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A local projection for integrating geodetic and terrestrial coordinate systems / Mike Bremmer in Survey review, vol 52 n° 374 (August 2020)  

Public [article]  inSurvey review > vol 52 n° 374 (August 2020) . - pp 394 - 402 Titre : A local projection for integrating geodetic and terrestrial coordinate systems Type de document : Article/Communication Auteurs : Mike Bremmer, Auteur ; Marcelo Santos, Auteur Année de publication : 2020 Article en page(s) : pp 394 - 402 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Projections [Termes descripteurs IGN] coordonnées cartésiennes géocentriques [Termes descripteurs IGN] coordonnées géodésiques [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] géodésie terrestre [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] projection [Termes descripteurs IGN] projection stéréographique [Termes descripteurs IGN] système de coordonnées Résumé : (auteur) This paper develops a system for projecting coordinates from a geocentric coordinate system to a topocentric coordinate system defined by terrestrial measurements. The proposed system uses an extension of the Stereographic Double Map Projection and a parametric least squares estimation to calculate the parameters for the map projection. The Extended Stereographic Double Projection and the projection parameter estimation are implemented and tested. Tests are performed to determine rate that discrepancies occur and the maximum extents of the Extended Stereographic Double Projection. This maximum area is determined to be ∼10 km2 with RMS values of residuals of 0.0029 m in northing and 0.0020 m in easting. Tests are also performed to determine the factor that limits the effective area of the Projection. Numéro de notice : A2020-516 Thématique : GEOMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1597490 date de publication en ligne : 08/04/2019 En ligne : https://doi.org/10.1080/00396265.2019.1597490 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95676 [article]

A robust total Kalman filter algorithm with numerical evaluation / Sida Li in Survey review, vol 52 n° 373 (July 2020)  

Public [article]  inSurvey review > vol 52 n° 373 (July 2020) . - pp 309 - 316 Titre : A robust total Kalman filter algorithm with numerical evaluation Type de document : Article/Communication Auteurs : Sida Li, Auteur ; Lintao Liu, Auteur ; Zhiping Liu, Auteur ; Guocheng Wang, Auteur Année de publication : 2020 Article en page(s) : pp 309 - 316 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] matrice [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] modèle d'erreur [Termes descripteurs IGN] précision du positionnement [Termes descripteurs IGN] valeur aberrante Résumé : (auteur) In this study, the observation model of Kalman Filter (KF) is extended to an errors-in-variables (EIV) model because the observations may exist in the design matrix of the observation model. Then, a robust total least squares method (RTLS) is introduced into the KF, and a robust total Kalman filter (RTKF) algorithm is derived. The RTKF is a simple, flexible and effective algorithm. It is simple because its computational formulae are similar to the computational formulae of a standard KF; it is flexible because it can be used in a wide range of applications; it is effective because the influence of outliers on estimated results is weakened. Finally, the simulated example of the indoor location and the empirical example of pseudorange differential positioning are used to demonstrate the performance of the RTKF algorithm. The results prove the validity, robustness, and reliability of the RTKF in dealing with the outliers that exist in both observation vector and design matrix of the EIV model. Furthermore, the results of the empirical example show that the RTKF improves the precision of a pseudorange differential positioning compared with KF and robust Kalman filter (RKF) algorithms regardless the observation model has outliers or not in this empirical example. Numéro de notice : A2020-457 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1563392 date de publication en ligne : 08/01/2019 En ligne : https://doi.org/10.1080/00396265.2018.1563392 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95556 [article]

