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Geometric modelling and calibration of a spherical camera imaging system / Derek D. Lichti in Photogrammetric record, vol 35 n° 170 (June 2020)
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Titre : Geometric modelling and calibration of a spherical camera imaging system Type de document : Article/Communication Auteurs : Derek D. Lichti, Auteur ; David Jarron, Auteur ; Wynand Tredoux, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 123 - 142 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] acquisition d'images
[Termes IGN] auto-étalonnage
[Termes IGN] caméra 3D
[Termes IGN] colinéarité
[Termes IGN] distorsion radiale
[Termes IGN] instrument de photogrammétrie
[Termes IGN] modélisation géométrique de prise de vue
[Termes IGN] orientation relative
[Termes IGN] reconstruction 3D
[Termes IGN] système de numérisation mobileRésumé : (auteur) The Ladybug5 is an integrated, multi‐camera system that features a near‐spherical field of view. It is commonly deployed on mobile mapping systems to collect imagery for 3D reality capture. This paper describes an approach for the geometric modelling and self‐calibration of this system. The collinearity equations of the pinhole camera model are augmented with five radial lens distortion terms to correct the severe barrel distortion. Weighted relative orientation stability constraints are added to the self‐calibrating bundle adjustment solution to enforce the angular and positional stability between the Ladybug5’s six cameras. Centimetre‐level 3D reconstruction accuracy can be achieved, with image‐space precision and object‐space accuracy improved by 92% and 93% , respectively, relative to a two‐term lens distortion model. Sub‐pixel interior orientation stability and millimetre‐level relative orientation stability were also demonstrated over a 10‐month period. Numéro de notice : A2020-401 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12315 Date de publication en ligne : 29/06/2020 En ligne : https://doi.org/10.1111/phor.12315 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95438
in Photogrammetric record > vol 35 n° 170 (June 2020) . - pp 123 - 142[article]Hyperspectral classification with noisy label detection via superpixel-to-pixel weighting distance / Bing Tu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)
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Titre : Hyperspectral classification with noisy label detection via superpixel-to-pixel weighting distance Type de document : Article/Communication Auteurs : Bing Tu, Auteur ; Chengle Zhou, Auteur ; Danbing He, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 4116 - 4131 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] classification barycentrique
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données étiquetées d'entrainement
[Termes IGN] erreur d'échantillon
[Termes IGN] image hyperspectrale
[Termes IGN] pondération
[Termes IGN] précision de la classification
[Termes IGN] superpixelRésumé : (auteur) Classification is an important technique for remotely sensed hyperspectral image (HSI) exploitation. Often, the presence of wrong (noisy) labels presents a drawback for accurate supervised classification. In this article, we introduce a new framework for noisy label detection that combines a superpixel-to-pixel weighting distance (SPWD) and density peak clustering. The proposed method is able to accurately detect and remove noisy labels in the training set before HSI classification. It considers two weak assumptions when exploiting the spectral–spatial information contained in the HSI: 1) all the pixels in a superpixel belong to the same class and 2) close pixels in spectral space have the same label. The proposed method consists of the following steps. First, a superpixel segmentation step is used to obtain self-adaptive spatial information for each training sample. Then, a metric is utilized to measure the spectral distance information between each superpixel and pixel. Meanwhile, in order to overcome the first weak assumption, we use K nearest neighbors to obtain the closest neighborhoods of pixels around each superpixel, and a Gaussian weight is employed to mitigate the second weak assumption by adapting the original distance information. Next, the noisy labels in the original training set are removed by a density threshold-based decision function. Finally, the support vector machine (SVM) classifier is employed to evaluate the effectiveness of the proposed SPWD detection method in terms of classification accuracy. Experiments performed on several real HSI data sets demonstrate that the method can effectively improve the performance of classifiers trained with noisy training sets in terms of classification accuracy. Numéro de notice : A2020-283 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2961141 Date de publication en ligne : 13/01/2020 En ligne : https://doi.org/10.1109/TGRS.2019.2961141 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95105
