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Mapping burned areas and land-uses in Kangaroo Island using an object-based image classification framework and Landsat 8 Imagery from Google Earth Engine / Jiyu Liu in Geomatics, Natural Hazards and Risk, vol 13 (2022)
[article]
Titre : Mapping burned areas and land-uses in Kangaroo Island using an object-based image classification framework and Landsat 8 Imagery from Google Earth Engine Type de document : Article/Communication Auteurs : Jiyu Liu, Auteur ; David Freudenberger, Auteur ; Lim Samsung, Auteur Année de publication : 2022 Article en page(s) : pp 1867 - 1897 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse spectrale
[Termes IGN] approche hiérarchique
[Termes IGN] Australie
[Termes IGN] carte thématique
[Termes IGN] écosystème forestier
[Termes IGN] Google Earth Engine
[Termes IGN] image infrarouge
[Termes IGN] image Landsat-8
[Termes IGN] incendie
[Termes IGN] Indien (océan)
[Termes IGN] segmentation d'image
[Termes IGN] utilisation du sol
[Termes IGN] zone sinistréeRésumé : (auteur) In Australia, fire has become part of the natural ecosystem. Severe fires have devastated Australia's unique forest ecosystems due to the global climate change. In this study, we integrated a multi-resolution segmentation method and a hierarchical classification framework based on expert-based knowledge to classify the burned areas and land-uses in Kangaroo Island, South Australia. Using an object-based image classification framework that combines colour and shape features from input layers, we demonstrated that the objects segmented from the multi-source data lead to a higher accuracy in classification with an overall accuracy of 90.2% and a kappa coefficient of 85.2%. On the other hand, the single source data from post-fire Landsat-8 imagery showed an overall accuracy of 87.4% which is also statistically acceptable. According to our experiment results, more than 30.44% of the study area was burned during the 2019–2020 ‘Black-Summer’ fire season in Australia. Among the burned areas, high severity accounted for 12.14%, moderate severity for 11.48%, while low severity was 6.82%. For unburned areas, farmland accounted for 45.52% of the study area, of which about one-third was affected by the disturbances other than fire. The remaining area consists of 19.42% unaffected forest, 3.48% building and bare land, and 1.14% water. The comparison analysis shows that our object-based image classification framework takes full advantage of the multi-source data and generates the edges of burned areas more clearly, which contributes to the improved fire management and control. Numéro de notice : A2022-873 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/19475705.2022.2098066 Date de publication en ligne : 02/08/2022 En ligne : https://doi.org/10.1080/19475705.2022.2098066 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102171
in Geomatics, Natural Hazards and Risk > vol 13 (2022) . - pp 1867 - 1897[article]Le mémento inventaire forestier, édition 2021 / Institut national de l'information géographique et forestière (2012 -) (2022)
Titre : Le mémento inventaire forestier, édition 2021 Type de document : Rapport Auteurs : Institut national de l'information géographique et forestière (2012 -), Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2022 Importance : 40 p. Format : 11 x 25 cm Langues : Français (fre) Descripteur : [Termes IGN] bois mort
[Termes IGN] bois sur pied
[Termes IGN] écosystème forestier
[Termes IGN] France (administrative)
[Termes IGN] France d'outre-mer
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] ressources forestières
[Vedettes matières IGN] Inventaire forestierIndex. décimale : 48.20 Inventaire forestier Résumé : (Editeur) Le mémento de l’inventaire forestier – édition 2021 – rassemble dans 40 pages les principaux chiffres, cartes et informations sur la forêt française issus des campagnes d’inventaire 2016 à 2020 de l’IGN. Note de contenu : SURFACES FORESTIERES
La forêt en Outre-Mer
La forêt en France métropolitaine
L'augmentation de la surface forestière
Le taux de boisement
À qui la forêt appartient-elle ?
