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Performance analysis of BDS/GPS precise point positioning with undifferenced ambiguity resolution / Min Wang in Advances in space research, vol 60 n° 12 (15 December 2017)
[article]
Titre : Performance analysis of BDS/GPS precise point positioning with undifferenced ambiguity resolution Type de document : Article/Communication Auteurs : Min Wang, Auteur ; Hongzhou Chai, Auteur ; Yu Li, Auteur Année de publication : 2017 Article en page(s) : pp 2581 - 2595 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] données BeiDou
[Termes IGN] données GPS
[Termes IGN] erreur systématique
[Termes IGN] méthode des moindres carrés
[Termes IGN] positionnement ponctuel précis
[Termes IGN] résolution d'ambiguïtéRésumé : (auteur) The undifferenced ambiguity resolution has been proved to be an effective method to shorten the initialization of precise point positioning (PPP) solution and improve the positioning accuracy. Several techniques were proposed for undifferenced ambiguity resolution with GPS observations. However, for BeiDou navigation satellite system (BDS), the satellite-induced variation in pseudorange observation changes the characteristics of Melbourne-Wűbbena (MW) combination observation, which leads to unacceptably low fixing rate of undifferenced ambiguity. Besides, the characteristics of satellite-induced variations in BDS observations vary with orbit type of satellite, which should be considered in correction effort. In this paper, the BDS fractional cycle biases (FCBs) are estimated with least-squares estimation method using the float undifferenced ambiguity collected from the network of reference stations. Based on the analysis of weekly stability of widelane FCBs and the distribution of fractional ambiguity parts, it is proven that the satellite-induced variation correction is necessary for the FCB estimation for IGSO and MEO satellites. Contaminated by relatively large orbit error, the ambiguities of GEO satellites should be skipped for ambiguity resolution attempt. Resolving BDS ambiguities in BDS/GPS combined PPP could significantly shorten the time needed for the first correct ambiguity resolution (FCAR). The experiment results of static PPP demonstrate that 90.6% of all sessions accomplish FCAR within 1350 s with only GPS observations. Meanwhile, by adding BDS ambiguities to the subset of ambiguity resolution, 91.9% of all sessions accomplish FCAR with only 870 s. Numéro de notice : A2017-752 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.asr.2017.01.045 En ligne : https://doi.org/10.1016/j.asr.2017.01.045 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89037
in Advances in space research > vol 60 n° 12 (15 December 2017) . - pp 2581 - 2595[article]Above-bottom biomass retrieval of aquatic plants with regression models and SfM data acquired by a UAV platform – A case study in Wild Duck Lake Wetland, Beijing, China / Ran Jing in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)
[article]
Titre : Above-bottom biomass retrieval of aquatic plants with regression models and SfM data acquired by a UAV platform – A case study in Wild Duck Lake Wetland, Beijing, China Type de document : Article/Communication Auteurs : Ran Jing, Auteur ; Zhaoning Gong, Auteur ; Wenji Zhao, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 122 - 134 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] arbre de décision
[Termes IGN] biomasse
[Termes IGN] croissance végétale
[Termes IGN] drone
[Termes IGN] image aérienne
[Termes IGN] indice de végétation
[Termes IGN] lac
[Termes IGN] macrophyte
[Termes IGN] modèle de régression
[Termes IGN] orthoimage
[Termes IGN] Pékin (Chine)
[Termes IGN] régression linéaire
[Termes IGN] semis de points
[Termes IGN] structure-from-motion
[Termes IGN] zone humideRésumé : (Auteur) Above-bottom biomass (ABB) is considered as an important parameter for measuring the growth status of aquatic plants, and is of great significance for assessing health status of wetland ecosystems. In this study, Structure from Motion (SfM) technique was used to rebuild the study area with high overlapped images acquired by an unmanned aerial vehicle (UAV). We generated orthoimages and SfM dense point cloud data, from which vegetation indices (VIs) and SfM point cloud variables including average height (HAVG), standard deviation of height (HSD) and coefficient of variation of height (HCV) were extracted. These VIs and SfM point cloud variables could effectively characterize the growth status of aquatic plants, and thus they could be used to develop a simple linear regression model (SLR) and a stepwise linear regression model (SWL) with field measured ABB samples of aquatic plants. We also utilized a decision tree method to discriminate different types of aquatic plants. The experimental results indicated that (1) the SfM technique could effectively process high overlapped UAV images and thus be suitable for the reconstruction of fine texture feature of aquatic plant canopy structure; and (2) an SWL model based on point cloud variables: HAVG, HSD, HCV and two VIs: NGRDI, ExGR as independent variables has produced the best predictive result of ABB of aquatic plants in the study area, with a coefficient of determination of 0.84 and a relative root mean square error of 7.13%. In this analysis, a novel method for the quantitative inversion of a growth parameter (i.e., ABB) of aquatic plants in wetlands was demonstrated. Numéro de notice : A2017-732 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.11.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.11.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88431
in ISPRS Journal of photogrammetry and remote sensing > vol 134 (December 2017) . - pp 122 - 134[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017121 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017122 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017123 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt Area-based estimation of growing stock volume in Scots pine stands using ALS and airborne image-based point clouds / Paweł Hawryło in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)
[article]
Titre : Area-based estimation of growing stock volume in Scots pine stands using ALS and airborne image-based point clouds Type de document : Article/Communication Auteurs : Paweł Hawryło, Auteur ; Piotr Tompalski, Auteur ; Piotr Wezyk, Auteur Année de publication : 2017 Article en page(s) : pp 686 - 696 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image aérienne
[Termes IGN] image infrarouge couleur
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Pinus sylvestris
[Termes IGN] régression linéaire
[Termes IGN] régression multiple
[Termes IGN] semis de points
[Termes IGN] volume en bois
