Descripteur
Termes IGN > 1- Outils - instruments et méthodes > document > document géographique > document cartographique > carte > carte thématique > carte de la végétation
carte de la végétationVoir aussi |
Documents disponibles dans cette catégorie (380)
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
Learning-based spatial-temporal superresolution mapping of forest cover with MODIS images / Yihang Zhang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 1 (January 2017)
[article]
Titre : Learning-based spatial-temporal superresolution mapping of forest cover with MODIS images Type de document : Article/Communication Auteurs : Yihang Zhang, Auteur ; Peter M. Atkinson, Auteur ; Xiaodong Li, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 600 - 614 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] algorithme d'apprentissage
[Termes IGN] carte forestière
[Termes IGN] couvert forestier
[Termes IGN] déboisement
[Termes IGN] données spatiotemporelles
[Termes IGN] image à très haute résolution
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] surveillance forestièreRésumé : (Auteur) Forest mapping from satellite sensor imagery provides important information for the timely monitoring of forest growth and deforestation, bioenergy potential assessment, and modeling of carbon flux, among others. Due to the daily global revisit rate and wide swath width, MODerate-resolution Imaging Spectroradiometer (MODIS) images are used commonly for satellite-derived forest mapping at both regional and global scales. However, the spatial resolution of MODIS images is too coarse to observe fine spatial variation in forest cover. The last few decades have seen the production of several fine-spatial-resolution satellite-derived global forest cover maps, such as Hansen's global tree canopy cover map of 2000, which includes abundant spectral, temporal, and spatial prior information about forest cover at a fine spatial resolution. In this paper, a novel learning-based spatial-temporal superresolution mapping approach is proposed to integrate both current MODIS images and prior maps of Hansen's tree canopy cover, to map present forest cover with a fine spatial resolution. The novel approach is composed of three main stages: 1) automatic generation of 240-m forest proportion images from both 240- and 480-m MODIS images using a nonlinear learning-based spectral unmixing method; 2) downscaling the 240-m forest proportion images to 30 m to predict the class possibilities at the subpixel scale using a temporal-example learning-based downscaling method; and 3) final production of the fine-spatial-resolution forest map by solving a regularization-based optimization problem. The novel approach produced more accurate fine-spatial-resolution forest cover maps in terms of both visual and quantitative evaluation than traditional pixel-based classification and the latest subpixel based superresolution mapping methods. The results show the great efficiency and potential of the novel approach for producing fine-spatial-resolution forest maps from MODIS images. Numéro de notice : A2017-023 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2613140 En ligne : https://doi.org/10.1109/TGRS.2016.2613140 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83955
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 1 (January 2017) . - pp 600 - 614[article]Les prairies de l’estuaire de la Loire : étude de la dynamique de la végétation de 1982 à 2014 / Mathieu Le Dez in Mappemonde, n° 119 (janvier 2017)
[article]
Titre : Les prairies de l’estuaire de la Loire : étude de la dynamique de la végétation de 1982 à 2014 Type de document : Article/Communication Auteurs : Mathieu Le Dez, Auteur ; Jérôme Sawtschuk, Auteur ; Frédéric Bioret, Auteur Année de publication : 2017 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse diachronique
[Termes IGN] boisement naturel
[Termes IGN] carte de la végétation
[Termes IGN] données spatiotemporelles
[Termes IGN] dynamique de la végétation
[Termes IGN] estuaire
[Termes IGN] Loire (bassin)
[Termes IGN] plante halophile
[Termes IGN] prairieRésumé : (Auteur) L’analyse diachronique de cartes de végétation est réalisée pour caractériser les dynamiques de la végétation de l’estuaire de la Loire à différentes échelles spatiales et temporelles. Le modèle des matrices de transition est utilisé pour décrire quantitativement les dynamiques observées. Les analyses révèlent notamment la régression des prairies, le développement des roselières et des boisements ainsi que la progression des végétations halophiles. Ces résultats sont mis en relation avec l’évolution des usages sur ce territoire et les modifications du fonctionnement hydro-sédimentaire de l’estuaire. Numéro de notice : A2017-522 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : sans En ligne : https://doi.org/10.4000/mappemonde.2097 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86539
in Mappemonde > n° 119 (janvier 2017)[article]Assimilation of SMOS retrievals in the land information system / Clay B. Blankenship in IEEE Transactions on geoscience and remote sensing, vol 54 n° 11 (November 2016)
[article]
Titre : Assimilation of SMOS retrievals in the land information system Type de document : Article/Communication Auteurs : Clay B. Blankenship, Auteur ; Jonathan L. Case, Auteur ; Bradley T. Zavodsky, Auteur ; William L. Crosson, Auteur Année de publication : 2016 Article en page(s) : pp 6320 - 6332 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] carte de la végétation