Discriminant analysis for lodging severity classification in wheat using RADARSAT-2 and Sentinel-1 data / Sugandh Chauhan in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 138 - 151 Titre : Discriminant analysis for lodging severity classification in wheat using RADARSAT-2 and Sentinel-1 data Type de document : Article/Communication Auteurs : Sugandh Chauhan, Auteur ; Roshanak Darvishzadeh, Auteur ; Mirco Boschetti, Auteur ; Andrew Nelson, Auteur Année de publication : 2020 Article en page(s) : pp 138 - 151 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] agrégation [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] analyse discriminante [Termes descripteurs IGN] blé (céréale) [Termes descripteurs IGN] courbure [Termes descripteurs IGN] gestion prévisionnelle [Termes descripteurs IGN] image Radarsat [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] Italie [Termes descripteurs IGN] matrice de confusion [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] rendement agricole [Termes descripteurs IGN] surveillance agricole Résumé : (auteur) Crop lodging - the bending of crop stems from their upright position or the failure of root-soil anchorage systems - is a major yield-reducing factor in wheat and causes deterioration of grain quality. The severity of lodging can be measured by a lodging score (LS)- an index calculated from the crop angle of inclination (CAI) and crop lodged area (LA). LS is difficult and time consuming to measure manually meaning that information on lodging occurrence and severity is limited and sparse. Remote sensing-based estimates of LS can provide more timely, synoptic and reliable information on crop lodging across vast areas. This information could improve estimates of crop yield losses, inform insurance loss adjusters and influence management decisions for subsequent seasons. This research - conducted in the 600 ha wheat sown area in the Bonifiche Ferraresi farm, located in Jolanda di Savoia, Ferrara, Italy - evaluated the performance of RADARSAT-2 and Sentinel-1 data to discriminate and classify lodging severity based on field measured LS. We measured temporal crop status characteristics related to lodging (e.g. lodged area, CAI, crop height) and collected relevant meteorological data (wind speed and rainfall) throughout May-June 2018. These field measurements were used to distinguish healthy (He) wheat from lodged wheat with different degrees of lodging severity (moderate, severe and very severe). We acquired multi-incidence angle (FQ8-27° and FQ21-41°) RADARSAT-2 and Sentinel-1 (40°) images and derived multiple metrics from them to discriminate and classify lodging severity. As a part of our data exploration, we performed a correlation analysis between the image-based metrics and LS. Next, a multi-temporal discriminant analysis approach, including a partial least squares (PLS-DA) method, was developed to classify lodging severities. We used the area under the curve-receiver operating characteristics (AUC-ROC) and confusion matrices to evaluate the accuracy of the PLS-DA classification models. Results show that (1) volume scattering components were highly correlated with LS at low incidence angles while double and surface scattering was more prevalent at high incidence angles; (2) lodging severity was best classified using low incidence angle R-FQ8 data (overall accuracy 72%) and (3) the Sentinel-1 data-based classification model was able to correctly identify 60% of the lodging severity cases in the study site. The results from this first study on classifying lodging severity using satellite-based SAR platforms suggests that SAR-based metrics can capture a substantial proportion of the observed variation in lodging severity, which is important in the context of operational crop lodging assessment in particular, and sustainable agriculture in general. Numéro de notice : A2020-276 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.04.012 date de publication en ligne : 29/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.04.012 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95087 [article]

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Modelling housing rents using spatial autoregressive geographically weighted regression: a case study in cracow, Poland / Mateusz Tomal in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 20 p. Titre : Modelling housing rents using spatial autoregressive geographically weighted regression: a case study in cracow, Poland Type de document : Article/Communication Auteurs : Mateusz Tomal, Auteur Année de publication : 2020 Article en page(s) : 20 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] autorégression [Termes descripteurs IGN] bien immobilier [Termes descripteurs IGN] Cracovie (Pologne) [Termes descripteurs IGN] distribution spatiale [Termes descripteurs IGN] économétrie [Termes descripteurs IGN] évaluation foncière [Termes descripteurs IGN] gestion foncière [Termes descripteurs IGN] hétérogénéité spatiale [Termes descripteurs IGN] méthode de Monte-Carlo [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] régression géographiquement pondérée Résumé : (auteur) The proportion of tenants will undoubtedly rise in Poland, where at present, the ownership housing model is very dominant. As a result, the rental housing market in Poland is currently under-researched in comparison with owner-occupancy. In order to narrow this research gap, this study attempts to identify the determinants affecting rental prices in Cracow. The latter were obtained from the internet platform otodom.pl using the web scraping technique. To identify rent determinants, ordinary least squares (OLS) regression and spatial econometric methods were used. In particular, traditional spatial autoregressive model (SAR) and spatial autoregressive geographically weighted regression (GWR-SAR) were employed, which made it possible to take into account the spatial heterogeneity of the parameters of determinants and the spatially changing spatial autocorrelation of housing rents. In-depth analysis of rent determinants using the GWR-SAR model exposed the complexity of the rental market in Cracow. Estimates of the above model revealed that many local markets can be identified in Cracow, with different factors shaping housing rents. However, one can identify some determinants that are ubiquitous for almost the entire city. This concerns mainly the variables describing the area of the flat and the age of the building. Moreover, the Monte Carlo test indicated that the spatial autoregressive parameter also changes significantly over space. Numéro de notice : A2020-314 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060346 date de publication en ligne : 26/05/2020 En ligne : https://doi.org/10.3390/ijgi9060346 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95169 [article]

