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Sea level variation around Australia and its relation to climate indices / Armin Agha Karimi in Marine geodesy, vol 42 n° 5 (September 2019)
[article]
Titre : Sea level variation around Australia and its relation to climate indices Type de document : Article/Communication Auteurs : Armin Agha Karimi, Auteur ; Xiaoli Deng, Auteur ; Ole Baltazar Andersen, Auteur Année de publication : 2019 Article en page(s) : pp 469 - 489 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] analyse spectrale
[Termes IGN] Australie
[Termes IGN] changement climatique
[Termes IGN] données altimétriques
[Termes IGN] El Niño-Southern oscillation
[Termes IGN] Indien (océan)
[Termes IGN] montée du niveau de la mer
[Termes IGN] Pacifique (océan)
[Termes IGN] régression multipleRésumé : (auteur) This study aims at investigating the intradecadal and decadal signals of the sea level using 25 years of altimetry data around Australia. We have used the multivariable spectral analysis to extract six periodic signals at the 95% confidence level from altimetry-derived sea-level time series in the study area. They are signals with periods of 1, 1.5, 3, 4.3, 5.7 and 11.17 years, which can also be detected in the estimated power spectra from climate indices of the Interdecadal Pacific Oscillation, Multivariate ENSO Index, and Pacific Decadal Oscillation. A parametric model including the detected periodic signals is used to estimate sea-level trends. The determined trends in the area are in a good agreement with recent studies that consider effects of climate indices through a multivariate regression model. The advantage of our model is to present more descriptive explanation of the sea level signals around Australia in terms of periodicity and spatial variability. Numéro de notice : A2019-299 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2019.1629131 Date de publication en ligne : 26/06/2019 En ligne : https://doi.org/10.1080/01490419.2019.1629131 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93219
in Marine geodesy > vol 42 n° 5 (September 2019) . - pp 469 - 489[article]Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images / Jie Wang in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)
[article]
Titre : Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images Type de document : Article/Communication Auteurs : Jie Wang, Auteur ; Xiangming Xiao, Auteur ; Rajen Bajgain, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 189 - 201 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse aérienne
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image Landsat-8
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] indice de végétation
[Termes IGN] Leaf Area Index
[Termes IGN] Oklahoma (Etats-Unis)
[Termes IGN] paturage
[Termes IGN] phénologie
[Termes IGN] régression multipleRésumé : (Auteur) Grassland degradation has accelerated in recent decades in response to increased climate variability and human activity. Rangeland and grassland conditions directly affect forage quality, livestock production, and regional grassland resources. In this study, we examined the potential of integrating synthetic aperture radar (SAR, Sentinel-1) and optical remote sensing (Landsat-8 and Sentinel-2) data to monitor the conditions of a native pasture and an introduced pasture in Oklahoma, USA. Leaf area index (LAI) and aboveground biomass (AGB) were used as indicators of pasture conditions under varying climate and human activities. We estimated the seasonal dynamics of LAI and AGB using Sentinel-1 (S1), Landsat-8 (LC8), and Sentinel-2 (S2) data, both individually and integrally, applying three widely used algorithms: Multiple Linear Regression (MLR), Support Vector Machine (SVM), and Random Forest (RF). Results indicated that integration of LC8 and S2 data provided sufficient data to capture the seasonal dynamics of grasslands at a 10–30-m spatial resolution and improved assessments of critical phenology stages in both pluvial and dry years. The satellite-based LAI and AGB models developed from ground measurements in 2015 reasonably predicted the seasonal dynamics and spatial heterogeneity of LAI and AGB in 2016. By comparison, the integration of S1, LC8, and S2 has the potential to improve the estimation of LAI and AGB more than 30% relative to the performance of S1 at low vegetation cover (LAI 2 m2/m2, AGB > 500 g/m2). These results demonstrate the potential of combining S1, LC8, and S2 monitoring grazing tallgrass prairie to provide timely and accurate data for grassland management. Numéro de notice : A2019-269 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.06.007 Date de publication en ligne : 21/06/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.06.007 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93086
