Descripteur
Termes IGN > foresterie > sylviculture
sylviculture
Commentaire :
Arboriculture, Arboriculture forestière, Arbres -- Techniques culturales, Cultures forestières, Forêts -- Techniques culturales, Forêts et sylviculture, Techniques forestières. Agriculture. >> Industrie forestière, Bois, Forêt -- Exploitation, Forêt, Machine forestière. Voir aussi les vedettes commençant par Forêts ; Foresterie ; Sylviculture. >>Terme(s) spécifique(s) : Écorçage, Martelage (sylviculture), Arbre -- Abattage, Déboisement, Déchet d'abattage, Dendrométrie, Inventaire forestier, Route forestière, Station forestière -- Typologie, Sylviculture tropicale, Essartage, Éclaircie (sylviculture), Cloisonnement (sylviculture), Coupe à blanc, Dégagement (sylviculture). Equiv. LCSH : Forest and forestry. |
Documents disponibles dans cette catégorie (1012)
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
Relating SAR image texture to the biomass of regenerating tropical forests / T.M. Kuplich in International Journal of Remote Sensing IJRS, vol 26 n° 21 (November 2005)
[article]
Titre : Relating SAR image texture to the biomass of regenerating tropical forests Type de document : Article/Communication Auteurs : T.M. Kuplich, Auteur ; P.J. Curran, Auteur ; P.M. Atkinson, Auteur Année de publication : 2005 Article en page(s) : pp 4829 - 4854 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande L
[Termes IGN] canopée
[Termes IGN] forêt tropicale
[Termes IGN] image JERS
[Termes IGN] image radar
[Termes IGN] Manaus
[Termes IGN] masse végétale
[Termes IGN] niveau de gris (image)
[Termes IGN] teneur en carbone
[Termes IGN] texture d'image
[Termes IGN] variogrammeRésumé : (Auteur) An accurate global carbon budget requires information on terrestrial carbon sink strength. Regenerating tropical forests are known to be important terrestrial carbon sinks but information on their location, extent and biomass (from which carbon content can be estimated) is incomplete. The use of remotely sensed data in optical wavelengths has been of limited use due to both the weak relationship between optical radiation and forest biomass and near-constant cloud cover in the tropics. L-band Synthetic Aperture Radar (SAR) backscatter, however, is related positively to biomass (but only up to an asymptote of around 40-90T ha-1) and can be obtained independently of cloud cover. Both canopy structure and biomass change over time as pioneer species are replaced by early and late regenerating species. These structural changes are related to an increase in (i) tree height, (ii) tree species richness and (iii) canopy thickness and influence the roughness of the canopy surface and consequently SAR image texture. Therefore, we investigated the degree to which textural information could be used to increase the correlation between image tone (backscatter) and biomass. Field data were used to estimate the biomass of 37 regenerating forests plots in Brazilian Amazonia. Texture measures derived from local statistics, the grey level co-occurrence matrix (GLCM) and the variogram were evaluated using simulated images on the basis of their ability to identify significant differences in image texture independently of image contrast. The selected texture measures were applied to L-band JERS-1 (Japanese Earth Resources Satellite) SAR images and the correlation between backscatter and biomass was determined for regenerating tropical forests. A strong correlation was found for the texture measures and biomass. The ra2 (adjusted coefficient of determination), measuring the correlation between backscatter and biomass, increased from 0.74 to 0.82 with the addition of GLCM-derived contrast. The addition of image texture (GLCM-derived contrast) to image tone (backscatter) potentially increases the accuracy with which JERS-1 SAR data can be used to estimate biomass in tropical forests. Numéro de notice : A2005-469 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500239107 En ligne : https://doi.org/10.1080/01431160500239107 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27605
in International Journal of Remote Sensing IJRS > vol 26 n° 21 (November 2005) . - pp 4829 - 4854[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05211 RAB Revue Centre de documentation En réserve L003 Disponible Estimating forest biomass using small footprint LiDAR data: An individual tree-based approach that incorporates training data / Z.J. Bortolot in ISPRS Journal of photogrammetry and remote sensing, vol 59 n° 6 (November 2005)
[article]