An integrated approach to registration and fusion of hyperspectral and multispectral images / Yuan Zhou in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 5 (May 2020) . - pp 3020 - 3033 Titre : An integrated approach to registration and fusion of hyperspectral and multispectral images Type de document : Article/Communication Auteurs : Yuan Zhou, Auteur ; Anand Rangarajan, Auteur ; Paul D. Gader, Auteur Année de publication : 2020 Article en page(s) : pp 3020 - 3033 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] algorithme de fusion [Termes descripteurs IGN] distorsion d'image [Termes descripteurs IGN] fusion d'images [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] points registration [Termes descripteurs IGN] tâche image d'un point Résumé : (auteur) Combining a hyperspectral (HS) image and a multispectral (MS) image—an example of image fusion—can result in a spatially and spectrally high-resolution image. Despite the plethora of fusion algorithms in remote sensing, a necessary prerequisite, namely registration, is mostly ignored. This limits their application to well-registered images from the same source. In this article, we propose and validate an integrated registration and fusion approach (code available at https://github.com/zhouyuanzxcv/Hyperspectral ). The registration algorithm minimizes a least-squares (LSQ) objective function with the point spread function (PSF) incorporated together with a nonrigid freeform transformation applied to the HS image and a rigid transformation applied to the MS image. It can handle images with significant scale differences and spatial distortion. The fusion algorithm takes the full high-resolution HS image as an unknown in the objective function. Assuming that the pixels lie on a low-dimensional manifold invariant to local linear transformations from spectral degradation, the fusion optimization problem leads to a closed-form solution. The method was validated on the Pavia University, Salton Sea, and the Mississippi Gulfport datasets. When the proposed registration algorithm is compared to its rigid variant and two mutual information-based methods, it has the best accuracy for both the nonrigid simulated dataset and the real dataset, with an average error less than 0.15 pixels for nonrigid distortion of maximum 1 HS pixel. When the fusion algorithm is compared with current state-of-the-art algorithms, it has the best performance on images with registration errors as well as on simulations that do not consider registration effects. Numéro de notice : A2020-231 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2941494 date de publication en ligne : 12/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2941494 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94969 [article]

Fusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method / Yuedong Wang in Journal of geodesy, vol 94 n° 5 (May 2020)  

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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)  

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A single-receiver geometry-free approach to stochastic modeling of multi-frequency GNSS observables / Baocheng Zhang in Journal of geodesy, vol 94 n°4 (April 2020)  

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The impact of second-order ionospheric delays on the ZWD estimation with GPS and BDS measurements / Shaocheng Zhang in GPS solutions, vol 24 n° 2 (April 2020)  

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Mapping precipitable water vapor time series from Sentinel-1 interferometric SAR / Pedro Mateus in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)  

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Postprocessing synchronization of a laser scanning system aboard a UAV / Marcela do Valle Machado in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 10 (October 2019)  

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On the application of Monte Carlo singular spectrum analysis to GPS position time series / Seyed Mohsen Khazraei in Journal of geodesy, vol 93 n° 9 (September 2019)  

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Sea level prediction in the Yellow Sea from satellite altimetry with a combined least squares-neural network approach / Jian Zhao in Marine geodesy, vol 42 n° 4 (July 2019)  

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Demonstrating the transferability of forest inventory attribute models derived using airborne laser scanning data / Piotr Tompalski in Remote sensing of environment, vol 227 (15 June 2019)  

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Helmert-VCE-aided fast-WTLS approach for global ionospheric VTEC modelling using data from GNSS, satellite altimetry and radio occultation / Andong Hu in Journal of geodesy, vol 93 n°6 (June 2019)  

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