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Auteur Valéry Gond |
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Affiner la recherche Interroger des sources externesQuels 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)
Titre : Quels besoins de connaissances pour le futur des forêts en France ? Au-delà du plan de relance Type de document : Article/Communication Auteurs : Maya Leroy, Auteur ; Jean-Daniel Bontemps Année de publication : 2021 Projets : 1-Pas de projet / Article en page(s) : pp 7 - 19 Note générale : bibliographie Langues : Français (fre) Descripteur : [Termes IGN] acquisition de connaissances
[Termes IGN] acteurs de la filière bois-forêt
[Termes IGN] changement climatique
[Termes IGN] conservation des ressources forestières
[Termes IGN] dynamique de la végétation
[Termes IGN] enjeu
[Termes IGN] forêt
[Termes IGN] France (administrative)
[Termes IGN] protection de la biodiversité
[Termes IGN] service écosystémique
[Termes IGN] territoire
[Vedettes matières IGN] ForesterieRésumé : (auteur) Le plan France Relance lancé en septembre 2020 prévoit des mesures forestières sur 2 ans, avec un accent sur la reconstitution des peuplements forestiers sinistrés, affaiblis par les sécheresses ou attaqués par les scolytes. Cependant la crise forestière liée au changement climatique est partie pour durer et les efforts sur les connaissances à acquérir pour aider la forêt à s’adapter au changement climatique devront être poursuivis sur le long terme. Nous identifions quatre enjeux principaux, fortement liés à la préservation de la biodiversité : 1) S’assurer des conditions de succès d’établissement des forêts plantées. 2) Tirer parti des dynamiques naturelles et de la biodiversité pour limiter les risques. 3) Raisonner territorialement, impliquer davantage les acteurs. 4) Connecter les enjeux nationaux aux enjeux économiques mondiaux. Numéro de notice : A2021-794 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : BIODIVERSITE/FORET Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.20870/revforfr.2021.4992 En ligne : https://doi.org/10.20870/revforfr.2021.4992 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99092
in Revue forestière française > vol 73 n° 1 (2021) . - pp 7 - 19[article]Documents numériques
en open access
Quels besoins de connaissances pour le futur des forêts en France - pdf éditeurAdobe Acrobat PDF
Titre : Automatic detection of inland water bodies along altimetry tracks for estimating surface water storage variations in the Congo basin Type de document : Article/Communication Auteurs : Frédéric Frappart, Auteur ; Pierre Zeiger, Auteur ; Julie Betbeder, Auteur ; Valéry Gond, Auteur ; Régis Bellot Année de publication : 2021 Projets : TOSCA / Article en page(s) : n° 3804 Note générale : bibliographie
This research was funded by CNES TOSCA grants number CASCHMIR and SWHYM.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] classification par nuées dynamiques
[Termes IGN] Congo (bassin)
[Termes IGN] détection automatique
[Termes IGN] données altimétriques
[Termes IGN] eau de surface
[Termes IGN] estimation statistique
[Termes IGN] image Envisat-ASAR
[Termes IGN] image Jason-AMR
[Termes IGN] niveau de l'eau
[Termes IGN] série temporelle
[Termes IGN] stockage
[Termes IGN] volume d'eau
[Termes IGN] zone humideRésumé : (auteur) Surface water storage in floodplains and wetlands is poorly known from regional to global scales, in spite of its importance in the hydrological and the carbon balances, as the wet areas are an important water compartment which delays water transfer, modifies the sediment transport through sedimentation and erosion processes, and are a source for greenhouse gases. Remote sensing is a powerful tool for monitoring temporal variations in both the extent, level, and volume, of water using the synergy between satellite images and radar altimetry. Estimating water levels over flooded area using radar altimetry observation is difficult. In this study, an unsupervised classification approach is applied on the radar altimetry backscattering coefficients to discriminate between flooded and non-flooded areas in the Cuvette Centrale of Congo. Good detection of water (open water, permanent and seasonal inundation) is above 0.9 using radar altimetry backscattering from ENVISAT and Jason-2. Based on these results, the time series of water levels were automatically produced. They exhibit temporal variations in good agreement with the hydrological regime of the Cuvette Centrale. Comparisons against a manually generated time series of water levels from the same missions at the same locations show