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Calibration of frequency shift system of wind imaging interferometer / Yongqiang Sun in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 12 (December 2020)
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Titre : Calibration of frequency shift system of wind imaging interferometer Type de document : Article/Communication Auteurs : Yongqiang Sun, Auteur ; Chunmin Zhang, Auteur ; Pengju Zhang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 153 - 160 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] étalonnage d'instrument
[Termes IGN] fréquence
[Termes IGN] interféromètre
[Termes IGN] réflectivité
[Termes IGN] température
[Termes IGN] vent
[Termes IGN] vitesseRésumé : (Article) In this paper, the frequency shift system calibration of the wind imaging interferometer is analyzed. By establishing the frequency shift system vibration and reflectivity models, the single factor and comprehensive factors models are used to invert the wind speed and temperature, respectively. The parameters of the frequency shift system that meet the design accuracy requirement of the instrument are determined. The conclusion of this paper provides theoretical instructions for the calibration process of wind imaging interferometer. Numéro de notice : A2020-764 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.12.753 Date de publication en ligne : 01/12/2020 En ligne : https://doi.org/10.14358/PERS.86.12.753 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96563
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 12 (December 2020) . - pp 153 - 160[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 105-2020121 SL Revue Centre de documentation Revues en salle Disponible Characterizing the spatial and temporal variation of the land surface temperature hotspots in Wuhan from a local scale / Chen Yang in Geo-spatial Information Science, vol 23 n° 4 (December 2020)
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Titre : Characterizing the spatial and temporal variation of the land surface temperature hotspots in Wuhan from a local scale Type de document : Article/Communication Auteurs : Chen Yang, Auteur ; Qingming Zhan, Auteur ; Sihang Gao, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 327 - 340 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spatio-temporelle
[Termes IGN] climat urbain
[Termes IGN] géomorphologie locale
[Termes IGN] ilot thermique urbain
[Termes IGN] image Landsat-OLI
[Termes IGN] image Terra-MODIS
[Termes IGN] image thermique
[Termes IGN] morphologie urbaine
[Termes IGN] processus gaussien
[Termes IGN] regroupement de données
[Termes IGN] série temporelle
[Termes IGN] température au sol
[Termes IGN] Wuhan (Chine)
[Termes IGN] zonage (urbanisme)Résumé : (auteur) Land Surface Temperature (LST) derived from space-borne Thermal-infrared (TIR) sensors is a key parameter of urban climate studies. Current studies are inefficient to capture the spatial and temporal variations of LST for only one snapshot adopted at one time. Focusing on the characterization of the spatial and temporal of LST variations at local scales, the latent patterns, and morphological characteristics are extracted in this study. Technically, sixteen MODerate-resolution Imaging Spectroradiometer (MODIS) eight-day synthesized LST products (MYD11A2) in 2002, 2007, 2012, and 2017 are employed. First, the non-parametric Multi-Task Gaussian Process Model (MTGP) is used to extract the smooth and continuous Latent LST (LLST) patterns using one LST subset and its temporally adjacent images. Second, the Multi-Scale Shape Index (MSSI) is then applied to quantify the morphological characteristics at the optimal scale. Then, the LLST patterns and MSSI maps are clustered into multiple spatial categories. The specific clusters with the highest LLST and MSSI values are considered as local LLST hotspots. The Hotspots Weighted Mean Center (HSWMC) and standard deviation ellipse are adopted to further investigate the spatiotemporal change of hotspots orientation, direction, and trajectories. Results revealed that Impervious Surfaces (IS) composition is the most significant external forcing of local LST anomalies. The configuration factors (e.g., shape index, aggregation index) also have a noticeable local warming effect. This study represents a latent pattern and morphology-based framework for LST hotspots spatial and temporal variations characterization, catering to the zoning and grading strategies in urban planning. Numéro de notice : A2020-788 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1834882 Date de publication en ligne : 06/11/2020 En ligne : https://doi.org/10.1080/10095020.2020.1834882 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96550
in Geo-spatial Information Science > vol 23 n° 4 (December 2020) . - pp 327 - 340[article]Comparison of spatially and nonspatially explicit nonlinear mixed effects models for Norway spruce individual tree growth under single-tree selection / Simone Bianchi in Forests, vol 11 n° 12 (December 2020)
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Titre : Comparison of spatially and nonspatially explicit nonlinear mixed effects models for Norway spruce individual tree growth under single-tree selection Type de document : Article/Communication Auteurs : Simone Bianchi, Auteur ; Mari Myllymäki, Auteur ; Jouni Siipilehto, Auteur ; Hannu Salminen, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 1338 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre (flore)
[Termes IGN] croissance des arbres
[Termes IGN] forêt boréale
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle non linéaire
[Termes IGN] Picea abies
[Vedettes matières IGN] SylvicultureRésumé : (auteur) Background and Objectives: Continuous cover forestry is of increasing importance, but operational forest growth models are still lacking. The debate is especially open if more complex spatial approaches would provide a worthwhile increase in accuracy. Our objective was to compare a nonspatial versus a spatial approach for individual Norway spruce tree growth models under single-tree selection cutting.
