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The impact of integrating WorldView-2 sensor and environmental variables in estimating plantation forest species aboveground biomass and carbon stocks in uMgeni Catchment, South Africa / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
[article]
Titre : The impact of integrating WorldView-2 sensor and environmental variables in estimating plantation forest species aboveground biomass and carbon stocks in uMgeni Catchment, South Africa Type de document : Article/Communication Auteurs : Timothy Dube, Auteur ; Onisimo Mutanga, Auteur Année de publication : 2016 Article en page(s) : pp 415 - 425 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Afrique du sud (état)
[Termes IGN] biomasse
[Termes IGN] biomasse aérienne
[Termes IGN] écosystème forestier
[Termes IGN] Eucalyptus dunii
[Termes IGN] Eucalyptus grandis
[Termes IGN] image multibande
[Termes IGN] image Worldview
[Termes IGN] Pinus taeda
[Termes IGN] puits de carbone
[Termes IGN] teneur en carboneRésumé : (Auteur) Reliable and accurate mapping and extraction of key forest indicators of ecosystem development and health, such as aboveground biomass (AGB) and aboveground carbon stocks (AGCS) is critical in understanding forests contribution to the local, regional and global carbon cycle. This information is critical in assessing forest contribution towards ecosystem functioning and services, as well as their conservation status. This work aimed at assessing the applicability of the high resolution 8-band WorldView-2 multispectral dataset together with environmental variables in quantifying AGB and aboveground carbon stocks for three forest plantation species i.e. Eucalyptus dunii (ED), Eucalyptus grandis (EG) and Pinus taeda (PT) in uMgeni Catchment, South Africa. Specifically, the strength of the Worldview-2 sensor in terms of its improved imaging agilities is examined as an independent dataset and in conjunction with selected environmental variables. The results have demonstrated that the integration of high resolution 8-band Worldview-2 multispectral data with environmental variables provide improved AGB and AGCS estimates, when compared to the use of spectral data as an independent dataset. The use of integrated datasets yielded a high R2 value of 0.88 and RMSEs of 10.05 t ha−1 and 5.03 t C ha−1 for E. dunii AGB and carbon stocks; whereas the use of spectral data as an independent dataset yielded slightly weaker results, producing an R2 value of 0.73 and an RMSE of 18.57 t ha−1 and 09.29 t C ha−1. Similarly, high accurate results (R2 value of 0.73 and RMSE values of 27.30 t ha−1 and 13.65 t C ha−1) were observed from the estimation of inter-species AGB and carbon stocks. Overall, the findings of this work have shown that the integration of new generation multispectral datasets with environmental variables provide a robust toolset required for the accurate and reliable retrieval of forest aboveground biomass and carbon stocks in densely forested terrestrial ecosystems. Numéro de notice : A2016-790 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.06.017 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.06.017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82506
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 415 - 425[article]Airborne lidar estimation of aboveground forest biomass in the absence of field inventory / António Ferraz in Remote sensing, vol 8 n° 8 (August 2016)
[article]
Titre : Airborne lidar estimation of aboveground forest biomass in the absence of field inventory Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Sassan Saatchi, Auteur ; Clément Mallet , Auteur ; Stéphane Jacquemoud, Auteur ; Gil Rito-Gonçalves , Auteur ; Carlos Alberto Silva, Auteur ; Paola Soares, Auteur ; Margarida Tomé, Auteur ; Luisa Pereira, Auteur Année de publication : 2016 Projets : 3-projet - voir note / Article en page(s) : pp 1 - 18 Note générale : Bibliographie
This work was supported in part by the Portuguese Foundation for Science and Technology under Grant PTDC/AGR-CFL/72380/2006, co-financed by the European Fund of Regional Development (FEDER) through COMPETE—Operational Factors of Competitiveness Program (POFC) and the Grant Pest-OE/EEI/UI308/2014Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] allométrie
[Termes IGN] analyse de groupement
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] classification automatique d'objets
[Termes IGN] couvert végétal
[Termes IGN] dendrométrie
[Termes IGN] données lidar
[Termes IGN] extraction d'arbres
[Termes IGN] fiabilité des données
[Termes IGN] houppier
[Termes IGN] Portugal
[Termes IGN] puits de carbone