ECOSYSTEMES FORESTIERS
La santé des forêts
La diversité des peuplements
La composition des peuplements
Le bois mort sur pied
Le bois mort au sol
La répartition de quelques plantes
RESSOURCES FORESTIERES
Le bois vivant sur pied
L'augmentation de la ressource
Informations sur les principales essences
La production biologique annuelle
Les prélèvements de bois
Quelques données régionalesNuméro de notice : 17695 Affiliation des auteurs : IGN (2020- ) Thématique : FORET Nature : Rapport statistique nature-HAL : Rapport DOI : sans En ligne : https://inventaire-forestier.ign.fr/spip.php?article583= Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99508 Voir aussi
- Le mémento inventaire forestier, édition 2018 / Institut national de l'information géographique et forestière (2012 -) (2018)
- Le mémento inventaire forestier, édition 2017 / Institut national de l'information géographique et forestière (2012 -) (2017)
- Le mémento inventaire forestier, édition 2019 / Institut national de l'information géographique et forestière (2012 -) (2019)
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mémento inventaire forestier, édition 2021Adobe Acrobat PDF Monitoring forest-savanna dynamics in the Guineo-Congolian transition area of the centre region of Cameroon / Le Bienfaiteur Sagang Takougoum (2022)
Titre : Monitoring forest-savanna dynamics in the Guineo-Congolian transition area of the centre region of Cameroon Type de document : Thèse/HDR Auteurs : Le Bienfaiteur Sagang Takougoum, Auteur ; Bonaventure Sonké, Directeur de thèse ; Nicolas Barbier, Directeur de thèse Editeur : Yaoundé : Université de Yaoundé Année de publication : 2022 Importance : 166 p. Format : 21 x 30 cm Note générale : Bibliographie
Thèse pour obtenir le grade de Docteur de l'Université de Yaoundé 1, Spécialité Botanique-EcologieLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse aérienne
[Termes IGN] Cameroun
[Termes IGN] carte d'utilisation du sol
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] dynamique de la végétation
[Termes IGN] écotone
[Termes IGN] flore locale
[Termes IGN] forêt
[Termes IGN] Google Earth Engine
[Termes IGN] image Landsat
[Termes IGN] image SPOT 6
[Termes IGN] image SPOT 7
[Termes IGN] incendie de forêt
[Termes IGN] modèle statistique
[Termes IGN] savane
[Termes IGN] surveillance forestièreIndex. décimale : THESE Thèses et HDR Résumé : (Auteur) Understanding the effects of global change (combining anthropic and climatic pressures) on biome distribution needs innovative approaches allowing to address the large spatial scales involved and the scarcity of available ground data. Characterizing vegetation dynamics at landscape to regional scale requires both a high level of spatial detail (resolution), generally obtained through precise field measurements, and a sufficient coverage of the land surface (extent) provided by satellite images. The difficulty usually lies between these two scales as both signal saturation from satellite data and ground sampling limitations contribute to inaccurate extrapolations. Airborne laser scanning (ALS) data has revolutionized the trade-off between spatial detail and landscape coverage as it gives accurate information of the vegetation’s structure over large areas which can be used to calibrate satellite data. Also recent satellite data of improved spectral and spatial resolutions (Sentinel 2) allow for detailed characterizations of compositional gradients in the vegetation, notably in terms of the abundance of broad functional/optical plant types. Another major obstacle comes from the lack of a temporal perspective on dynamics and disturbances. Growing satellite imagery archives over several decades (45 years; Landsat) and available computing facilities such as Google Earth Engine (GEE) provide new possibilities to track long term successional trajectories and detect significant disturbances (i.e. fire) at a fine spatial detail (30m) and relate them to the current structure and composition of the vegetation. With these game changing tools our objective was to track long-term dynamics of forest-savanna ecotone in the Guineo-Congolian transition area of the Central Region of Cameroon with induced changes in the vegetatio structure and composition within two contrasted scenarios of anthropogenic pressures: 1) the Nachtigal area which is targeted for the dam construction and subject to intense agricultural activities and 2) the Mpem et Djim National Park (MDNP) which has no management plan. The maximum likelihood classification of the Spot 6/7 image aided with the information from the canopy height derived from ALS data discriminated the vegetation types within the Nachtigal area with good accuracy (96.5%). Using field plots data in upscaling aboveground biomass (AGB) form field plots estimates to the satellite