Descripteur
Termes IGN > sciences naturelles > sciences de la vie > biologie > botanique > productivité biologique > biomasse > biomasse forestière > biomasse aérienne
biomasse aérienneVoir aussi |
Documents disponibles dans cette catégorie (109)
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
Estimation of forest aboveground biomass from HJ1B imagery using a canopy reflectance model and a forest growth model / Xinyun Wang in Geocarto international, vol 33 n° 2 (February 2018)
[article]
Titre : Estimation of forest aboveground biomass from HJ1B imagery using a canopy reflectance model and a forest growth model Type de document : Article/Communication Auteurs : Xinyun Wang, Auteur ; Yige Guo, Auteur ; Jie He, Auteur ; Lingtong Du, Auteur ; Tianhua Hu, Auteur Année de publication : 2018 Article en page(s) : pp 148 - 162 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse aérienne
[Termes IGN] Chine
[Termes IGN] image HJ-1B
[Termes IGN] juniperus (genre)
[Termes IGN] modèle de croissance végétale
[Termes IGN] Pinophyta
[Termes IGN] Pinus (genre)
[Termes IGN] Populus (genre)
[Termes IGN] réflectance végétale
[Termes IGN] steppe
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] Ulmus (genre)Mots-clés libres : stochastic Gradient boosting Résumé : (Auteur) Accurately estimating the spatial distribution of forest aboveground biomass (AGB) is important because of its carbon budget forms part of the global carbon cycle. This paper presented three methods for obtaining forest AGB based on a forest growth model, a Multiple-Forward-Mode (MFM) method and a stochastic gradient boosting (SGB) model. A Li-Strahler geometric-optical canopy reflectance model (GOMS) with the ZELIG forest growth model was run using HJ1B imagery to derive forest AGB. GOMS-ZELIG simulated data were used to train the SGB model and AGB estimation. The GOMS-ZELIG AGB estimation was evaluated for 24 field-measured data and compared against the GOMS-SGB model and GOMS-MFM biomass predictions from multispectral HJ1B data. The results show that the estimation accuracy of the GOMS-MFM model is slightly higher than that of the GOMS-SGB model. The GOMS-ZELIG and GOMS-MFM models are considerably more accurate at estimating forest AGB in arid and semiarid regions. Numéro de notice : A2018-032 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1232438 En ligne : https://doi.org/10.1080/10106049.2016.1232438 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89205
in Geocarto international > vol 33 n° 2 (February 2018) . - pp 148 - 162[article]
Titre : Forest biomass and carbon Type de document : Monographie Auteurs : Gopal Shukla, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2018 Importance : 112 p. Format : 19 x 27 cm ISBN/ISSN/EAN : 978-1-78984-362-0 Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] densité de la végétation
[Termes IGN] énergie renouvelable
[Termes IGN] gestion forestière durable
[Termes IGN] matière organique
[Termes IGN] Pinus (genre)
[Termes IGN] puits de carbone
[Termes IGN] savane
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] Theobroma cacao
[Termes IGN] zone intertropicale
[Vedettes matières IGN] Ecologie forestièreRésumé : (éditeur) Forests grow and their biomass increases; they absorb carbon from the atmosphere and store it in plant tissue. Understanding the biomass of forest vegetation is essential for determining the storage of carbon in the dominant tree component and computing carbon cycling at a regional as well as global level. This book consisting of five chapters will give a comprehensive understanding of biomass production vis-à-vis carbon storage in relation to litter and nutrient dynamics of the forest by analyzing the mode and magnitude of biomass production and carbon storage as a function of various silvicultural factors. Note de contenu : 1- Effects of forest stand structure in biomass and carbon
2- Tree stock, structure and use of common woody species of a town neighboring forest reserve in Tanzania: Implication for managing carbon accumulation
3- Plant diversity, ecological services, and carbon stock assessment in cocoa agroforestry plantations of forest and savannah transitions in Cameroon
4- Effects of eucalyptus and pinus forest management on soil organic carbon in Brazilian wooded-savanna
5- Determinants and tools to evaluate the ecological sustainability of using forest biomass as an alternative energy sourceNuméro de notice : 25955 Affiliation des auteurs : non IGN Thématique : FORET Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.69011 En ligne : https://doi.org/10.5772/intechopen.69011 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96421
