine surface located in Reggio Calabria near the seafront). The results obtained show a substantial comparability of the results both between the two methods and with the actual data measured at sea with dedicated instrumentation. Numéro de notice : A2019-533 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-019-00264-9 date de publication en ligne : 22/05/2019 En ligne : https://doi.org/10.1007/s12518-019-00264-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94126 [article]

Robust M–M unscented Kalman filtering for GPS/IMU navigation / Cheng Yang in Journal of geodesy, vol 93 n° 8 (August 2019)  

Public [article]  inJournal of geodesy > vol 93 n° 8 (August 2019) . - pp 1093 - 1104 Titre : Robust M–M unscented Kalman filtering for GPS/IMU navigation Type de document : Article/Communication Auteurs : Cheng Yang, Auteur ; Wenzhong Shi, Auteur ; Wu Chen, Auteur Année de publication : 2019 Article en page(s) : pp 1093 - 1104 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] coefficient de corrélation [Termes descripteurs IGN] erreur de mesure [Termes descripteurs IGN] erreur de modèle [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] GNSS-INS [Termes descripteurs IGN] matrice de covariance [Termes descripteurs IGN] méthode du maximum de vraisemblance (estimation) [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] modèle non linéaire Résumé : (auteur) In this paper, a robust unscented Kalman filter (UKF) based on the generalized maximum likelihood estimation (M-estimation) is proposed to improve the robustness of the integrated navigation system of Global Navigation Satellite System and Inertial Measurement Unit. The UKF is a variation of Kalman filter by which the Jacobian matrix calculation in a nonlinear system state model is not necessary. The proposed robust M–M unscented Kalman filter (RMUKF) applies the M-estimation principle to both functional model errors and measurement errors. Hence, this robust filter attenuates the influences of disturbances in the dynamic model and of measurement outliers without linearizing the nonlinear state space model. In addition, an equivalent weight matrix, composed of the bi-factor shrink elements, is proposed in order to keep the original correlation coefficients of the predicted state unchanged. Furthermore, a nonlinear error model is used as the dynamic equation to verify the performance of the proposed RMUKF with a simulation and field test. Compared with the conventional UKF, the impacts of measurement outliers and system disturbances on the state estimation are both controlled by RMUKF. Numéro de notice : A2019-370 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-01227-5 date de publication en ligne : 22/01/2019 En ligne : https://doi.org/10.1007/s00190-018-01227-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93455 [article]

Scale effect in indirect measurement of leaf area index / Guangjian Yan in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 6 (June 2016) . - pp 3475 - 3484 Titre : Scale effect in indirect measurement of leaf area index Type de document : Article/Communication Auteurs : Guangjian Yan, Auteur ; Ronghai Hu, Auteur ; Yiting Wang, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 3475 - 3484 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] indice foliaire [Termes descripteurs IGN] longueur [Termes descripteurs IGN] mesure optique [Termes descripteurs IGN] méthode de mesure [Termes descripteurs IGN] modèle non linéaire [Termes descripteurs IGN] surface hétérogène Résumé : (Auteur) Scale effect, which is caused by a combination of model nonlinearity and surface heterogeneity, has been of interest to the remote sensing community for decades. However, there is no current analysis of scale effect in the ground-based indirect measurement of leaf area index (LAI), where model nonlinearity and surface heterogeneity also exist. This paper examines the scale effect on the indirect measurement of LAI. We built multiscale data sets based on realistic scenes and field measurements. We then implemented five representative methods of indirect LAI measurement at scales (segment lengths) that range from meters to hundreds of meters. The results show varying degrees of deviation and fluctuation that exist in all five methods when the segment length is shorter than 20 m. The retrieved LAI from either Beer's law or the gap-size distribution method shows a decreasing trend with increasing segment lengths. The length at which the LAI values begin to stabilize is about a full period of row in row crops and 100 m in broadleaf or coniferous forests. The impacts of segment length on the finite-length averaging method, the combination of gap-size distribution and finite-length methods, and the path-length distribution method are relatively small. These three methods stabilize at the segment scale longer than 20 m in all scenes. We also find that computing the average LAI of all of the short segment lengths, which is commonly done, is not as good as merging these short segments into a longer one and computing the LAI value of the merged one. Numéro de notice : A2016-856 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1109/TGRS.2016.2519098 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82995 [article]

Eléments de géodésie et de la théorie des moindres carrés / Abdelmajid Ben Hadj Salem (février 2016) 

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Weighted total least squares for solving non-linear problem: GNSS point positioning / S. Jazaeri in Survey review, vol 47 n° 343 (July 2015)  

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LASSO-type estimators for semiparametric nonlinear mixed-effects models estimation / Ana Arribas-Gil in Statistics and Computing, vol 24 n° 3 (May 2014)  

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Nonlinear unmixing of hyperspectral data using semi-nonnegative matrix factorization / Naoto Yokoya in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)  

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Bayesian and frequentist regression methods / Jon Wakefield (2013)  

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Diameter and death of whorl and interwhorl branches in Atlas cedar (Cedrus atlantica Manetti): a model accounting for acrotony / François Courbet in Annals of Forest Science, Vol 69 n° 2 (March 2012)  

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Modelos armonicos no lineales para series temporales geodéticas = Non-linear harmonic models for geodetic time series / P.A. Martinez-Ortiz (2011)

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Automated derivation of bathymetric information from multi-spectral satellite imagery using a non-linear inversion model / H. Su in Marine geodesy, vol 31 n° 4 (December 2008)

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A quaternion-based geodetic datum transformation algorithm / Y.Z. Shen in Journal of geodesy, vol 80 n° 5 (August 2006)

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Modélisation des tissus adipeux et traitement d'images IRM / I. Leonard (2001)

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