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestierRésumé : (Auteur) The scientific community involved in the UN-REDD program is still reporting large uncertainties about the amount and spatial variability of CO2 stored in forests. The main limitation has been the lack of field samplings over space and time needed to calibrate and convert remote sensing measurements into aboveground biomass (AGB). As an alternative to costly field inventories, we examine the reliability of state-of-the-art lidar methods to provide direct retrieval of many forest metrics that are commonly collected through field sampling techniques (e.g., tree density, individual tree height, crown cover). AGB is estimated using existing allometric equations that are fed by lidar-derived metrics at either the individual tree- or forest layer-level (for the overstory or underneath layers, respectively). Results over 40 plots of a multilayered forest located in northwest Portugal show that the lidar method provides AGB estimates with a relatively small random error (RMSE = of 17.1%) and bias (of 4.6%). It provides local AGB baselines that meet the requirements in terms of accuracy to calibrate satellite remote sensing measurements (e.g., the upcoming lidar GEDI (Global Ecosystem Dynamics Investigation), and the Synthetic Aperture Radar (SAR) missions NISAR (National Aeronautics and Space Administration and Indian Space Research Organization SAR) and BIOMASS from the European Space Agency, ESA) for AGB mapping purposes. The development of similar techniques over a variety of forest types would be a significant improvement in quantifying CO2 stocks and changes to comply with the UN-REDD policies. Numéro de notice : A2016--104 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs8080653 Date de publication en ligne : 12/08/2016 En ligne : https://doi.org/10.3390/rs8080653 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84675
in Remote sensing > vol 8 n° 8 (August 2016) . - pp 1 - 18[article]Documents numériques
en open access
A2016--104_Airborne_lidar_estimation_of_aboveground_forest_biomassAdobe Acrobat PDF Allometric models for estimating tree volume and aboveground biomass in lowland forests of Tanzania / Wilson Ancelm Mugasha in International journal of forestry research, vol 2016 ([01/08/2016])
[article]
Titre : Allometric models for estimating tree volume and aboveground biomass in lowland forests of Tanzania Type de document : Article/Communication Auteurs : Wilson Ancelm Mugasha, Auteur ; Ezekiel Edward Mwakalukwa, Auteur ; Emannuel Luoga, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : 13 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation
[Termes IGN] allométrie
[Termes IGN] biomasse aérienne
[Termes IGN] densité du bois
[Termes IGN] modèle numérique
[Termes IGN] Tanzanie
[Termes IGN] volume en boisRésumé : (auteur) Models to assist management of lowland forests in Tanzania are in most cases lacking. Using a sample of 60 trees which were destructively harvested from both dry and wet lowland forests of Dindili in Morogoro Region (30 trees) and Rondo in Lindi Region (30 trees), respectively, this study developed site specific and general models for estimating total tree volume and aboveground biomass. Specifically the study developed (i) height-diameter (ht-dbh) models for trees found in the two sites, (ii) total, merchantable, and branches volume models, and (iii) total and sectional aboveground biomass models of trees found in the two study sites. The findings show that site specific ht-dbh model appears to be suitable in estimating tree height since the tree allometry was found to differ significantly between studied forests. The developed general volume models yielded unbiased mean prediction error and hence can adequately be applied to estimate tree volume in dry and wet lowland forests in Tanzania. General aboveground biomass model appears to yield biased estimates; hence, it is not suitable when accurate results are required. In this case, site specific biomass allometric models are recommended. Biomass allometric models which include basic wood density are highly recommended for improved estimates accuracy when such information is available. Numéro de notice : A2016--110 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1155/2016/8076271 En ligne : http://dx.doi.org/10.1155/2016/8076271 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84741
in International journal of forestry research > vol 2016 [01/08/2016] . - 13 p.[article]Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland / Eetu Kotivuori in Silva fennica, vol 50 n° 4 (2016)
[article]
Titre : Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland Type de document : Article/Communication Auteurs : Eetu Kotivuori, Auteur ; Lauri Korhonen, Auteur ; Petteri Packalen, Auteur Année de publication : 2016 Article en page(s) : 280 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse aérienne