Materials and Methods: We calibrated nonlinear mixed models using data from a long-term experiment in Finland (20 stands with 3538 individual trees for 10,238 growth measurements). We compared the use of nonspatial versus spatial predictors to describe the competitive pressure and its release after cutting. The models were compared in terms of Akaike Information Criteria (AIC), root mean square error (RMSE), and mean absolute bias (MAB), both with the training data and after cross-validation with a leave-one-out method at stand level.
Results: Even though the spatial model had a lower AIC than the nonspatial model, RMSE and MAB of the two models were similar. Both models tended to underpredict growth for the highest observed values when the tree-level random effects were not used. After cross-validation, the aggregated predictions at stand level well represented the observations in both models. For most of the predictors, the use of values based on trees’ height rather than trees’ diameter improved the fit. After single-tree selection cutting, trees had a growth boost both in the first and second five-year period after cutting, however, with different predicted intensity in the two models.
Conclusions: Under the research framework here considered, the spatial modeling approach was not more accurate than the nonspatial one. Regarding the single-tree selection cutting, an intervention regime spaced no more than 15 years apart seems necessary to sustain the individual tree growth. However, the model’s fixed effect parts were not able to capture the high growth of the few fastest-growing trees, and a proper estimation of site potential is needed for uneven-aged stands.Numéro de notice : A2020-578 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.3390/f11121338 Date de publication en ligne : 16/12/2020 En ligne : https://doi.org/10.3390/f11121338 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97034
in Forests > vol 11 n° 12 (December 2020) . - n° 1338[article]Competition overrides climate as trigger of growth decline in a mixed Fagaceae Mediterranean rear-edge forest / Alvaro Rubio-Cuadrado in Annals of Forest Science, vol 77 n° 4 (December 2020)
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Titre : Competition overrides climate as trigger of growth decline in a mixed Fagaceae Mediterranean rear-edge forest Type de document : Article/Communication Auteurs : Alvaro Rubio-Cuadrado, Auteur ; J. Julio Camarero, Auteur ; Guillermo G. Gordaliza, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] croissance des arbres
[Termes IGN] dendrochronologie
[Termes IGN] densité de la végétation
[Termes IGN] dynamique de la végétation
[Termes IGN] exploitation forestière
[Termes IGN] Fagaceae
[Termes IGN] Fagus sylvatica
[Termes IGN] forêt méditerranéenne
[Termes IGN] gestion forestière
[Termes IGN] modèle de croissance végétale
[Termes IGN] peuplement mélangé
[Termes IGN] Quercus pyrenaica
[Termes IGN] Quercus sessiliflora
[Termes IGN] structure d'un peuplement forestier
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Key message: In recent decades, there has been a decline in growth in a rear-edge broadleaf forest of Fagus sylvatica , Quercus petraea , and Quercus pyrenaica . Although temperatures have been rising due to climate change, the observed decline in growth was mainly attributed to increased density and competition between trees since the cessation of traditional uses such as logging in the 1960s.
Context: In recent decades, two major factors have influenced tree growth in many forests: climate warming, which is associated with aridification and negative growth trends in many Mediterranean forests, and abandonment of forest management, resulting from forest policy in conjunction with rural depopulation in Europe, often leading to an increase in competition and a decrease in growth.
Aims: Here, we study the growth trends in a mixed forest of Fagus sylvatica, Quercus petraea, and Quercus pyrenaica, where the abandonment of traditional uses in the 1960s has been followed by an increase in tree density. In this forest, both F. sylvatica and Q. petraea reach their south-westernmost limits of distribution.
Methods: Using dendrochronological methods and growth modeling, we assess the importance of climate warming on the shifts in competitive growth advantage of these three coexisting tree species and the relative importance of climate and competition on growth trends.
Results: Q. petraea and especially F. sylvatica showed a favorable evolution of their competitive capacity, despite the increase in temperatures that has occurred in the area in recent decades. F. sylvatica presented the lowest sensitivity to climate.