estimates with model-based approaches lead to a systematic overestimation in AGB density estimates and a root mean squared prediction error (RMSPE) of up to 65 Mg.ha−1 (90%), whereas calibration with ALS data (AGBALS) lead to low bias and a drop of ~30% in RMSPE (down to 43 Mg.ha−1, 58%) with little effect of the satellite sensor used. However, these results also confirm that, whatever the spectral indices used and attention paid to sensor quality and pre-processing, the signal is not sufficient to warrant accurate pixel wise predictions, because of large relative RMSPE, especially above (200–250 Mg.ha−1). The design-based approach, for which average AGB density values were attributed to mapped land cover classes, proved to be a simple and reliable alternative (for landscape to region level estimations), when trained with dense ALS samples. AGB and species diversity measured within 74 field inventory plots (distributed along a savanna to forest successional gradient) were higher for the vegetation located in the MDNP compared to their pairs in the Nachtigal area. The automated unsupervised long-term (45 years) land cover change monitoring from Landsat image archives based on GEE captured a consistent and regular pattern of forest progression into savanna at an average rate of 1% (ca. 6 km².year-1). No fire occurrence was captured for savanna that transited to forest within five years of monitoring. Distinct assemblages of spectral species are apparent in forest vegetation which is consistent with the age of transition. As forest gets older AGBALS recovers at a rate of 4.3 Mg.ha-1.year-1 in young forest stands ( Note de contenu : Chapter 1. Generalities
1.1 Introduction
1.2 Literature Review
Chapter 2. Material And Methods
2.1 Material
2.2 Methods
Chapter 3. Results And Discussion
3.1 Results
3.2 Discussion
Chapter 4. Conclusion And Perspectives
4.1 Conclusion
4.2 PerspectivesNuméro de notice : 26820 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Thèse étrangère Note de thèse : Thèse de doctorat : Botanique-Ecologie : Yaoundé : 2022 Organisme de stage : Institut de Recherche pour le Développement IRD nature-HAL : Thèse DOI : sans Date de publication en ligne : 13/04/2022 En ligne : https://hal.inrae.fr/tel-03528875/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100465 Regeneration of spruce - fir - beech mixed forests under climate and ungulate pressure / Mithila Unkule (2022)
Titre : Regeneration of spruce - fir - beech mixed forests under climate and ungulate pressure Titre original : Régénération des forêts mixtes épicéa - sapin - hêtre sous la pression du climat et des ongulés Type de document : Thèse/HDR Auteurs : Mithila Unkule, Auteur ; Benoît Courbaud, Directeur de thèse ; Philippe Balandier, Directeur de thèse Editeur : Grenoble [France] : Université Grenoble Alpes Année de publication : 2022 Importance : pp 207 Format : 21 x 30 cm Note générale : bibliographie
Thèse pour obtenir le grade de Docteur de l'Université Grenoble Alpes, Spécialité Biodiversité, Ecologie, EnvironnementLangues : Anglais (eng) Descripteur : [Termes IGN] Abies alba
[Termes IGN] Alpes (France)
[Termes IGN] altitude
[Termes IGN] aménagement forestier
[Termes IGN] Cervidae
[Termes IGN] dynamique de la végétation
[Termes IGN] écologie forestière
[Termes IGN] Fagus sylvatica
[Termes IGN] forêt inéquienne
[Termes IGN] gestion forestière durable
[Termes IGN] jeune arbre
[Termes IGN] Jura, massif du
[Termes IGN] pente
[Termes IGN] Picea abies
[Termes IGN] régénération (sylviculture)
[Vedettes matières IGN] Végétation et changement climatiqueIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Global environmental changes are affecting tree population demography with potentially significant impacts on forest biodiversity and wood industry. Forest regeneration processes include seed production, growth and survival of saplings to the recruitment sizes at which trees are considered in forest inventories. Changes in regeneration dynamics directly affect forest composition and structure and can jeopardize the sustainability of forest management. This is especially the case in mountain forests where environmental gradients are strong and where forests are often uneven-aged, i.e. combining trees of all ages in a single stand. Regeneration processes are difficult to monitor. Large data sets often give only fixed pictures of sapling densities with little information on demographic processes. In this thesis, we quantified the effects of different biotic and abiotic factors on regeneration dynamics of Picea abies (spruce), Abies alba (fir) and Fagus sylvatica (beech) in the French Alps and Jura mountains. We also predicted changes in tree recruitment fluxes in these forests, for potential climate change situations. We recorded sapling height increment and density