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Accurate modelling of canopy traits from seasonal Sentinel-2 imagery based on the vertical distribution of leaf traits / Tawanda W. Gara in ISPRS Journal of photogrammetry and remote sensing, vol 157 (November 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 157 (November 2019) . - pp 108 - 123 Titre : Accurate modelling of canopy traits from seasonal Sentinel-2 imagery based on the vertical distribution of leaf traits Type de document : Article/Communication Auteurs : Tawanda W. Gara, Auteur ; Roshanak Darvishzadeh, Auteur ; Andrew K. Skidmore, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 108 - 123 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Bavière (Allemagne) [Termes descripteurs IGN] canopée [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] écosystème forestier [Termes descripteurs IGN] hétérogénéité spatiale [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] indice foliaire [Termes descripteurs IGN] Leaf mass per area [Termes descripteurs IGN] photosynthèse [Termes descripteurs IGN] variation saisonnière Résumé : (Auteur) Leaf traits at canopy level (hereinafter canopy traits) are conventionally expressed as a product of total canopy leaf area index (LAI) and leaf trait content based on samples collected from the exposed upper canopy. This traditional expression is centered on the theory that absorption of incident photosynthetically active radiation (PAR) follow a bell-shaped function skewed to the upper canopy. However, the validity of this theory has remained untested for a suite of canopy traits in a temperate forest ecosystem across multiple seasons using multispectral imagery. In this study, we examined the effect of canopy traits expression in modelling canopy traits using Sentinel-2 multispectral data across the growing season in Bavaria Forest National Park (BFNP), Germany. To achieve this, we measured leaf mass per area (LMA), chlorophyll (Cab), nitrogen (N) and carbon content and LAI from the exposed upper and shaded lower canopy respectively over three seasons (spring, summer and autumn). Subsequently, we estimated canopy traits using two expressions, i.e. the traditional expression-based on the product of LAI and leaf traits content of samples collected from the sunlit upper canopy (hereinafter top-of-canopy expression) and the weighted expression - established on the proportion between the shaded lower and sunlit upper canopy LAI and their respective leaf traits content. Using a Random Forest machine-learning algorithm, we separately modelled canopy traits estimated from the two expressions using Sentinel-2 spectral bands and vegetation indices. Our results showed that dry matter related canopy traits (LMA, N and carbon) estimated based on the weighted canopy expression yield stronger correlations and higher prediction accuracy (NRMSECV  0.48 µg/cm2) across all seasons. We also developed a generalized model that explained 52.57–67.82% variation in canopy traits across the three seasons. Using the most accurate Random Forest model for each season, we demonstrated the capability of Sentinel-2 data to map seasonal dynamics of canopy traits across the park. Results presented in this study revealed that canopy trait expression can have a profound effect on modelling the accuracy of canopy traits using satellite imagery throughout the growing seasons. These findings have implications on model accuracy when monitoring the dynamics of ecosystem functions, processes and services. Numéro de notice : A2019-493 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.09.005 date de publication en ligne : 11/09/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.09.005 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93725 [article]

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Decomposition of geodetic time series: A combined simulated annealing algorithm and Kalman filter approach / Feng Ming in Advances in space research, vol 64 n°5 (1 September 2019)  

Public [article]  inAdvances in space research > vol 64 n°5 (1 September 2019) . - pp Titre : Decomposition of geodetic time series: A combined simulated annealing algorithm and Kalman filter approach Type de document : Article/Communication Auteurs : Feng Ming, Auteur ; Yuanxi Yang, Auteur ; Anmin Zeng, Auteur ; Bin Zhao, Auteur Année de publication : 2019 Article en page(s) : pp Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] algorithme du recuit simulé [Termes descripteurs IGN] bruit (théorie du signal) [Termes descripteurs IGN] bruit blanc [Termes descripteurs IGN] bruit rose [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] méthode du maximum de vraisemblance (estimation) [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] variation saisonnière [Vedettes matières IGN] Traitement de données GNSS Numéro de notice : A2019-399 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.asr.2019.05.049 date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1016/j.asr.2019.05.049 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93519 [article]

