Descripteur
Termes IGN > imagerie > image spatiale > image satellite > image Sentinel > image Sentinel-MSI
image Sentinel-MSISynonyme(s)image sentinel-2Voir aussi |
Documents disponibles dans cette catégorie (266)
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
A LiDAR–optical data fusion approach for identifying and measuring small stream impoundments and dams / Benjamin Swan in Transactions in GIS, Vol 24 n° 1 (February 2020)
[article]
Titre : A LiDAR–optical data fusion approach for identifying and measuring small stream impoundments and dams Type de document : Article/Communication Auteurs : Benjamin Swan, Auteur ; Robert Griffin, Auteur Année de publication : 2020 Article en page(s) : pp 174 - 188 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] Alabama (Etats-Unis)
[Termes IGN] barrage
[Termes IGN] cours d'eau
[Termes IGN] données lidar
[Termes IGN] écosystème
[Termes IGN] fusion de données
[Termes IGN] image à haute résolution
[Termes IGN] image optique
[Termes IGN] image Sentinel-MSI
[Termes IGN] modèle numérique de surface
[Termes IGN] Normalized Difference Water Index
[Termes IGN] ressources en eau
[Termes IGN] semis de points
[Termes IGN] surveillance hydrologique
[Termes IGN] système d'information géographiqueRésumé : (auteur) This article outlines a semi‐autonomous approach for using a fusion of light detection and ranging (LiDAR) and optical remote sensing data to identify and measure small impoundments (SIs) and their dams. Quantifying such water bodies as hydrologic network features is critical for ecosystem and species conservation, emergency management, and water resource planning; however, such features are incompletely mapped at national and state levels. By merging an airborne LiDAR‐derived point cloud with a normalized water index using airborne optical imagery we demonstrate an improvement upon single‐source methods for identifying these water bodies; classification accuracies increased over 10% by using this multi‐source fusion method. Furthermore, the method presented here illustrates a cost‐effective pathway to improve the National Inventory of Dams (NID) and includes a framework for estimating dam heights, with results showing strong correlations between derived dam heights and those recorded in the NID (r=.78). With the steady increase in available LiDAR coverage, the 87,000+ dams in the NID could be updated using this technique, a method which could also be expanded for global inventories of SIs and dams. Numéro de notice : A2020-103 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12595 Date de publication en ligne : 13/11/2019 En ligne : https://doi.org/10.1111/tgis.12595 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94694
in Transactions in GIS > Vol 24 n° 1 (February 2020) . - pp 174 - 188[article]Multi-Spatial Resolution Satellite and sUAS Imagery for Precision Agriculture on Smallholder Farms in Malawi / Brad G. Peter in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 2 (February 2020)
[article]
Titre : Multi-Spatial Resolution Satellite and sUAS Imagery for Precision Agriculture on Smallholder Farms in Malawi Type de document : Article/Communication Auteurs : Brad G. Peter, Auteur ; Joseph P. Messina, Auteur ; Jon W. Carroll, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 107 - 119 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] agriculture de précision
[Termes IGN] analyse multirésolution
[Termes IGN] exploitation agricole
[Termes IGN] image Pléiades
[Termes IGN] image Sentinel-MSI
[Termes IGN] image SPOT 6
[Termes IGN] MalawiRésumé : (Auteur) A collection of spectral indices, derived from a range of remote sensing imagery spatial resolutions, are compared to on-farm measurements of maize chlorophyll content and yield at two trial farms in central Malawi to evaluate what spatial resolutions are most effective for relating multispectral images with crop status. Single and multiple linear regressions were tested for spatial resolutions ranging from 7 cm to 20 m using a small unmanned aerial system (sUAS) and satellite imagery from Planet, SPOT 6, Pléiades, and Sentinel-2. Results suggest that imagery with spatial resolutions nearer the maize plant scale (i.e., 14–27 cm) are most effective for relating spectral signals with crop health on smallholder farms in Malawi. Consistent with other studies, green-band indices were more strongly correlated with maize chlorophyll content and yield than conventional red-band indices, and multivariable models often outperformed single variable models. Numéro de notice : A2020-127 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.2.107 Date de publication en ligne : 01/02/2020 En ligne : https://doi.org/10.14358/PERS.86.2.107 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94796
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 2 (February 2020) . - pp 107 - 119[article]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 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]Extracting soil salinization information with a fractional-order filtering algorithm and grid-search support vector machine (GS-SVM) model / Xiaoping Wang in International Journal of Remote Sensing IJRS, vol 41 n° 3 (15 - 22 janvier 2020)PermalinkApplication of geographic Information system and remote sensing in multiple criteria analysis to identify priority areas for biodiversity conservation in Vietnam / Xuan Dinh Vu (2020)PermalinkCartographie des essences forestières à partir de séries temporelles d’images satellitaires à hautes résolutions : stabilité des prédictions, autocorrélation spatiale et cohérence avec la phénologie observée in situ / Nicolas Karasiak (2020)PermalinkClassification of poplar trees with object-based ensemble learning algorithms using Sentinel-2A imagery / H. Tombul in Journal of geodetic science, vol 10 n° 1 (January 2020)PermalinkClassification of time series of Sentinel-2 images for large scale mapping in Cameroon / Hermann Tagne (2020)PermalinkComparison of multi-seasonal Landsat 8, Sentinel-2 and hyperspectral images for mapping forest alliances in Northern California / Matthew L. Clark in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)PermalinkEstimation et suivi de la ressource en bois en France métropolitaine par valorisation des séries multi-temporelles à haute résolution spatiale d'images optiques (Sentinel-2) et radar (Sentinel-1, ALOS-PALSAR) / David Morin (2020)PermalinkEtudes des dynamiques spatiales d’évolution de l’occupation et de l’utilisation des sols dans la fenêtre lacustre camerounaise du lac Tchad et son arrière-pays à partir des grandes sécheresses sahéliennes de 1970 / Paul Gérard Gbetkom (2020)PermalinkPermalinkNational scale identification and characterization of braided rivers in New Zealand using Google Earth Engine / Alexis Jean (2020)Permalink