of spruce, fir and beech in 152 plots across the French Alps and Jura mountains. We then analysed how biotic and abiotic factors known to affect regeneration, namely altitude, slope, aspect, light availability, soil characteristics, ungulate browsing, temperature, precipitation and evapotranspiration, affected sapling density and growth using non-linear mixed models. We showed that temperature has a positive non-linear effect on sapling height growth and water resource availability has a positive effect on sapling density. Terminal shoot browsing, which prevents sapling height growth, is especially frequent on fir. In a second analysis, we built a more comprehensive model of regeneration dynamics, representing explicitly the process of new seedling production, sapling growth, browsing and survival, and finally their recruitment into adult trees. We predicted parameters for these processes in combination, using Approximate Bayesian Computation (ABC), based on the field data collected earlier. The results imply that more frequent and intense heat and drought events could negatively influence sapling growth and survival of the three species, with probable reduction of forest renewal fluxes. An increase of ungulate populations leading to increased browsing could be especially detrimental to fir and possibly also to beech saplings. We also predicted the potential tree recruitment fluxes for different IPCC climate projection scenarios for the year 2100, and showed that a reduction in tree recruitments is highly likely. This study shows that the ABC method can be efficiently used to estimate regeneration dynamic processes, based on sapling density, height increment and browsing data. It highlights the vulnerability of future forest regeneration to water availability and ungulate presence, urging researchers and forest managers alike to anticipate future potential important changes in mountain forest dynamics. Note de contenu : 1- Introduction
2- Theoretical framework
3- Spruce-fir-beech regeneration in French Alps
4- Estimating regeneration processes and tree recruitment rates
5- Discussion and perspectives
6- ConclusionsNuméro de notice : 15288 Affiliation des auteurs : non IGN Thématique : FORET Nature : Thèse française Note de thèse : Thèse de Doctorat : Biodiversité, Ecologie, Environnement : Grenoble : 2022 Organisme de stage : Laboratoire des EcoSystèmes et des Sociétés en Montagne DOI : sans En ligne : https://tel.hal.science/tel-03722811 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101511
Titre : Remote sensing in applications of geoinformation Type de document : Monographie Auteurs : Silas Michaelides, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2022 Importance : 174 p. ISBN/ISSN/EAN : 978-3-0365-2325-5 Note générale : Bibliographie
This book is a printed edition of the Special Issue Remote Sensing in Applications of Geoinformation that was published in Remote SensingLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] cartographie des risques
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] écosystème forestier
[Termes IGN] écosystème urbain
[Termes IGN] image Sentinel-MSI
[Termes IGN] inondation
[Termes IGN] modèle 3D de l'espace urbainIndex. décimale : 35.40 Applications de télédétection - généralités Résumé : (Editeur) Remote sensing, especially from satellites, is a source of invaluable data which can be used to generate synoptic information for virtually all parts of the Earth, including the atmosphere, land, and ocean. In the last few decades, such data have evolved as a basis for accurate information about the Earth, leading to a wealth of geoscientific analysis focusing on diverse applications. Geoinformation systems based on remote sensing are increasingly becoming an integral part of the current information and communication society. The integration of remote sensing and geoinformation essentially involves combining data provided from both, in a consistent and sensible manner. This process has been accelerated by technologically advanced tools and methods for remote sensing data access and integration, paving the way for scientific advances in a broadening range of remote sensing exploitations in applications of geoinformation. This volume hosts original research focusing on the exploitation of remote sensing in applications of geoinformation. The emphasis is on a wide range of applications, such as the mapping of soil nutrients, detection of plastic litter in oceans, urban microclimate, seafloor morphology, urban forest ecosystems, real estate appraisal, inundation mapping, and solar potential analysis. Note de contenu : - Vis-NIR Spectroscopy and Satellite Landsat-8 OLI Data to Map Soil Nutrients in Arid Conditions: A Case Study of the Northwest Coast of Egypt / Elsayed Said Mohamed, A. A El Baroudy, T. El-beshbeshy, M. Emam, A. A. Belal, Abdelaziz Elfadaly, Ali A. Aldosari, Abdelraouf. M. Ali and Rosa Lasaponara