A novel method for separating woody and herbaceous time series / Qiang Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 7 (July 2019) . - pp 509 - 520 Titre : A novel method for separating woody and herbaceous time series Type de document : Article/Communication Auteurs : Qiang Zhou, Auteur ; Shuguang Liu, Auteur ; Michael J Hill, Auteur Année de publication : 2019 Article en page(s) : pp 509 - 520 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Afrique australe [Termes descripteurs IGN] bois [Termes descripteurs IGN] extraction de la végétation [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image Ikonos [Termes descripteurs IGN] image Landsat-SWIR [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] plante herbacée [Termes descripteurs IGN] savane [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] variation saisonnière Résumé : (auteur) Mapping the spatial distribution of woody and herbaceous vegetation in high temporal resolution in savannas would be beneficial for modeling interrelationships between trees and grasses, and monitoring fuel loads and biomass for livestock. In this study, we developed a frequency decomposition method to separate woody and herbaceous vegetation components using Normalized Difference Vegetation Index (NDVI) time series. The results were validated using fractional cover data derived from high-resolution images. The validation revealed a close relationship between our decomposed NDVI and corresponding fractional cover (R2 = 0.55 and 0.64 for woody and herbaceous components, respectively). We examined the spatial and temporal patterns of the decomposed NDVI, where woody and herbaceous NDVI showed different responses to precipitation. The methods proposed in this study can be used to separate the woody and herbaceous NDVI time series as an alternative approach for monitoring woody and herbaceous vegetation interrelationships related to climatic drivers. Numéro de notice : A2019-259 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.7.509 date de publication en ligne : 01/07/2019 En ligne : https://doi.org/10.14358/PERS.85.7.509 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93062 [article]

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Seasonal pattern in time series of variances of GPS residual errors Anova estimates / Darko Anđić in Geodetski vestnik, vol 63 n° 2 (June - August 2019)  

Public [article]  inGeodetski vestnik > vol 63 n° 2 (June - August 2019) . - pp 260 - 271 Titre : Seasonal pattern in time series of variances of GPS residual errors Anova estimates Type de document : Article/Communication Auteurs : Darko Anđić, Auteur Année de publication : 2019 Article en page(s) : pp 260 - 271 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] double différence [Termes descripteurs IGN] positionnement par GPS [Termes descripteurs IGN] propagation ionosphérique [Termes descripteurs IGN] propagation troposphérique [Termes descripteurs IGN] rayonnement solaire [Termes descripteurs IGN] résidu [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] variance [Termes descripteurs IGN] variation saisonnière Résumé : (auteur) In this paper, which represents a continuation of the previous author's work, an inconstancy of GPS residual error ANOVA estimates and their variances are presented. For the purpose of the analysis, fixed solutions for all of the three coordinates, e (eastwards), n (northwards) and u (upwards), obtained by using ionosphere-free (L0) linear combination of double-difference phase observations in the processing of GPS data, were employed. The aim of the research was to consider the behaviour of variances of GPS residual error ANOVA estimates in time because there has not been any paper dealing with that issue so far. Herein, it turned out a seasonal pattern in related time series was present. In addition, it was concluded there was a difference in ANOVA estimate extreme values obtained when one considered daily data subsets compared to those obtained in the approach considering monthly data of the fixed solutions. GPS data collected at ending stations of a baseline of 40 km in length within a four-year period, involving the lowest and increased solar activity, were used in calculations. Numéro de notice : A2019-405 Thématique : POSITIONNEMENT Nature : Article DOI : 10.15292/geodetski-vestnik.2019.02.260-271 En ligne : http://dx.doi.org/10.15292/geodetski-vestnik.2019.02.260-271 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93509 [article]