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Recent research has shown that image-derived point clouds (IPCs) are a highly competitive alternative to airborne laser scanning (ALS) data in the context of selected forest inventory activities. However, there is still a need for investigating different kinds of aerial images used for point cloud generation. This study compares the effectiveness of IPCs derived from true colour (RGB) and colour infrared (CIR) aerial images with ALS data for growing stock volume estimation of single canopy layer Scots pine stands. A multiple linear regression method was used to create predictive models. All models predicted growing stock volume with low root mean square errors – ALS: 15.2%, IPC-CIR: 17.0% and IPC-RGB: 17.5%. The following variables for each data type were found to be the most robust: ALS – mean height of points, percentage of all returns above mean height of points, interquartile range of point heights; IPC-CIR – mean height of points, percentage of all returns above mode height of points, canopy relief ratio; IPC-RGB – mean height of points and canopy relief ratio. Our results show that for single canopy layer Scots pine dominated stands it is possible to predict growing stock volume using IPCs with a comparable accuracy as using ALS data. The comparable performance of IPC-RGB and IPC-CIR based models suggests that a mixed usage of RGB and CIR data in retrospective studies could be possible. Numéro de notice : A2017-904 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx026 En ligne : https://doi.org/10.1093/forestry/cpx026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93205
in Forestry, an international journal of forest research > vol 90 n° 5 (December 2017) . - pp 686 - 696[article]Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery / Jose Alan A. Castillo in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)
[article]
Titre : Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery Type de document : Article/Communication Auteurs : Jose Alan A. Castillo, Auteur ; Armando A. Apan, Auteur ; Tek N. Maraseni, Auteur ; Severino G. Salmo, Auteur Année de publication : 2017 Article en page(s) : pp 70 - 85 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] biomasse aérienne
[Termes IGN] carte d'utilisation du sol
[Termes IGN] déboisement
[Termes IGN] estimation statistique
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] indice de végétation
[Termes IGN] mangrove
[Termes IGN] modèle de simulation
[Termes IGN] Philippines
[Termes IGN] régression linéaire
[Termes IGN] rétrodiffusion
[Termes IGN] variable biophysique (végétation)Résumé : (Auteur) The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82–0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8–28.5 Mg ha−1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement non-forest land uses, especially with the inclusion of elevation data. The study demonstrates encouraging results in biomass mapping of mangroves and other coastal land uses in the tropics using the freely accessible and relatively high-resolution Sentinel imagery. Numéro de notice : A2017-730 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.10.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.10.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88428
in ISPRS Journal of photogrammetry and remote sensing > vol 134 (December 2017) . - pp 70 - 85[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017121 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017122 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017123 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt Efficient weighted total least-squares solution for partial errors-in-variables model / J. Zhao in Survey review, vol 49 n° 356 (November 2017)
[article]
Titre : Efficient weighted total least-squares solution for partial errors-in-variables model Type de document : Article/Communication Auteurs : J. Zhao, Auteur Année de publication : 2017 Article en page(s) : pp 346 - 354 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] itération
[Termes IGN] méthode des moindres carrésRésumé : (Auteur) Due to great computation burden of the original computational formula for partial errors-in-variables (EIV), an alternative formula for parameter estimation in the partial EIV model was proposed to promote computational efficiency. Unfortunately, more iteration is required for obtaining the weighted total least-squares (WTLS) solution of the partial EIV model with above two formulae. Consequently, those methods are not proper for larger data problem in terms of computational efficiency. To circumvent this difficulty, a new formula and the fast algorithm are proposed based on the Lagrange extreme value method. Through some numerical examples with coordinate transformation, it is illustrated that the new developed method is an effective strategy to conduct the WTLS adjustment for the partial EIV model. The computational efficiency is significantly improved at least 80%. Numéro de notice : A2017-556 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/00396265.2016.1173329 En ligne : https://doi.org/10.1080/00396265.2016.1180753 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86617
in Survey review > vol 49 n° 356 (November 2017) . - pp 346 - 354[article]Incidence angle dependence of first-year sea ice backscattering coefficient in Sentinel-1 SAR Imagery over the kara sea / Marko P. Mäkynen in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)PermalinkRemote sensing of species diversity using Landsat 8 spectral variables / Sabelo Madonsela in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)PermalinkThe Naïve Overfitting Index Selection (NOIS): A new method to optimize model complexity for hyperspectral data / Alby D. Rocha in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)PermalinkWeighted coordinate transformation formulated by standard least-squares theory / D. Mihajlovic in Survey review, vol 49 n° 356 (November 2017)PermalinkHyperspectral dimensionality reduction for biophysical variable statistical retrieval / Juan Pablo Rivera-Caicedo in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)PermalinkStand-volume estimation from multi-source data for coppiced and high forest Eucalyptus spp. silvicultural systems in KwaZulu-Natal, South Africa / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)PermalinkMulti-dimensional and multi-temporal motion estimation of a beam surface during dynamic testing using low-frame rate digital cameras / I. Detchev in Applied geomatics, vol 9 n° 3 (September 2017)PermalinkA robust weighted total least-squares solution with Lagrange multipliers / X. Gong in Survey review, vol 49 n° 354 (September 2017)PermalinkA Stepwise-Then-Orthogonal Regression (STOR) with quality control for optimizing the RFM of high-resolution satellite imagery / Chang Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 9 (September 2017)PermalinkFusing tree‐ring and forest inventory data to infer influences on tree growth / Margaret E.K. Evans in Ecosphere, vol 8 n° 7 (July 2017)Permalink