Titre : Image processing in agriculture and forestry Type de document : Monographie Auteurs : Gonzalo Pajares Martinsanz, Éditeur scientifique ; Francisco Rovira-Más, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2018 Importance : 222 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 9783038970972 9783038970989 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] biomasse aérienne
[Termes IGN] changement d'occupation du sol
[Termes IGN] chlorophylle
[Termes IGN] couvert forestier
[Termes IGN] image captée par drone
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] indice foliaire
[Termes IGN] instrument embarqué
[Termes IGN] phénologie
[Termes IGN] positionnement en intérieur
[Termes IGN] reconstruction 3D
[Termes IGN] teneur en eau de la végétation
[Termes IGN] traitement automatique de données
[Termes IGN] vision par ordinateurRésumé : (édition) Image processing in agriculture and forestry represents a challenge towards the automation of tasks for better performances. Agronomists, computer and robotics engineers, and agricultural machinery industry manufacturers now have at their disposal a book containing a collection of methods, procedures, designs, and descriptions at the technological forefront, which serves as an important support and aid for the implementation and development of their own ideas.The book describes: (1) Applications (canopy on trees, aboveground biomass, phenotyping, chlorophyll, leaf area index, water and nutrient content, land cover change, soil properties, and secure autonomous navigation); (2) Imaging devices onboard robots, unmanned aerial vehicles (UAVs), and satellites operating at different spectral ranges (visible, infrared, hyper-multispectral bands, and radar), as well as guidelines for selecting machine vision systems in outdoor environments; and (3) (Specific computer vision methods (generic and convolutional neural networks, machine learning, specific segmentation approaches, vegetation indices, and three-dimensional (3D) reconstruction). Note de contenu : Preface
1- Machine-vision systems selection for agricultural vehicles
2- Precise navigation of small agricultural robots in sensitive areas with a smart plant camera
3- Using deep learning to challenge safety standard for highly autonomous machines in agriculture
4- 3D reconstruction of plant/tree canopy using monocular and binocular vision
5- Peach flower monitoring using aerial multispectral imaging
6- Early yield prediction using image analysis of apple fruit and tree canopy features with neural networks
7- Non-parametric retrieval of aboveground biomass in Siberian boreal forests with ALOS PALSAR interferometric coherence and backscatter intensity
8- Imaging for high-throughput phenotyping in energy sorghum
9- Viewing geometry sensitivity of commonly used vegetation indices towards the estimation of biophysical variables in orchards
10- Estimating mangrove biophysical variables using WorldView-2 satellite data: Rapid creek, Northern Territory, Australia
11- Land cover change image analysis for Assateague Island National Seashore following hurricane Sandy
12- Automated soil physical parameter assessment using smartphone and digital camera imageryNuméro de notice : 25921 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Monographie En ligne : https://doi.org/10.3390/books978-3-03897-098-9 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96137 Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery / Jose Alan A. Castillo in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)
[article]
Titre : Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery Type de document : Article/Communication Auteurs : Jose Alan A. Castillo, Auteur ; Armando A. Apan, Auteur ; Tek N. Maraseni, Auteur ; Severino G. Salmo, Auteur Année de publication : 2017 Article en page(s) : pp 70 - 85 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] biomasse aérienne
[Termes IGN] carte d'utilisation du sol
[Termes IGN] déboisement
[Termes IGN] estimation statistique
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] indice de végétation
[Termes IGN] mangrove
[Termes IGN] modèle de simulation
[Termes IGN] Philippines
[Termes IGN] régression linéaire
[Termes IGN] rétrodiffusion
[Termes IGN] variable biophysique (végétation)Résumé : (Auteur) The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82–0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8–28.5 Mg ha−1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement non-forest land uses, especially with the inclusion of elevation data. The study demonstrates encouraging results in biomass mapping of mangroves and other coastal land uses in the tropics using the freely accessible and relatively high-resolution Sentinel imagery. Numéro de notice : A2017-730 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.10.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.10.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88428