[Termes IGN] Etats-Unis
[Termes IGN] filtre de Kalman
[Termes IGN] humidité du sol
[Termes IGN] image radar
[Termes IGN] image SMOS
[Termes IGN] modèle numérique de surface
[Termes IGN] radiométrie
[Termes IGN] système d'information foncièreRésumé : (Auteur) The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in roughly the upper 5 cm with a 30-50-km resolution and a mission accuracy requirement of 0.04 cm3/cm-3. These observations can be used to improve land surface model (LSM) soil moisture states through data assimilation (DA). In this paper, SMOS soil moisture retrievals are assimilated into the Noah LSM via an Ensemble Kalman Filter within the National Aeronautics and Space Administration Land Information System. Bias correction is implemented using cumulative distribution function (cdf) matching, with points aggregated by either land cover or soil type to reduce the sampling error in generating the cdfs. An experiment was run for the warm season of 2011 to test SMOS DA and to compare assimilation methods. Verification of soil moisture analyses in the 0-10-cm upper layer and the 0-1-m root zone was conducted using in situ measurements from several observing networks in central and southeastern United States. This experiment showed that SMOS DA significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10-cm layer. Time series at specific stations demonstrates the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared with using a simple uniform correction curve. Numéro de notice : A2016-913 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2579604 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2579604 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83135
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 11 (November 2016) . - pp 6320 - 6332[article]Estimating forest species abundance through linear unmixing of CHRIS/PROBA imagery / S. Stagakis in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
[article]
Titre : Estimating forest species abundance through linear unmixing of CHRIS/PROBA imagery Type de document : Article/Communication Auteurs : S. Stagakis, Auteur ; Theofilos Vanikiotis, Auteur ; Olga Sykioti, Auteur Année de publication : 2016 Article en page(s) : pp 79 - 89 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse des mélanges spectraux
[Termes IGN] carte de la végétation
[Termes IGN] classification bayesienne
[Termes IGN] effet d'ombre
[Termes IGN] espèce végétale
[Termes IGN] Fagus sylvatica
[Termes IGN] Grèce
[Termes IGN] image hyperspectrale
[Termes IGN] image Landsat-8
[Termes IGN] image PROBA-CHRIS
[Termes IGN] orthoimage
[Termes IGN] parc naturel national
[Termes IGN] partition d'image
[Termes IGN] Pinus nigra
[Termes IGN] richesse floristique
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) The advancing technology of hyperspectral remote sensing offers the opportunity of accurate land cover characterization of complex natural environments. In this study, a linear spectral unmixing algorithm that incorporates a novel hierarchical Bayesian approach (BI-ICE) was applied on two spatially and temporally adjacent CHRIS/PROBA images over a forest in North Pindos National Park (Epirus, Greece). The scope is to investigate the potential of this algorithm to discriminate two different forest species (i.e. beech – Fagus sylvatica, pine – Pinus nigra) and produce accurate species-specific abundance maps. The unmixing results were evaluated in uniformly distributed plots across the test site using measured fractions of each species derived by very high resolution aerial orthophotos. Landsat-8 images were also used to produce a conventional discrete-type classification map of the test site. This map was used to define the exact borders of the test site and compare the thematic information of the two mapping approaches (discrete vs abundance mapping). The required ground truth information, regarding training and validation of the applied mapping methodologies, was collected during a field campaign across the study site. Abundance estimates reached very good overall accuracy (R2 = 0.98, RMSE = 0.06). The most significant source of error in our results was due to the shadowing effects that were very intense in some areas of the test site due to the low solar elevation during CHRIS acquisitions. It is also demonstrated that the two mapping approaches are in accordance across pure and dense forest areas, but the conventional classification map fails to describe the natural spatial gradients of each species and the actual species mixture across the test site. Overall, the BI-ICE algorithm presented increased potential to unmix challenging objects with high spectral similarity, such as different vegetation species, under real and not optimum acquisition conditions. Its full potential remains to be investigated in further and more complex study sites in view of the upcoming satellite hyperspectral missions. Numéro de notice : A2016-778 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.05.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.05.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82473
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 79 - 89[article]Object-based image mapping of conifer tree mortality in San Diego county based on multitemporal aerial ortho-imagery / Mary Pyott Freeman in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 7 (juillet 2016)
[article]