a very good agreement between the two processes (i.e., RMSE ≤ 0.25 m in more than 80%/90% of the cases and R ≥ 0.95 in more than 95%/75% of the cases for ENVISAT and Jason-2, respectively). The use of the time series of water levels over rivers and wetlands improves the spatial pattern of the annual amplitude of water storage in the Cuvette Centrale. It also leads to a decrease by a factor of four for the surface water estimates in this area, compared with a case where only time series over rivers are considered. Numéro de notice : A2021-935 Affiliation des auteurs : IGN+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13193804 Date de publication en ligne : 23/09/2021 En ligne : https://doi.org/10.3390/rs13193804 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99542
in Remote sensing > vol 13 n° 19 (October-1 2021) . - n° 3804[article]
Titre : Mapping ecosystem services at the regional scale: the validity of an upscaling approach Type de document : Article/Communication Auteurs : Solen Le Clec'h, Auteur ; Sean Sloan, Auteur ; Valéry Gond, Auteur ; Guillaume Cornu, Auteur ; Thibaud Decaens, Auteur ; Simon Dufour, Auteur ; Michel Grimaldi, Auteur ; Johan Oszwald, Auteur Année de publication : 2018 Article en page(s) : pp 1593 - 1610 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] caractérisation
[Termes IGN] carte thématique
[Termes IGN] image Landsat
[Termes IGN] image Terra-MODIS
[Termes IGN] indicateur environnemental
[Termes IGN] Para (Brésil)
[Termes IGN] puits de carbone
[Termes IGN] service écosystémiqueRésumé : (auteur) Mapping ecosystem services (ES) over large scales is important for environmental monitoring but is often prohibitively expensive and difficult. We test a hybrid, low-cost method of mapping ES indicators over large scales in Pará State, Brazil. Four ES indicators (vegetation carbon stocks, biodiversity index, soil chemical quality index and rates of water infiltration into soil) were measured in the field and then summarized spatially for regional land-cover classes derived from satellite imagery. The regionally mapped ES values correlated strongly with independent and local measures of ES. For example, regional estimates of the vegetation carbon stocks are strongly correlated with actual measures derived from field samples and validation data (significant anova test – p-value = 4.51e−9) and differed on average by only 20 Mg/ha from the field data. Our spatially-nested approach provides reliable and accurate maps of ES at both local and regional scales. Local maps account for the specificities of an area while regional maps provide an accurate generalization of an ES’ state. Such up-scaling methods infuse large-scale ES maps with localized data and enable the estimation of uncertainty of at regional scales. Our approach is first step towards the spatial characterization of ES at large and potentially global scales. Numéro de notice : A2018-283 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/13658816.2018.1445256 Date de publication en ligne : 22/03/2018 En ligne : https://doi.org/10.1080/13658816.2018.1445256 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90367
in International journal of geographical information science IJGIS > vol 32 n° 7-8 (July - August 2018) . - pp 1593 - 1610[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2018041 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Aboveground biomass mapping in French Guiana by combining remote sensing, forest inventories and environmental data Type de document : Article/Communication Auteurs : Ibrahim Fayad, Auteur ; Nicolas Baghdadi, Auteur ; Stéphane Guitet Année de publication : 2016 Article en page(s) : pp 502 - 514 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse aérienne
[Termes IGN] données environnementales
[Termes IGN] données ICEsat
[Termes IGN] forêt tropicale
[Termes IGN] Guyane (département français)
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] régressionRésumé : (auteur) Mapping forest aboveground biomass (AGB) has become an important task, particularly for the reporting of carbon stocks and changes. AGB can be mapped using synthetic aperture radar data (SAR) or passive optical data. However, these data are insensitive to high AGB levels (>150 Mg/ha, and >300 Mg/ha for P-band), which are commonly found in tropical forests. Studies have mapped the rough variations in AGB by combining optical and environmental data at regional and global scales. Nevertheless, these maps cannot represent local variations in AGB in tropical forests. In this paper, we hypothesize that the problem of misrepresenting local