Titre : Estimating forest biomass using small footprint LiDAR data: An individual tree-based approach that incorporates training data Type de document : Article/Communication Auteurs : Z.J. Bortolot, Auteur ; R. Wynne, Auteur Année de publication : 2005 Article en page(s) : pp 342 - 360 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] couvert forestier
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] forêt tempérée
[Termes IGN] houppier
[Termes IGN] lasergrammétrie
[Termes IGN] masse végétale
[Termes IGN] optimisation (mathématiques)
[Termes IGN] Pinus taeda
[Termes IGN] régression
[Termes IGN] sylviculture
[Termes IGN] Virginie (Etats-Unis)Résumé : (Auteur) A new individual tree-based algorithm for determining forest biomass using small footprint LiDAR data was developed and tested. This algorithm combines computer vision and optimization techniques to become the first training data-based algorithm specifically designed for processing forest LiDAR data. The computer vision portion of the algorithm uses generic properties of trees in small footprint LiDAR canopy height models (CHMs) to locate trees and find their crown boundaries and heights. The ways in which these generic properties are used for a specific scene and image type is dependent on 11 parameters, nine of which are set using training data and the Nelder-Mead simplex optimization procedure. Training data consist of small sections of the LiDAR data and corresponding ground data. After training, the biomass present in areas without ground measurements is determined by developing a regression equation between properties derived from the LiDAR data of the training stands and biomass, and then applying the equation to the new areas. A first test of this technique was performed using 25 plots (radius = 15 m) in a loblolly pine plantation in central Virginia, USA (37.42N, 78.68W) that was not intensively managed, together with corresponding data from a LiDAR canopy height model (resolution = 0.5 m). Results show correlations (r) between actual and predicted aboveground biomass ranging between 0.59 and 0.82, and RMSEs between 13.6 and 140.4 t/ha depending on the selection of training and testing plots, and the minimum diameter at breast height (7 or 10 cm) of trees included in the biomass estimate. Correlations between LiDAR-derived plot density estimates were low (0.22 Numéro de notice : A2005-490 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2005.07.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2005.07.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27626
in ISPRS Journal of photogrammetry and remote sensing > vol 59 n° 6 (November 2005) . - pp 342 - 360[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-05041 SL Revue Centre de documentation Revues en salle Disponible A simple and effective radiometric correction method to improve landscape change detection across sensors and across time / X. Chen in Remote sensing of environment, vol 98 n° 1 (30/09/2005)
[article]
Titre : A simple and effective radiometric correction method to improve landscape change detection across sensors and across time Type de document : Article/Communication Auteurs : X. Chen, Auteur ; Lee Alexander Vierling, Auteur ; D. Deering, Auteur Année de publication : 2005 Article en page(s) : pp 63 - 79 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] correction radiométrique
[Termes IGN] couvert végétal
[Termes IGN] détection de changement
[Termes IGN] données multitemporelles
[Termes IGN] Enhanced vegetation index
[Termes IGN] forêt boréale
[Termes IGN] groupe
[Termes IGN] image Landsat
[Termes IGN] image multitemporelle
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] régression
[Termes IGN] SibérieRésumé : (Auteur) Satellite data offer unrivaled utility in monitoring and quantifying large scale land cover change over time. Radiometric consistency among collocated multi-temporal imagery is difficult to maintain, however, due to variations in sensor characteristics, atmospheric conditions, solar angle, and sensor view angle that can obscure surface change detection. To detect accurate landscape change using multitemporal images, we developed a variation of the pseudoinvariant feature (PIF) normalization scheme: the temporally invariant cluster (TIC) method. Image data were acquired on June 9, 1990 (Landsat 4), June 20, 2000 (Landsat 7), and August 26, 2001 (Landsat 7) to analyze boreal forest near the Siberian city of Krasnoyarsk using the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and reduced simple ratio (RSR). The