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 6 (June 2020) . - pp 4116 - 4131[article]Improved SMAP dual-channel algorithm for the retrieval of soil moisture / Mario Julian Chaubell in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)
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Titre : Improved SMAP dual-channel algorithm for the retrieval of soil moisture Type de document : Article/Communication Auteurs : Mario Julian Chaubell, Auteur ; Simon H. Yueh, Auteur ; R. Scott Dunbar, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 3894 - 3905 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] humidité du sol
[Termes IGN] mission SMAP
[Termes IGN] polarisation
[Termes IGN] radiomètre
[Termes IGN] rugosité
[Termes IGN] teneur en eau de la végétationRésumé : (auteur) The soil moisture active passive (SMAP) mission was designed to acquire L-band radiometer measurements for the estimation of soil moisture (SM) with an average ubRMSD of not more than 0.04 m3/m3 volumetric accuracy in the top 5 cm for vegetation with a water content of less than 5 kg/ m2 . Single-channel algorithm (SCA) and dual-channel algorithm (DCA) are implemented for the processing of SMAP radiometer data. The SCA using the vertically polarized brightness temperature (SCA-V) has been providing satisfactory SM retrievals. However, the DCA using prelaunch design and algorithm parameters for vertical and horizontal polarization data has a marginal performance. In this article, we show that with the updates of the roughness parameter h and the polarization mixing parameters Q , a modified DCA (MDCA) can achieve improved accuracy over DCA; it also allows for the retrieval of vegetation optical depth (VOD or τ ). The retrieval performance of MDCA is assessed and compared with SCA-V and DCA using four years (April 1, 2015 to March 31, 2019) of in situ data from core validation sites (CVSs) and sparse networks. The assessment shows that SCA-V still outperforms all the implemented algorithms. Numéro de notice : A2020-282 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2959239 Date de publication en ligne : 15/01/2020 En ligne : https://doi.org/10.1109/TGRS.2019.2959239 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95104
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 6 (June 2020) . - pp 3894 - 3905[article]Improving GNSS-acoustic positioning by optimizing the ship’s track lines and observation combinations / Guanxu Chen in Journal of geodesy, vol 94 n° 6 (June 2020)
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Titre : Improving GNSS-acoustic positioning by optimizing the ship’s track lines and observation combinations Type de document : Article/Communication Auteurs : Guanxu Chen, Auteur ; Yang Liu, Auteur ; Yanxiong Liu, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] contrainte géométrique
[Termes IGN] fond marin
[Termes IGN] GNSS-Acoustique
[Termes IGN] navire
[Termes IGN] positionnement par GNSS
[Termes IGN] précision du positionnement
[Termes IGN] profondeur
[Termes IGN] station GNSS
[Termes IGN] trajectoire (véhicule non spatial)Résumé : (auteur) The position of a seafloor geodetic station can be determined by combining Global Navigation Satellite System (GNSS) and acoustic technologies, called GNSS-acoustic positioning. The precision of GNSS-acoustic positioning, a technique that employs the distance intersection, is determined by the positioning geometry formed by the ship’s track lines with respect to the seafloor station and the errors in the measurements. In the context of a shallow sea trial, we studied three key techniques in GNSS-acoustic positioning: the optimal geometric configuration, differencing techniques for acoustic observations and depth constraints offered by pressure gauges. The results showed that the optimal geometric configuration is a circular track with a radius of 2‾√ times the depth plus an overhead cross-track with a length of the circle diameter. Differenced observations can improve the horizontal positioning precision but will worsen the vertical positioning precision due to the change in the geometric configuration and the elimination of vertical information if the number of observations is limited. The proposed difference strategy, that is, applying a symmetric location difference operator to the circular track and an undifference operator to the cross-track, can effectively improve the horizontal precision and avoid vertical defects. By using relative depth observations from two pressure gauges as constraints, the vertical defects of GNSS-acoustic positioning can be improved, achieving a better vertical positioning precision. Applying the proposed methods to high-quality GNSS and acoustic observations, the positioning precision of a shallow seafloor geodetic station can be better than 2 cm. Numéro de notice : A2020-377 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01389-1 Date de publication en ligne : 27/06/2020 En ligne : https://doi.org/10.1007/s00190-020-01389-1 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95369
