Descripteur
Documents disponibles dans cette catégorie (450)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Prediction of plant diversity in grasslands using Sentinel-1 and -2 satellite image time series / Mathieu Fauvel in Remote sensing of environment, Vol 237 (February 2020)
[article]
Titre : Prediction of plant diversity in grasslands using Sentinel-1 and -2 satellite image time series Type de document : Article/Communication Auteurs : Mathieu Fauvel, Auteur ; Maylis Lopes, Auteur ; Titouan Dubo, Auteur ; Justine Rivers-Moore, Auteur ; Pierre-Louis Frison , Auteur ; Nicolas Gross, Auteur ; Annie Ouin, Auteur Année de publication : 2020 Projets : SEBIOREF / Ouin, Annie Article en page(s) : 13 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] biodiversité végétale
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] Haute-Garonne (31)
[Termes IGN] image radar moirée
[Termes IGN] image RapidEye
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] indice de diversité
[Termes IGN] indice de végétation
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] prairie
[Termes IGN] série temporelle
[Termes IGN] taxinomieRésumé : (auteur) The prediction of grasslands plant diversity using satellite image time series is considered in this article. Fifteen months of freely available Sentinel optical and radar data were used to predict taxonomic and functional diversity at the pixel scale (10 m × 10 m) over a large geographical extent (40,000 km2). 415 field measurements were collected in 83 grasslands to train and validate several statistical learning methods. The objective was to link the satellite spectro-temporal data to the plant diversity indices. Among the several diversity indices tested, Simpson and Shannon indices were best predicted with a coefficient of determination around 0.4 using a Random Forest predictor and Sentinel-2 data. The use of Sentinel-1 data was not found to improve significantly the prediction accuracy. Using the Random Forest algorithm and the Sentinel-2 time series, the prediction of the Simpson index was performed. The resulting map highlights the intra-parcel variability and demonstrates the capacity of satellite image time series to monitor grasslands plant taxonomic diversity from an ecological viewpoint. Numéro de notice : A2020-004 Affiliation des auteurs : UPEM-LASTIG+Ext (2016-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2019.111536 Date de publication en ligne : 26/11/2019 En ligne : https://doi.org/10.1016/j.rse.2019.111536 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94296
in Remote sensing of environment > Vol 237 (February 2020) . - 13 p.[article]Red-edge band vegetation indices for leaf area index estimation from Sentinel-2/MSI imagery / Yuanheng Sun in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)
[article]
Titre : Red-edge band vegetation indices for leaf area index estimation from Sentinel-2/MSI imagery Type de document : Article/Communication Auteurs : Yuanheng Sun, Auteur ; Qiming Qin, Auteur ; Huazhong Ren, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 826 - 840 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] bande rouge
[Termes IGN] canopée
[Termes IGN] Chine
[Termes IGN] image multibande
[Termes IGN] image proche infrarouge
[Termes IGN] image Sentinel-MSI
[Termes IGN] indice de végétation
[Termes IGN] indice foliaire
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] teneur en chlorophylle des feuillesRésumé : (auteur) The estimation of leaf area index (LAI) from optical remotely sensed data based on vegetation indices (VIs) is a quick and practical approach to acquire LAI over vast areas. Reflectance in the red-edge bands is sensitive to vegetation status, and its information is thought to be useful in agricultural applications. Based on three red-edge band observations (represented as RE1, RE2, and RE3 for bands 5–7) from the Multispectral Instrument (MSI) onboard the Sentinel-2 satellite, this article aims to investigate the feasibility and performance of using red-edge bands for LAI estimates with the VI method and ground-measured LAI data sets. Sensitivity analysis from PROSAIL simulations revealed that RE1 is mainly affected by the influence of the leaf chlorophyll content, and this uncertainty should not be ignored during LAI estimation. For the normalized difference vegetation index (NDVI), modified simple ratio (MSR), chlorophyll index (CI), and wide dynamic range vegetation index (WDRVI), the optimal combination of Sentinel-2 bands for LAI estimation was RE2 and RE3, with a minimum root-mean-square error (RMSE) of 0.75. Four 3-band red-edge VIs were proposed to exploit the full content of the red-edge bands of Sentinel-2, and their performance in LAI estimation improved slightly. However, both 2-band red-edge VIs and 3-band red-edge VIs remained slightly saturated at high LAI levels; therefore, a segmental estimation with a threshold was suggested for large LAIs. The results indicate that the optimal 2-band red-edge VIs and proposed 3-band red-edge VIs are effective tools for crop LAI estimation in multiple-growth stages with Sentinel-2 MSI images. Numéro de notice : A2020-069 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2940826 Date de publication en ligne : 27/09/2019 En ligne : http://doi.org/10.1109/TGRS.2019.2940826 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94615