variations in AGB and AGB estimation with good precision occurs because of both methodological limits (signal saturation or dilution bias) and a lack of adequate calibration data in this range of AGB values. We test this hypothesis by developing a calibrated regression model to predict variations in high AGB values (mean >300 Mg/ha) in French Guiana by a methodological approach for spatial extrapolation with data from the optical geoscience laser altimeter system (GLAS), forest inventories, radar, optics, and environmental variables for spatial inter- and extrapolation. Given their higher point count, GLAS data allow a wider coverage of AGB values. We find that the metrics from GLAS footprints are correlated with field AGB estimations (R2 = 0.54, RMSE = 48.3 Mg/ha) with no bias for high values. First, predictive models, including remote-sensing, environmental variables and spatial correlation functions, allow us to obtain “wall-to-wall” AGB maps over French Guiana with an RMSE for the in situ AGB estimates of ∼50 Mg/ha and R2 = 0.66 at a 1-km grid size. We conclude that a calibrated regression model based on GLAS with dependent environmental data can produce good AGB predictions even for high AGB values if the calibration data fit the AGB range. We also demonstrate that small temporal and spatial mismatches between field data and GLAS footprints are not a problem for regional and global calibrated regression models because field data aim to predict large and deep tendencies in AGB variations from environmental gradients and do not aim to represent high but stochastic and temporally limited variations from forest dynamics. Thus, we advocate including a greater variety of data, even if less precise and shifted, to better represent high AGB values in global models and to improve the fitting of these models for high values. Numéro de notice : A2016--202 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2016.07.015 Date de publication en ligne : 01/08/2016 En ligne : https://doi.org/10.1016/j.jag.2016.07.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96037
in International journal of applied Earth observation and geoinformation > vol 52 (October 2016) . - pp 502 - 514[article]
Titre : Regional scale rain-forest height mapping using regression-kriging of spaceborne and airborne Lidar data: application on French Guiana Type de document : Article/Communication Auteurs : Ibrahim Fayad, Auteur ; Nicolas Baghdadi, Auteur ; Jean-Stéphane Bailly, Auteur ; Nicolas Barbier, Auteur ; Valéry Gond, Auteur ; Bruno Hérault, Auteur ; Mahmoud El-Hajj, Auteur ; Frédéric Fabre, Auteur ; José Perrin, Auteur Année de publication : 2016 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données ICEsat
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] Guyane (département français)
[Termes IGN] hauteur des arbres
[Termes IGN] krigeage
[Termes IGN] régressionRésumé : (auteur) LiDAR data has been successfully used to estimate forest parameters such as canopy heights and biomass. Major limitation of LiDAR systems (airborne and spaceborne) arises from their limited spatial coverage. In this study, we present a technique for canopy height mapping using airborne and spaceborne LiDAR data (from the Geoscience Laser Altimeter System (GLAS)). First, canopy heights extracted from both airborne and spaceborne LiDAR were extrapolated from available environmental data. The estimated canopy height maps using Random Forest (RF) regression from airborne or GLAS calibration datasets showed similar precisions (~6 m). To improve the precision of canopy height estimates, regression-kriging was used. Results indicated an improvement in terms of root mean square error (RMSE, from 6.5 to 4.2 m) using the GLAS dataset, and from 5.8 to 1.8 m using the airborne LiDAR dataset. Finally, in order to investigate the impact of the spatial sampling of future LiDAR missions on canopy height estimates precision, six subsets were derived from the initial airborne LiDAR dataset. Results indicated that using the regression-kriging approach a precision of 1.8 m on the canopy height map was achievable with a flight line spacing of 5 km. This precision decreased to 4.8 m for flight line spacing of 50 km. Numéro de notice : A2016--121 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs8030240 En ligne : http://doi.org/10.3390/rs8030240 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84818
in Remote sensing > vol 8 n° 3 (March 2016)[article]Contribution des données NOAA-AVHRR à la caractérisation des savanes africaines / Valéry Gond (1995)
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