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Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis / Matheus Pinheiro Ferreira in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 149 (March 2019) . - pp 119 - 131 Titre : Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis Type de document : Article/Communication Auteurs : Matheus Pinheiro Ferreira, Auteur ; Fabien Hubert Wagner, Auteur ; Luiz E.O.C. Aragão, Auteur Année de publication : 2019 Article en page(s) : pp 119 - 131 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse texturale [Termes descripteurs IGN] arbre (flore) [Termes descripteurs IGN] Brésil [Termes descripteurs IGN] canopée [Termes descripteurs IGN] classification dirigée [Termes descripteurs IGN] espèce végétale [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] houppier [Termes descripteurs IGN] image à très haute résolution [Termes descripteurs IGN] image infrarouge [Termes descripteurs IGN] image Worldview [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] matrice de co-occurence [Termes descripteurs IGN] pansharpening (fusion d'images) [Termes descripteurs IGN] variation saisonnière Résumé : (Auteur) Tropical forest conservation and management can significantly benefit from information about the spatial distribution of tree species. Very-high resolution (VHR) spaceborne platforms have been hailed as a promising technology for mapping tree species over broad spatial extents. WorldView-3, the most advanced VHR sensor, provides spectral data in 16 bands covering the visible to near-infrared (VNIR, 400–1040 nm) and shortwave-infrared (SWIR, 1210–2365 nm) wavelength ranges. It also collects images at unprecedented levels of details using a panchromatic band with 0.3-m of spatial resolution. However, the potential of WorldView-3 at its full spectral and spatial resolution for tropical tree species classification remains unknown. In this study, we performed a comprehensive assessment of WorldView-3 images acquired in the dry and wet seasons for tree species discrimination in tropical semi-deciduous forests. Classification experiments were performed using VNIR individually and combined with SWIR channels. To take advantage of the sub-metric resolution of the panchromatic band for classification, we applied an individual tree crown (ITC)-based approach that employed pan-sharpened VNIR bands and gray level co-occurrence matrix texture features. We determined whether the combination of images from the two annual seasons improves the classification accuracy. Finally, we investigated which plant traits influenced species detection. The new SWIR sensing capabilities of WorldView-3 increased the average producer’s accuracy up to 7.8%, by enabling the detection of non-photosynthetic vegetation within ITCs. The combination of VNIR bands from the two annual seasons did not improve the classification results when compared to the results obtained using images from each season individually. The use of VNIR bands at their original 1.2-m spatial resolution yielded average producer’s accuracies of 43.1 ± 3.1% and 38.8 ± 3% in the wet and dry seasons, respectively. The ITC-based approach improved the accuracy to 70 ± 8% in the wet and 68.4 ± 7.4% in the dry season. Texture analysis of the panchromatic band enabled the detection of species-specific differences in crown structure, which improved species detection. The use of texture analysis, pan-sharpening, and ITC delineation is a potential approach to perform tree species classification in tropical forests with WorldView-3 satellite images. Numéro de notice : A2019-117 Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.019 date de publication en ligne : 28/01/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.019 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92444 [article]

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Learning scene geometry for visual localization in challenging conditions / Nathan Piasco (2019)    

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Identification and extraction of seasonal geodetic signals due to surface load variations / Stacy Larochelle in Journal of geophysical research : Solid Earth, vol 123 n° 12 (December 2018)  

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Seasonal time-course of the above ground biomass production efficiency in beech trees (Fagus sylvatica L.) / Laura Heid in Annals of Forest Science [en ligne], vol 75 n° 1 (March 2018)  

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Déformation saisonnière de la Terre / Kristel Chanard (2018) 

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Exploring the impact of seasonality on urban land-cover mapping using multi-season sentinel-1A and GF-1 WFV images in a subtropical monsoon-climate region / Tao Zhou in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)  

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ITRF and seasonal station motions / Zuheir Altamimi (2018)

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On the estimation of physical height changes using GRACE satellite mission data – A case study of Central Europe / Walyeldeen Godah in Geodesy and cartography, vol 66 n° 2 (December 2017)  

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Seasonal low-degree changes in terrestrial water mass load from global GNSS measurements / Thierry Meyrath in Journal of geodesy, vol 91 n° 11 (November 2017)  

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Adapter les itinéraires sylvicoles pour atténuer les effets du changement climatique. Résultats pour la chênaie sessiliflore française à partir des réseaux d’expérimentations sylvicoles / François Lebourgeois in Revue forestière française [en ligne], vol 69 n° 1 (octobre 2017)  

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Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications / Amanda Veloso in Remote sensing of environment, vol 199 (15 September 2017)  

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