in ISPRS Journal of photogrammetry and remote sensing > vol 154 (August 2019) . - pp 189 - 201[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2019081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019083 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019082 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Pavement marking retroreflectivity estimation and evaluation using mobile Lidar data / Erzhuo Che in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 8 (August 2019)
[article]
Titre : Pavement marking retroreflectivity estimation and evaluation using mobile Lidar data Type de document : Article/Communication Auteurs : Erzhuo Che, Auteur ; Michael J. Olsen, Auteur ; Christopher E. Parrish, Auteur ; Jaehoon Jung, Auteur Année de publication : 2019 Article en page(s) : pp 573 - 583 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] étalonnage radiométrique
[Termes IGN] réflectivité
[Termes IGN] régression
[Termes IGN] semis de points
[Termes IGN] signalisation routièreRésumé : (Auteur) Pavement markings are produced with retroreflective materials to enhance visibility for motorists, particularly at night. Retroreflectivity evaluation throughout an extensive highway network for maintenance and asset management purposes is a critical, yet challenging task for transportation agencies because visual evaluation can often be subjective and inconsistent, while field measurement can be time-consuming. Mobile Light Detection and Ranging (Lidar) datasets can potentially provide a safe, cost-effective, and reliable method of performing the required evaluation. This paper presents an empirical model for radiometric calibration of Lidar intensity information from the Leica Pegasus:Two system for pavement marking evaluation. The model was developed using dense handheld retroreflectometer measurements and mobile Lidar data collected in a variety of geometric configurations on a test site consisting of various markings with varying degrees of wear. The quantitative accuracy assessment of the proposed radiometric calibration model for estimating retroreflectivity was conducted to another independent dataset collected in different lanes and system configurations. Numéro de notice : A2019-409 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.8.573 Date de publication en ligne : 01/08/2019 En ligne : https://doi.org/10.14358/PERS.85.8.573 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93540
in Photogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 8 (August 2019) . - pp 573 - 583[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2019081 SL Revue Centre de documentation Revues en salle Disponible 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)
[article]
Titre : Sea level prediction in the Yellow Sea from satellite altimetry with a combined least squares-neural network approach Type de document : Article/Communication Auteurs : Jian Zhao, Auteur ; Yanguo Fan, Auteur ; Yuxiang Mu, Auteur Année de publication : 2019 Article en page(s) : pp 344 - 366 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] détection d'anomalie
[Termes IGN] données altimétriques
[Termes IGN] données Jason
[Termes IGN] données Topex-Poseidon
[Termes IGN] image ERS-SAR
[Termes IGN] méthode des moindres carrés
[Termes IGN] montée du niveau de la mer
[Termes IGN] Pacifique nord
[Termes IGN] prévision
[Termes IGN] réseau neuronal artificiel
[Termes IGN] série temporelleRésumé : (auteur) Accessible high-quality observation datasets and proper modeling process are critically required to accurately predict sea level rise in coastal areas. This study focuses on developing and validating a combined least squares-neural network approach applicable to the short-term prediction of sea level variations in the Yellow Sea, where the periodic terms and linear trend of sea level change are fitted and extrapolated using the least squares model, while the prediction of the residual terms is performed by several different types of artificial neural networks. The input and output data used are the sea level anomalies (SLA) time series in the Yellow Sea from 1993 to 2016 derived from ERS-1/2, Topex/Poseidon, Jason-1/2, and Envisat satellite altimetry missions. Tests of different neural network architectures and learning algorithms are performed to assess their applicability for predicting the residuals of SLA time series. Different neural networks satisfactorily provide reliable results and the root mean square errors of the predictions from the proposed combined approach are less than 2 cm and correlation coefficients between the observed and predicted SLA are up to 0.87. Results prove the reliability of the combined least squares-neural network approach on the short-term prediction of sea level variability close to the coast. Numéro de notice : A2019-281 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2019.1626306 Date de publication en ligne : 12/06/2019 En ligne : https://doi.org/10.1080/01490419.2019.1626306 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93115