Conclusion: Under the current climate and forest structure conditions, competition is the most limiting factor on tree growth for the two oak species.Numéro de notice : A2020-661 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01004-5 Date de publication en ligne : 01/10/2020 En ligne : https://doi.org/10.1007/s13595-020-01004-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96135
in Annals of Forest Science > vol 77 n° 4 (December 2020) . - 18 p.[article]Convolutional Neural Networks accurately predict cover fractions of plant species and communities in Unmanned Aerial Vehicle imagery / Teja Kattenborn in Remote sensing in ecology and conservation, vol 6 n° 4 (December 2020)
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Titre : Convolutional Neural Networks accurately predict cover fractions of plant species and communities in Unmanned Aerial Vehicle imagery Type de document : Article/Communication Auteurs : Teja Kattenborn, Auteur ; Jana Eichel, Auteur ; Susan Wiser, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 472 - 486 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte forestière
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] espèce exotique envahissante
[Termes IGN] image à très haute résolution
[Termes IGN] image captée par drone
[Termes IGN] image RVBRésumé : (auteur) Unmanned Aerial Vehicles (UAV) greatly extended our possibilities to acquire high resolution remote sensing data for assessing the spatial distribution of species composition and vegetation characteristics. Yet, current pixel- or texture-based mapping approaches do not fully exploit the information content provided by the high spatial resolution. Here, to fully harness this spatial detail, we apply deep learning techniques, that is, Convolutional Neural Networks (CNNs), on regular tiles of UAV-orthoimagery (here 2–5 m) to identify the cover of target plant species and plant communities. The approach was tested with UAV-based orthomosaics and photogrammetric 3D information in three case studies, that is, (1) mapping tree species cover in primary forests, (2) mapping plant invasions by woody species into forests and open land and (3) mapping vegetation succession in a glacier foreland. All three case studies resulted in high predictive accuracies. The accuracy increased with increasing tile size (2–5 m) reflecting the increased spatial context captured by a tile. The inclusion of 3D information derived from the photogrammetric workflow did not significantly improve the models. We conclude that CNN are powerful in harnessing high resolution data acquired from UAV to map vegetation patterns. The study was based on low cost red, green, blue (RGB) sensors making the method accessible to a wide range of users. Combining UAV and CNN will provide tremendous opportunities for ecological applications. Numéro de notice : A2020-852 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1002/rse2.146 Date de publication en ligne : 05/02/2020 En ligne : https://doi.org/10.1002/rse2.146 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98681
in Remote sensing in ecology and conservation > vol 6 n° 4 (December 2020) . - pp 472 - 486[article]Florence: A web-based grammar of graphics for making maps and learning cartography / Ate Poorthuis in Cartographic perspectives, n° 96 (December 2020)
PermalinkGeomorphological analysis of the San Domino Island (Tremiti Islands, Southern Adriatic Sea). Results from the 2019 Geomorphological Field Camp of the MSc in Geological Science and Technology (University of Chieti-Pescara) / Marcello Buccolini in Journal of maps, vol 16 n° 3 ([01/12/2020])
PermalinkImproving aboveground biomass estimates by taking into account density variations between tree components / Antoine Billard in Annals of Forest Science, vol 77 n° 4 (December 2020)
PermalinkInclusion of GPS clock estimates for satellites Sentinel-3A/3B in DORIS geodetic solutions / Petr Štěpánek in Journal of geodesy, vol 94 n° 12 (December 2020)
PermalinkIntercomparisons of precipitable water vapour derived from radiosonde, GPS and sunphotometer observations / Shaoqi Gong in Geodetski vestnik, vol 64 n° 4 (December 2020 - February 2021)
PermalinkLarge-scale stochastic flood hazard analysis applied to the Po River / A. Curran in Natural Hazards, vol 104 n° 3 (December 2020)
PermalinkLearning from urban form to predict building heights / Nikola Milojevic-Dupont in Plos one, vol 15 n° 12 (December 2020)
PermalinkMapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks / Felix Schiefer in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)
PermalinkMapping of land cover with open-source software and ultra-high-resolution imagery acquired with unmanned aerial vehicles / Ned Horning in Remote sensing in ecology and conservation, vol 6 n° 4 (December 2020)
PermalinkMS-RRFSegNetMultiscale regional relation feature segmentation network for semantic segmentation of urban scene point clouds / Haifeng Luo in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)
PermalinkNonlocal graph convolutional networks for hyperspectral image classification / Lichao Mou in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)
PermalinkA novel intelligent classification method for urban green space based on high-resolution remote sensing images / Zhiyu Xu in Remote sensing, vol 12 n° 22 (December-1 2020)
PermalinkQuality assessment of photogrammetric methods - A workflow for reproducible UAS orthomosaics / Marvin Ludwig in Remote sensing, vol 12 n° 22 (December-1 2020)
PermalinkQuantification of cotton water consumption by remote sensing / Jefferson Vieira José in Geocarto international, vol 35 n° 16 ([01/12/2020])
PermalinkReference system origin and scale realization within the future GNSS constellation “Kepler” / Susanne Glaser in Journal of geodesy, vol 94 n° 12 (December 2020)
PermalinkRemote sensing in urban planning: Contributions towards ecologically sound policies? / Thilo Wellmann in Landscape and Urban Planning, vol 204 (December 2020)
PermalinkSemantic trajectory segmentation based on change-point detection and ontology / Yuan Gao in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)
PermalinkSemi-supervised PolSAR image classification based on improved tri-training with a minimum spanning tree / Shuang Wang in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)
PermalinkStand-level mortality models for Nordic boreal forests / Jouni Siipilehto in Silva fennica, vol 54 n° 5 (December 2020)
PermalinkStereophotogrammetry for 2-D building deformation monitoring using Kalman Filter / J.O. Odumosu in Reports on geodesy and geoinformatics, vol 110 n° 1 (December 2020)
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