temporally invariant cluster (TIC) centers were identified via a point density map of collocated pixel VIs from the base image and the target image, and a normalization regression line was created to intersect all TIC centers. Target image VI values were then recalculated using the regression function so that these two images could be compared using the resulting common radiometric scale. We found that EVI was very indicative of vegetation structure because of its sensitivity to shadowing effects and could thus be used to separate conifer forests from deciduous forests and grass/crop lands. Conversely, because NDVI reduced the radiometric influence of shadow, it did not allow for distinctions among these vegetation types. After normalization, correlations of NDVI and EVI with forest leaf area index (LAI) field measurements combined for 2000 and 2001 were significantly improved; the r2 values in these regressions rose from 0.49 to 0.69 and from 0.46 to 0.61, respectively. An EVI "cancellation effect" where FVI was positively related to understory greenness but negatively related to forest canopy coverage was evident across a post fire chronosequence with normalized data. These findings indicate that the TIC method provides a simple, effective and repeatable method to create radiometrically comparable data sets for remote detection of landscape change. Compared to some previous relative radiometric normalization methods, this new method does not require high level programming and statistical skills, yet remains sensitive to landscape changes occurring over seasonal and inter-annual time scales. In addition, the TIC method maintains sensitivity to subtle changes in vegetation phenology and enables normalization even when invariant features are rare. While this normalization method allowed detection of a range of land use, land cover, and phonological/biophysical changes in the Siberian boreal forest region studied here, it is necessary to further examine images representing a wide variety of ecoregions to thoroughly evaluate the TIC method against other normalization schemes. Numéro de notice : A2005-403 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2005.05.021 En ligne : https://doi.org/10.1016/j.rse.2005.05.021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27539
in Remote sensing of environment > vol 98 n° 1 (30/09/2005) . - pp 63 - 79[article]Application of SeaWinds scatterometer and TMI-SSM/I rain rates to hurricane analysis and forecasting / R. Atlas in ISPRS Journal of photogrammetry and remote sensing, vol 59 n° 4 (June - July 2005)
[article]
Titre : Application of SeaWinds scatterometer and TMI-SSM/I rain rates to hurricane analysis and forecasting Type de document : Article/Communication Auteurs : R. Atlas, Auteur ; A.Y. Hou, Auteur ; O. Reale, Auteur Année de publication : 2005 Article en page(s) : pp 233 - 243 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] capteur actif
[Termes IGN] capteur passif
[Termes IGN] cyclone
[Termes IGN] diffusomètre
[Termes IGN] Etats-Unis
[Termes IGN] forêt tropicale
[Termes IGN] image DMSP-SSM/I
[Termes IGN] image TRMM-MI
[Termes IGN] modèle atmosphérique
[Termes IGN] pluie
[Termes IGN] prévision météorologique
[Termes IGN] risque naturel
[Termes IGN] télédétection en hyperfréquence
[Termes IGN] tempête
[Termes IGN] TRMM
[Termes IGN] zone intertropicaleRésumé : (Auteur) Results provided by two different assimilation methodologies involving data from passive and active space-borne microwave instruments are presented. The impact of the precipitation estimates produced by the TRMM Microwave Imager (TMI) and Special Sensor Microwave/lmager (SSM/I) in a previously developed 1D variational continuous assimilation algorithm for assimilating tropical rainfall is shown on two hurricane cases. Results on the impact of the SeaWinds scatterometer on the intensity and track forecast of a mid-Atlantic hurricane are also presented. This work is the outcome of a collaborative effort between NASA and NOAA, and indicates the substantial improvement in tropical cyclone forecasting that can result from the assimilation of space-based data in global atmospheric models. Copyright ISPRS Numéro de notice : A2005-292 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2005.02.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2005.02.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27428