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 2 (February 2020) . - pp 826 - 840[article]The effects of different combinations of simulated climate change-related stressors on juveniles of seven forest tree species grown as mono-species and mixed cultures / Alfas Pliüra in Baltic forestry, vol 26 n° 1 ([01/02/2020])
[article]
Titre : The effects of different combinations of simulated climate change-related stressors on juveniles of seven forest tree species grown as mono-species and mixed cultures Type de document : Article/Communication Auteurs : Alfas Pliüra, Auteur ; Gintare Bajerkeviciene, Auteur ; Juozas Labokas, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 14 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Alnus glutinosa
[Termes IGN] Betula pendula
[Termes IGN] biomasse
[Termes IGN] croissance des arbres
[Termes IGN] dioxyde de carbone
[Termes IGN] écophysiologie
[Termes IGN] écosystème forestier
[Termes IGN] Fraxinus excelsior
[Termes IGN] Leaf Area Index
[Termes IGN] Lituanie
[Termes IGN] peuplement mélangé
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] Populus tremula
[Termes IGN] Quercus pedunculata
[Termes IGN] sécheresse
[Termes IGN] stress hydrique
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) The aim of the study was to assess changes in performance and competition for light of juveniles of seven forest tree species, Pinus sylvestris, Picea abies, Betula pendula, Alnus glutinosa, Populus tremula, Quercus robur and Fraxinus excelsior, grown in mono-species and mixed cultures with isolated potted roots under the impact of different combinations of climate change-related stressors, simulated in a phytotron under the elevated CO2 concentration during one growing season, as follows: i) heat + elevated humidity (HW); ii) heat + frost +
drought (HFD); iii) heat + elevated humidity + increased UV-B radiation doses + elevated ozone concentration (HWUO); and iv) heat + frost + drought + increased UV-B radiation doses + elevated ozone concentration (HFDUO). For the mixed cultures, three typical species’ mixtures were used: i) P. sylvestris, B. pendula and P. abies, ii) P. abies, B. pendula and Q. robur and iii) F. excelsior, A. glutinosa and P. tremula. For the control, the same material was grown outside the phytotron in ambient conditions. Analysis of variance (ANOVA) revealed that the effects of the complex treatments, species and species by treatment interactions
were highly significant in most of the biomass, growth, physiological and biochemical traits studied. Pattern of species culture had highly significant effect on physiological and biochemical traits (except for H2O2 concentration); meanwhile it was of low significance for biomass and growth traits. Pattern of species culture by treatment interaction was highly significant in all traits, suggesting that the effects of the applied complex treatments vary depending on the pattern of species culture. Under the hot wet conditions the highest stem volume index, tree biomass, and growth were observed in deciduous P. tremula, A. glutinosa and B. pendula with more clearly pronounced differences in performance between different patterns of species cultures than in ambient conditions showing that the enhanced growth conditions facilitate revealing the potential and specific requirements of the fast-growers. P. abies in all treatments had lower stem volume index and tree biomass than in ambient conditions with no significant differences between the patterns of species culture, indicating that it suffered irrespectively of light availability in different cultures. The differences between performances of most tree species in mono- and mixed cultures in HFD treatment were rather small and nonsignificant. A complex HWUO treatment caused further reduction in tree biomass in all species and culture patterns except for mono-species cultures of A. glutinosa and B. pendula. The most complex HFDUO treatment had the strongest negative effect on biomass of almost all tree species compared to that observed in HW treatment, except for Q. robur and P. sylvestris which biomass and height increments remained higher than those in ambient conditions. This was due to relatively high drought tolerance and compensatory effects of the increased CO2 concentration and temperature. Physiological and biochemical responses of species in different patterns of species cultures across treatments were very variable although often did not reflect in the effects on growth and biomass traits. The observed changes in performance of different tree species in different patterns of species cultures under various complex treatments allowed inferring that climate change may condition certain changes in competitiveness of some tree species resulting in atypical ecological successions of species and forest ecosystemsNuméro de notice : A2020-595 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.46490/BF326 Date de publication en ligne : 23/03/2020 En ligne : https://doi.org/10.46490/BF326 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95888