in ISPRS Journal of photogrammetry and remote sensing > vol 134 (December 2017) . - pp 70 - 85[article]Réservation
Réserver ce documentExemplaires (3)
Code-barres Cote Support Localisation Section Disponibilité 081-2017121 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017122 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017123 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt Tree size thresholds produce biased estimates of forest biomass dynamics / Eric B. Searle in Forest ecology and management, vol 400 (15 September 2017)
[article]
Titre : Tree size thresholds produce biased estimates of forest biomass dynamics Type de document : Article/Communication Auteurs : Eric B. Searle, Auteur ; Han Y.H. Chen, Auteur Année de publication : 2017 Article en page(s) : pp 468 - 474 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse aérienne
[Termes IGN] changement climatique
[Termes IGN] diamètre des arbres
[Termes IGN] échantillonnage
[Termes IGN] erreur systématique
[Termes IGN] estimation statistique
[Termes IGN] forêt boréale
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Manitoba (Canada)
[Termes IGN] placette d'échantillonnage
[Termes IGN] seuillage
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Studies that examine forest biomass dynamics often rely on long-term, spatially extensive, repeatedly measured permanent sample plots. Due to the intensive cost of sampling all trees within these plots, an arbitrary size threshold is typically imposed, which leads to only larger trees being sampled. However, it remains unclear whether the sampling of only large trees is representative of the entirety of stands of diverse sizes; the sampling of only large trees may produce biased estimates of biomass dynamics (growth, ingrowth, and mortality). Using a network of 141 permanent sample plots from Manitoba, Canada, with all trees of >1.3 m in height repeatedly measured, we constructed three distinct data sets, with 10 cm, 5 cm, and no diameter at breast height threshold, to illustrate that total productivity and mortality are increasingly underestimated with increasingly larger diameter at breast height thresholds. This effect is particularly significant in young stands, where productivity estimates peak at least 20 years earlier than the determined estimates under large thresholds. We highlight the need to account for smaller trees in long-term observational studies to ensure unbiased estimates of stand level aboveground biomass productivity and loss. Numéro de notice : A2017-807 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.1016/j.foreco.2017.06.042 En ligne : https://doi.org/10.1016/j.foreco.2017.06.042 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89245
in Forest ecology and management > vol 400 (15 September 2017) . - pp 468 - 474[article]Coverage of high biomass forests by the ESA BIOMASS mission under defense restrictions / João M.B. Carreiras in Remote sensing of environment, vol 196 (July 2017)PermalinkForest classification and impact of BIOMASS resolution on forest area and aboveground biomass estimation / Michael Schlund in International journal of applied Earth observation and geoinformation, vol 56 (April 2017)PermalinkTerrestrial laser scanning as a tool for assessing tree growth / Jonathan Sheppard in iForest, biogeosciences and forestry, vol 10 n° 1 (February 2017)PermalinkForest inventory-based projection systems for wood and biomass availability, ch. France [National woody biomass projection systems based on forest inventory - Projecting wood resources and potential wood supply of French forests: an approach to cope with forest system diversity] / Antoine Colin (2017)PermalinkLand Surface Remote Sensing in Continental Hydrology, ch. 3. Using satellite scatterometers to monitor continental surfaces / Pierre-Louis Frison (2017)PermalinkTélédétection pour l'observation des surfaces continentales, ch. 3. Utilisation des diffusiomètres satellitaires pour le suivi des surfaces continentales / Pierre-Louis Frison (2017)PermalinkAboveground biomass mapping in French Guiana by combining remote sensing, forest inventories and environmental data / Ibrahim Fayad in International journal of applied Earth observation and geoinformation, vol 52 (October 2016)PermalinkProgress in the remote sensing of C3 and C4 grass species aboveground biomass over time and space / Cletah Shoko in ISPRS Journal of photogrammetry and remote sensing, vol 120 (october 2016)PermalinkRelative importance analysis of Landsat, waveform LIDAR and PALSAR inputs for deciduous biomass estimation / Alyssa Endres in European journal of remote sensing, vol 49 n° 1 (2016)PermalinkLidar detection of individual tree size in tropical forests / António Ferraz in Remote sensing of environment, vol 183 (15 September 2016)Permalink