in ISPRS Journal of photogrammetry and remote sensing > vol 59 n° 4 (June - July 2005) . - pp 233 - 243[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-05021 SL Revue Centre de documentation Revues en salle Disponible Survival analysis of a neotropical rainforest using multitemporal satellite imagery / J.A. Greenberg in Remote sensing of environment, vol 96 n° 2 (30/05/2005)
[article]
Titre : Survival analysis of a neotropical rainforest using multitemporal satellite imagery Type de document : Article/Communication Auteurs : J.A. Greenberg, Auteur ; S.C. Kefauver, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 202 - 211 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] amérindien
[Termes IGN] analyse spatiale
[Termes IGN] déboisement
[Termes IGN] Equateur (état)
[Termes IGN] forêt équatoriale
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] impact sur l'environnement
[Termes IGN] parc naturel national
[Termes IGN] prédiction
[Termes IGN] routeRésumé : (Auteur) We present results of an analysis of deforestation at a UNESCO Biosphere Reserve, the Parque National Yasuni, located in the rainforests of eastern Ecuador using multitemporal Landsat TM and ETM+ satellite imagery. Using survival analysis, we assessed both current and future trends in deforestation rates, and investigated the impact of spatial, cultural, and economic factors on deforestation. These factors included the distance from roads, rivers research facilities, oil facilities, markets and towns, and land ownership by colonists, native inhabitants, and an oil company. We found the annual rate of deforestation is currently only 0.11%, but that this rate is increasing with time and, assuming that the trend of increasing rate of forest loss continues, we would predict that by 2063, 50% of the forest within 2 km of an oil access road will be lost to unhindered colonization and anthropogenic conversion. The Quechua colonists are associated with areas of the highest rate of deforestation, followed by the native Huaorani and the lowest region of deforestation was in areas occupied by a local oil company. By far, the strongest predictor of where deforestation is predicted to occur was proximity to the road. Proximity to research sites, oil facilities, market, and rivers significantly decreases deforestation rates, and proximity to towns significantly increases deforestation rates. Copyright Elsevier Numéro de notice : A2005-265 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2005.02.010 En ligne : https://doi.org/10.1016/j.rse.2005.02.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27401
in Remote sensing of environment > vol 96 n° 2 (30/05/2005) . - pp 202 - 211[article]Land covers change detection at coarse spatial scales based on iterative estimation and previous state information / Sylvie Le Hégarat-Mascle in Remote sensing of environment, vol 95 n° 4 (30/04/2005)PermalinkSPOT-4 Vegetation multi-temporal compositing for land cover change studies over tropical regions / João M.B. Carreiras in International Journal of Remote Sensing IJRS, vol 26 n° 7 (April 2005)PermalinkEstimating tropical pasture quality at canopy level using band depth analysis with continuum removal in the visible domain / Onisimo Mutanga in International Journal of Remote Sensing IJRS, vol 26 n° 6 (March 2005)PermalinkExtension d'un guide pour l'identification des stations forestières : utilisation des données de l'Inventaire forestier national, un exemple d'application aux confins du Gâtinais oriental / Marie Forêt in Ingénieries : eau, agriculture, territoires, n° 41 (mars 2005)PermalinkMapping tropical forest structure in south-eastern Madagascar using remote sensing and artificial neural networks / J.C. Ingram in Remote sensing of environment, vol 94 n° 4 (28/02/2005)PermalinkAssesment of manual and automated methods for updating stand-level forest inventories based on aerial photography / Perttu Antilla (2005)PermalinkThird expert meeting on harmonizing forest-related definitions for use by various stakeholders, Rome, Italy, 17 - 19 January 2005 / Wulf Killmann (2005)PermalinkAssessing the feasibility of a global model for multi-temporal burned area mapping using Spot-Vegetation data / J.M. Silva in International Journal of Remote Sensing IJRS, vol 25 n° 22 (November 2004)PermalinkLIDAR-based geometric reconstruction of boreal type forest stands at single tree level for forest and wildland fire management / F. Morsdorf in Remote sensing of environment, vol 92 n° 3 (30 August 2004)PermalinkEstimation of interannual variation in productivity of global vegetation using NDVI data / Z.M. Chen in International Journal of Remote Sensing IJRS, vol 25 n° 16 (August 2004)Permalink