in Baltic forestry > vol 26 n° 1 [01/02/2020] . - 14 p.[article]The potentiality of Sentinel-2 to assess the effect of fire events on Mediterranean mountain vegetation / Walter de Simone in Plant sociology, vol 57 n° 1 ([01/02/2020])
[article]
Titre : The potentiality of Sentinel-2 to assess the effect of fire events on Mediterranean mountain vegetation Type de document : Article/Communication Auteurs : Walter de Simone, Auteur ; Michele Di Musciano, Auteur ; Valter Di Cecco, Auteur Année de publication : 2020 Article en page(s) : pp 11 - 22 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] forêt méditerranéenne
[Termes IGN] habitat d'intérêt communautaire
[Termes IGN] image Sentinel-MSI
[Termes IGN] incendie de forêt
[Termes IGN] Italie
[Termes IGN] montagne
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] surveillance forestière
[Termes IGN] zone sinistréeRésumé : (auteur) Wildfires are currently one of the most important environmental problems, as they cause disturbance in ecosystems generating environmental, economic and social costs. The Sentinel-2 from Copernicus Program (Sentinel satellites) offers a great tool for post-fire monitoring. The main objective of this study is to evaluate the potential of Sentinel-2 in a peculiar mountainous landscape by measuring and identifying the burned areas and monitor the short-term response of the vegetation in different ‘burn severity’ classes. A Sentinel-2 dataset was created, and pre-processing operations were performed. Relativized Burn Ratio (RBR) was calculated to identify ‘burn scar’ and discriminate the ‘burn severity’ classes. A two-year monitoring was carried out with areas identified based on different severity classes, using Normalized Difference Vegetation Index (NDVI) to investigate the short-term vegetation dynamics of the burned habitats; habitats refer to Annex I of the European Directive 92/43/EEC. The study area is located in ‘Campo Imperatore’ within the Gran Sasso — Monti della Laga National Park (central Italy). The first important result was the identification and quantification of the area affected by fire. The RBR allowed us to identify even the less damaged habitats with high accuracy. The survey highlighted the importance of these Open-source tools for qualitative and quantitative evaluation of fires and the short-term assessment of vegetation recovery dynamics. The information gathered by this type of monitoring can be used by decision-makers both for emergency management and for possible environmental restoration of the burned areas. Numéro de notice : A2020-851 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3897/pls2020571/02 Date de publication en ligne : 13/04/2020 En ligne : https://doi.org/10.3897/pls2020571/02 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98668
in Plant sociology > vol 57 n° 1 [01/02/2020] . - pp 11 - 22[article]Analyse automatique du couvert végétal pour la gestion du risque végétation en milieu ferroviaire à partir d'imagerie aérienne / Hélène Rouillon (2020)
Titre : Analyse automatique du couvert végétal pour la gestion du risque végétation en milieu ferroviaire à partir d'imagerie aérienne Type de document : Mémoire Auteurs : Hélène Rouillon, Auteur Editeur : Strasbourg : Institut National des Sciences Appliquées INSA Strasbourg Année de publication : 2020 Importance : 93 p. Format : 21 x 30 cm Note générale : bibliographie
Mémoire de fin d'études d'Ingénieur INSA, spécialité TopographieLangues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] carte de la végétation
[Termes IGN] classification orientée objet
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] couvert végétal
[Termes IGN] extraction de la végétation
[Termes IGN] image aérienne
[Termes IGN] image captée par drone
[Termes IGN] image RVB
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] orthophotographie
[Termes IGN] réseau ferroviaire
[Termes IGN] segmentation d'image