in Journal of geodesy > vol 94 n° 6 (June 2020)[article]Improving precision of field inventory estimation of aboveground biomass through an alternative view on plot biomass / Christoph Kleinn in Forest ecosystems, vol 7 (2020)
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Titre : Improving precision of field inventory estimation of aboveground biomass through an alternative view on plot biomass Type de document : Article/Communication Auteurs : Christoph Kleinn, Auteur ; Magnussen, Steen, Auteur ; Nils Nölke, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 57 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Basse-Saxe (Allemagne)
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] écologie forestière
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] parcelle forestière
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) We contrast a new continuous approach (CA) for estimating plot-level above-ground biomass (AGB) in forest inventories with the current approach of estimating AGB exclusively from the tree-level AGB predicted for each tree in a plot, henceforth called DA (discrete approach). With the CA, the AGB in a forest is modelled as a continuous surface and the AGB estimate for a fixed-area plot is computed as the integral of the AGB surface taken over the plot area. Hence with the CA, the portion of the biomass of in-plot trees that extends across the plot perimeter is ignored while the biomass from trees outside of the plot reaching inside the plot is added. We use a sampling simulation with data from a fully mapped two hectare area to illustrate that important differences in plot-level AGB estimates can emerge. Ideally CA-based estimates of mean AGB should be less variable than those derived from the DA. If realized, this difference translates to a higher precision from field sampling, or a lower required sample size. In our case study with a target precision of 5% (i.e. relative standard error of the estimated mean AGB), the CA required a 27.1% lower sample size for small plots of 100 m2 and a 10.4% lower sample size for larger plots of 1700 m2. We examined sampling induced errors only and did not yet consider model errors. We discuss practical issues in implementing the CA in field inventories and the potential in applications that model biomass with remote sensing data. The CA is a variation on a plot design for above-ground forest biomass; as such it can be applied in combination with any forest inventory sampling design. Numéro de notice : A2020-812 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1186/s40663-020-00268-7 Date de publication en ligne : 23/10/2020 En ligne : https://doi.org/10.1186/s40663-020-00268-7 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96985
in Forest ecosystems > vol 7 (2020) . - n° 57[article]Mapping aboveground biomass and its prediction uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors / Svetlana Saarela in Forest ecosystems, vol 7 (2020)
PermalinkMapping forest age using National Forest Inventory, airborne laser scanning, and Sentinel-2 data / Johannes Schumacher in Forest ecosystems, vol 7 (2020)
PermalinkMining spatiotemporal association patterns from complex geographic phenomena / Zhanjun He in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)
PermalinkMonitoring clearcutting and subsequent rapid recovery in Mediterranean coppice forests with Landsat time series / Gherardo Chirici in Annals of Forest Science, Vol 77 n° 2 (June 2020)
PermalinkPolarimetric SAR calibration and residual error estimation when corner reflectors are unavailable / Lei Shi in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)
PermalinkPrediction of traffic accidents hot spots using fuzzy logic and GIS / Aslam Al-Omari in Applied geomatics, vol 12 n° 2 (June 2020)
PermalinkA probabilistic framework for improving reverse geocoding output / Zhengcong Yin in Transactions in GIS, Vol 24 n° 3 (June 2020)
PermalinkThe position of sound in audiovisual maps: an experimental study of performance in spatial memory / Nils Siepmann in Cartographica, vol 55 n° 2 (Summer 2020)
PermalinkTrajectory drift–compensated solution of a stereo RGB-D mapping system / Shengjun Tang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 6 (June 2020)
PermalinkUnder-canopy UAV laser scanning for accurate forest field measurements / Eric Hyyppä in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)
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