- Investigating Detection of Floating Plastic Litter from Space Using Sentinel-2 Imagery / Kyriacos Themistocleous, Christiana Papoutsa, Silas Michaelides and Diofantos Hadjimitsis
- A New Approach for Understanding Urban Microclimate by Integrating Complementary Predictors at Different Scales in Regression and Machine Learning Models /8 Lucille Alonso and Florent Renard
- Automatic Pattern Recognition of Tectonic Lineaments in Seafloor Morphology to Contribute in the Structural Analysis of Potentially Hydrocarbon-Rich Areas / Eleni Kokinou and Costas Panagiotakis
- Integrating Remote Sensing and Street View Images to Quantify Urban Forest Ecosystem Services / Elena Barbierato, Iacopo Bernetti, Irene Capecchi and Claudio Saragosa
- Sensitivity Analysis of Machine Learning Models for the Mass Appraisal of Real Estate. Case Study of Residential Units in Nicosia, Cyprus / Thomas Dimopoulos, Nikolaos P. Bakas
- Automatic Inundation Mapping Using Sentinel-2 Data Applicable to Both Camargue and Donana Biosphere Reserves / Georgios A. Kordelas, Ioannis Manakos, Gaëtan Lefebvre and Brigitte Poulin
- The Application of LiDAR Data for the Solar Potential Analysis Based on Urban 3D Model / I˜naki Prieto, Jose Luis Izkara and Elena UsobiagaNuméro de notice : 26796 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/URBANISME Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-2326-2 En ligne : https://doi.org/10.3390/books978-3-0365-2326-2 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100057 SenRVM: A multi-modal deep learning regression methodology for continuous vegetation monitoring with dense temporal NDVI time series / Anatol Garioud (2022)PermalinkPermalinkVegetation changes in the understory of nitrogen-sensitive temperate forests over the past 70 years / Marina Roth in Forest ecology and management, vol 503 (January-1 2022)PermalinkPermalinkThe efficiency of retention measures in continuous-cover forestry for conserving epiphytic cryptogams: A case study on Abies alba / Stefan Kaufmann in Forest ecology and management, vol 502 (December-15 2021)PermalinkClimate warming-induced replacement of mesic beech by thermophilic oak forests will reduce the carbon storage potential in aboveground biomass and soil / Jan Kasper in Annals of Forest Science, vol 78 n° 4 (December 2021)PermalinkDrought in the forest breaks plant–fungi interactions / Andrzej Boczoń in European Journal of Forest Research, vol 140 n° 6 (December 2021)PermalinkExtensification and afforestation of cultivated mineral soil for climate change mitigation in Finland / Boris Tupek in Forest ecology and management, vol 501 (December-1 2021)PermalinkPrescribed burning as a cost-effective way to address climate change and forest management in Mediterranean countries / Renata Martins Pacheco in Annals of Forest Science, vol 78 n° 4 (December 2021)PermalinkForest type matters: Global review about the structure of oak dominated old-growth temperate forests / Janos Bölöni in Forest ecology and management, vol 500 (November-15 2021)PermalinkInflation of wood resources in European forests: The footprints of a big-bang / Jean-Daniel Bontemps in Plos one, vol 16 n° 11 (November 2021)PermalinkQuels besoins de connaissances pour le futur des forêts en France ? Au-delà du plan de relance / Maya Leroy in Revue forestière française, vol 73 n° 1 (2021)PermalinkVariation in plant–soil interactions among temperate forest herbs / Jared J. Beck in Plant ecology, vol 222 n° 11 (November 2021)PermalinkThe impact of air pollution on the growth of scots pine stands in poland on the basis of dendrochronological analyses / Longina Chojnacka-Ożga in Forests, vol 12 n° 10 (October 2021)PermalinkVariation in downed deadwood density, biomass, and moisture during decomposition in a natural temperate forest / Tomas Přívětivý in Forests, vol 12 n° 10 (October 2021)PermalinkModeling in forestry using mixture models fitted to grouped and ungrouped data / Eric K. Zenner in Forests, vol 12 n° 9 (September 2021)PermalinkForest floor bryophyte and lichen diversity in Scots pine and Norway spruce production forests / Lisa Petersson in Forest ecology and management, vol 493 (August-1 2021)PermalinkForest inventory-based assessments of the invasion risk of Pseudotsuga menziesii (Mirb.) Franco and Quercus rubra L. in Germany / A. Bindewald in European Journal of Forest Research, vol 140 n° 4 (August 2021)PermalinkClimate warming predispose sessile oak forests to drought-induced tree mortality regardless of management legacies / Any Mary Petritan in Forest ecology and management, vol 491 (July-1 2021)PermalinkAltimétrie laser et surveillance / Laurent Polidori in Géomètre, n° 2192 (juin 2021)Permalink