[Termes IGN] système d'information géographiqueIndex. décimale : INSAS Mémoires d'ingénieur de l'INSA Strasbourg - Topographie, ex ENSAIS Résumé : (auteur) La végétation et les risques qu’elle peut comporter pour les infrastructures ferroviaires et leurs usagers constituent un enjeu majeur pour SNCF Réseau. Aujourd’hui, l’entreprise ferroviaire souhaite connaître et maîtriser ce risque végétation. L’objet de ce PFE est l’analyse automatique du couvert végétal en milieu ferroviaire à partir d’imagerie aérienne RGB acquise par drone, hélicoptère ou avion. Pour répondre à cette problématique, un réseau de neurones destiné à la segmentation sémantique des images est mis en œuvre. En effet, une fois bien entraînés, les réseaux de neurones, par leur capacité d’apprentissage, sont en mesure de classifier efficacement toute nouvelle image. Trois classes ont été définies en fonction des risques que pouvaient présenter la végétation : « arbres », « reste de la végétation » et « non-végétation ». Une chaîne de traitement complète des données a été proposée permettant, sur la base de ces images, une cartographie SIG de la végétation. Cette connaissance, aisément déployable sur des lignes entières, doit permettre au mainteneur de cibler les zones prioritaires et d’optimiser ses plans d’élagages. Note de contenu : Introduction
1- Etude préalable au développement de la solution
2- Le réseau de neurones SegNet pour le traitement d’images d’observation de la Terre et la base de données
3- Optimisation du traitement des données
ConclusionNuméro de notice : 28529 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Mémoire ingénieur INSAS Organisme de stage : Altametris DOI : sans En ligne : http://eprints2.insa-strasbourg.fr/4133/ Format de la ressource électronique : url Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97346 Combination of linear regression lines to understand the response of Sentinel-1 dual polarization SAR data with crop phenology - case study in Miyazaki, Japan / Emal Wali in Remote sensing, vol 12 n° 1 (January 2020)PermalinkDétermination conjointe des inondations et du type d’eau au moyen de l’imagerie multi-spectrale / Sabrine Amzil (2020)PermalinkIndividual tree detection and classification for mapping pine wilt disease using multispectral and visible color imagery acquired from unmanned aerial vehicle / Takeshi Hoshikawa in Journal of The Remote Sensing Society of Japan, vol 40 n° 1 (2020)PermalinkOn the joint exploitation of optical and SAR satellite imagery for grassland monitoring / Anatol Garioud (2020)PermalinkRegional-scale forest mapping over fragmented landscapes using global forest products and Landsat time series classification / Viktor Myroniuk in Remote sensing, vol 12 n° 1 (January 2020)PermalinkPermalinkA systematic evaluation of influence of image selection process on remote sensing-based burn severity indices in North American boreal forest and tundra ecosystems / Dong Chen in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)PermalinkAn implicit radar convolutional burn index for burnt area mapping with Sentinel-1 C-band SAR data / Puzhao Zhang in ISPRS Journal of photogrammetry and remote sensing, Vol 158 (December 2019)PermalinkSpatiotemporal variation in the relationship between boreal forest productivity proxies and climate data / Clémentine Ols in Dendrochronologia, vol 58 (December 2019)PermalinkAccurate 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)PermalinkDeep learning for multi-modal classification of cloud, shadow and land cover scenes in PlanetScope and Sentinel-2 imagery / Yuri Shendryk in ISPRS Journal of photogrammetry and remote sensing, vol 157 (November 2019)PermalinkResidences information extraction from Landsat imagery using the multi-parameter decision tree method / Yujie Yang in Geocarto international, vol 34 n° 14 ([30/10/2019])PermalinkAutomatic canola mapping using time series of Sentinel 2 images / Davoud Ashourloo in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)PermalinkEstimating 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)PermalinkCombining spatiotemporal fusion and object-based image analysis for improving wetland mapping in complex and heterogeneous urban landscapes / Meng Zhang in Geocarto international, vol 34 n° 10 ([15/07/2019])PermalinkMonitoring the structure of forest restoration plantations with a drone-lidar system / D.R.A. Almeida in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)PermalinkA novel method for separating woody and herbaceous time series / Qiang Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)PermalinkUsing LiDAR-modified topographic wetness index, terrain attributes with leaf area index to improve a single-tree growth model in south-eastern Finland / Cheikh Mohamedou in Forestry, an international journal of forest research, vol 92 n° 3 (July 2019)PermalinkLong-term soil moisture content estimation using satellite and climate data in agricultural area of Mongolia / Enkhjargal Natsagdorj in Geocarto international, vol 34 n° 7 ([01/06/2019])PermalinkUsing Sentinel-1A DInSAR interferometry and Landsat 8 data for monitoring water level changes in two lakes in Crete, Greece / D.D. Alexakis in Geocarto international, vol 34 n° 7 ([01/06/2019])Permalink