in Marine geodesy > vol 42 n° 4 (July 2019) . - pp 344 - 366[article]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)
[article]
Titre : Demonstrating the transferability of forest inventory attribute models derived using airborne laser scanning data Type de document : Article/Communication Auteurs : Piotr Tompalski, Auteur ; Joanne C. White, Auteur ; Nicholas C. Coops, Auteur ; Michael A. Wulder, Auteur Année de publication : 2019 Article en page(s) : pp 110 - 124 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] classification barycentrique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] densité des points
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] méthode des moindres carrés
[Termes IGN] méthode robuste
[Termes IGN] modèle mathématique
[Termes IGN] régression
[Termes IGN] semis de points
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Airborne laser scanning (ALS) is a reliable source of accurate information for forest stand inventory attributes including height, cover, basal area, and volume. The commonly applied area-based approach (ABA) allows the derivation of wall-to-wall geospatial coverages representing each of the modeled attributes at a grid-cell level, with spatial resolutions typically between 20 and 30 m. The ABA predictive models are developed using stratified inventory data from field plots, the requirement for which can increase the overall cost of the ALS-based inventory. Parsimonious use of ground plots is a key means to control variable costs in the operational implementation of the ABA. In this paper, we demonstrate how the prediction accuracy of Lorey's height (HL, m), quadratic mean diameter (QMD, cm), and gross volume (V, m3) vary when existing ABA models are transferred to different areas or are applied to point cloud data with different characteristics than those on which the original model was developed. Specifically, we consider three scenarios of model transferability: (i) same point cloud characteristics, different areas; (ii) different point cloud characteristics, same areas; and (iii) different point cloud characteristics, different areas. We generated area-based models using three modeling approaches: linear regression (OLS), random forests (RF), and k-nearest neighbour (kNN) imputation. Results indicated that the prediction accuracy of area-based models varied by attribute and by modeling approach. We found that when the models were transferred their prediction accuracy decreased, with an average increase in relative bias up to 22.04%, and increase in relative RMSE up to 29.31%. Prediction accuracies for HL were higher than those of QMD or V when models were transferred, and had the lowest average increase in relative bias and relative RMSE of Numéro de notice : A2019-227 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2019.04.006 Date de publication en ligne : 13/04/2019 En ligne : https://doi.org/10.1016/j.rse.2019.04.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92741
in Remote sensing of environment > vol 227 (15 June 2019) . - pp 110 - 124[article]Analyzing the recent dynamics of wildland fires in Quercus suber L. woodlands in Sardinia (Italy), Corsica (France) and Catalonia (Spain) / Michele Salis in European Journal of Forest Research, vol 138 n° 3 (June 2019)PermalinkHelmert-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)PermalinkInvestigating the effects of 3D urban morphology on the surface urban heat island effect in urban functional zones by using high-resolution remote sensing data : A case study of Wuhan, Central China / Xin Huang in ISPRS Journal of photogrammetry and remote sensing, vol 152 (June 2019)PermalinkA regression model-based method for indoor positioning with compound location fingerprints / Tomofumi Takayama in Geo-spatial Information Science, vol 22 n° 2 (June 2019)PermalinkA new method of equiangular sectorial voxelization of single-scan terrestrial laser scanning data and its applications in forest defoliation estimation / Langning Huo in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)PermalinkBIM-Tracker: A model-based visual tracking approach for indoor localisation using a 3D building model / Debaditya Acharya in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)PermalinkIncluding Sentinel-1 radar data to improve the disaggregation of MODIS land surface temperature data / Abdelhakim Amazirh in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)PermalinkIntegrated relative orientation based on point and line features via Plücker coordinates / Qinghong Sheng in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 4 (avril 2019)PermalinkRobust external calibration of terrestrial laser scanner and digital camera for structural monitoring / Mohammad Omidalizarandi in Journal of applied geodesy, vol 13 n° 2 (April 2019)PermalinkVertical ionospheric delay estimation for single-receiver operation / Ahmed Elsayed in Journal of applied geodesy, vol 13 n° 2 (April 2019)Permalink