Titre : Object-based image mapping of conifer tree mortality in San Diego county based on multitemporal aerial ortho-imagery Type de document : Article/Communication Auteurs : Mary Pyott Freeman, Auteur ; Douglas A. Stow, Auteur ; Dar A. Roberts, Auteur Année de publication : 2016 Article en page(s) : pp 571 - 580 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] arbre mort
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] image aérienne
[Termes IGN] image multitemporelle
[Termes IGN] orthoimage
[Termes IGN] Pinophyta
[Termes IGN] San DiegoRésumé : (Auteur) Two GEOBIA approaches are compared for their effectiveness in mapping dead trees within island montane forests of Southern California: a spatial contextual approach using an artificial neural network classifier, and a segmentation and multi-pixel classification approach. Both approaches are tested with multitemporal aerial orthoimagery having varying spatial resolutions. Spectral transformation inputs are also tested. An object-based accuracy assessment is conducted. Accuracies range between 30 percent to 90 percent for the dead tree class and are significantly higher for the spatial-contextual approach. Inclusion of spectral transforms increased accuracies by 5 percent for the true object-based approach, up to 13 percent for the spatial contextual approach, and reduced commission error up to 10 percent for both approaches. Masking techniques increased accuracies of the spatial contextual approach by 20 percent. With manual editing, the most accurate maps of individual live and dead trees from the spatial contextual approach are suitable for studying spatio-temporal trends in montane conifer mortality. Numéro de notice : A2016-518 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.7.571 En ligne : http://dx.doi.org/10.14358/PERS.82.7.571 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81589
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 7 (juillet 2016) . - pp 571 - 580[article]Pan-tropical hinterland forests: mapping minimally disturbed forests / Alexandra Tyukavina in Global ecology and biogeography, vol 25 n° 2 (February 2016)PermalinkAn interactive system for intrinsic validation of citizen science data for species distribution mapping and modelling applications / Hossein Vahidi (2016)PermalinkApport de la télédétection radar satellitaire pour la cartographie de la forêt des Landes / Yousra Hamrouni (2016)PermalinkCanopy density model: A new ALS-derived product to generate multilayer crown cover maps / António Ferraz in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)PermalinkForest cover maps of China in 2010 from multiple approaches and data sources: PALSAR, Landsat, MODIS, FRA, and NFI / Yuanwei Qin in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)PermalinkTélédétection pour l'agriculture de précision par caméra hyperspectrale miniature / D. Constantin in Géomatique suisse, vol 113 n° 9 (septembre 2015)PermalinkTerraSAR-X dual-pol time-series for mapping of wetland vegetation / Julie Betbeder in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)PermalinkApport de modèles numériques de hauteur à l'amélioration de la précision d'inventaires statistiques forestiers / Jean-Pierre Renaud in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)PermalinkCartographie du châtaignier en Alsace par imagerie satellite multi-date / Colette Meyer in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)PermalinkEstimation de la déforestation des forêts humides à Madagascar utilisant une classification multidate d'images Landsat entre 2005, 2010 et 2013 / F.A. Rakotomala in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)PermalinkThe spatiotemporal dynamics of forest–heathland communities over 60 years in Fontainebleau, France / Samira Mobaied in ISPRS International journal of geo-information, vol 4 n°2 (June 2015)PermalinkUse of Landsat and Corona data for mapping forest cover change from the mid-1960s to 2000s: Case studies from the Eastern United States and Central Brazil / Dan-Xia Song in ISPRS Journal of photogrammetry and remote sensing, vol 103 (May 2015)PermalinkCartographie des végétations herbacées des marais littoraux à partir de données topographiques LiDAR / Sébastien Rapinel in Revue Française de Photogrammétrie et de Télédétection, n° 210 (Avril 2015)PermalinkLes séries de végétation de la vallée d’Ascu (Corse) : typologie et cartographie au 1:25 000 / Pauline Delbosc in Ecologia mediterranea, vol 41 n° 1 (2015)PermalinkEtude expérimentale en cartographie de la végétation par télédétection / Vanessa Sellin in Cybergeo, European journal of geography, n° 2015 ([01/01/2015])PermalinkMediterranean forest species mapping using classification of Hyperion imagery / Georgia Galidaki in Geocarto international, vol 30 n° 1 - 2 (January - February 2015)PermalinkThe potential of Pléiades imagery for vegetation mapping: a case study of plain and mountainous open environments / Vincent Thierion in Revue Française de Photogrammétrie et de Télédétection, n° 208 (Octobre 2014)PermalinkExigence et cartes de vigilance climatique des chênes pédonculé, sessiles et pubescent. / Jean Lemaire in Forêt entreprise, n° 218 (septembre-octobre 2014)PermalinkCrop type classification by simultaneous use of satellite images of different resolutions / Mark W. Liu in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)PermalinkCaractérisation et cartographie de la structure forestière à partir d'images satellitaires à très haute résolution spatiale / Benoit Beguet (2014)Permalink