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Finlande
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle de simulation
[Termes IGN] régression
[Termes IGN] volume en bois
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) The aim of this study was to examine how well stem volume, above-ground biomass and dominant height can be predicted using nationwide airborne laser scanning (ALS) based regression models. The study material consisted of nine practical ALS inventory projects taken from different parts of Finland. We used field sample plots and airborne laser scanning data to create nationwide and regional models for each response variable. The final models had one or two ALS predictors, which were chosen based on the root mean square error (RMSE), and cross-validated. Finally, we tested how much predictions would improve if the nationwide models were calibrated with a small number of regional sample plots. Although forest structures differ among different parts of Finland, the nationwide volume and biomass models performed quite well (leave-inventory-area-out RMSE 22.3% to 33.8%, mean difference [MD] –13.8% to 18.7%) compared with regional models (leave-plot-out RMSE 20.2% to 26.8%). However, the nationwide dominant height model (RMSE 5.4% to 7.7%, MD –2.0% to 2.8%, with the exception of the Tornio region – RMSE 11.4%, MD –9.1%) performed nearly as well as the regional models (RMSE 5.2% to 6.7%). The results show that the nationwide volume and biomass models provided different means than real means at regional level, because forest structure and ALS device have a considerable effect on the predictions. Large MDs appeared especially in northern Finland. Local calibration decreased the MD and RMSE of volume and biomass models. However, the nationwide dominant height model did not benefit much from calibration. Numéro de notice : A2016--113 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.14214/sf.1567 En ligne : https://doi.org/10.14214/sf.1567 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84766
in Silva fennica > vol 50 n° 4 (2016) . - 280 p.[article]Estimating forest and woodland aboveground biomass using active and passive remote sensing / Zhuoting Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 4 (April 2016)
[article]
Titre : Estimating forest and woodland aboveground biomass using active and passive remote sensing Type de document : Article/Communication Auteurs : Zhuoting Wu, Auteur ; Dennis Dye, Auteur ; John Vogel, Auteur ; Barry Middleton, Auteur Année de publication : 2016 Article en page(s) : pp 271 - 281 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Arizona (Etats-Unis)
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] capteur actif
[Termes IGN] capteur passif
[Termes IGN] données lidar
[Termes IGN] écosystème forestier
[Termes IGN] hauteur des arbres
[Termes IGN] image Landsat-8
[Termes IGN] surface forestièreRésumé : (auteur) Aboveground biomass was estimated from active and passive remote sensing sources, including airborne lidar and Landsat-8 satellites, in an eastern Arizona (USA) study area comprised of forest and woodland ecosystems. Compared to field measurements, airborne lidar enabled direct estimation of individual tree height with a slope of 0.98 (R2 = 0.98). At the plot-level, lidar-derived height and intensity metrics provided the most robust estimate for aboveground biomass, producing dominant species-based aboveground models with errors ranging from 4 to 14 Mg ha –1 across all woodland and forest species. Landsat-8 imagery produced dominant species-based aboveground biomass models with errors ranging from 10 to 28 Mg ha –1. Thus, airborne lidar allowed for estimates for fine-scale aboveground biomass mapping with low uncertainty, while Landsat-8 seems best suited for broader spatial scale products such as a national biomass essential climate variable (ECV) based on land cover types for the United States. Numéro de notice : A2016-179 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.82.4.271 En ligne : http://dx.doi.org/10.14358/PERS.82.4.271 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80521
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 4 (April 2016) . - pp 271 - 281[article]Forest above ground biomass inversion by fusing GLAS with optical remote sensing data / Xiaohuan Xi in ISPRS International journal of geo-information, vol 5 n° 4 (April 2016)PermalinkOn the interest of penetration depth, canopy area and volume metrics to improve Lidar-based models of forest parameters / Cédric Vega in Remote sensing of environment, vol 175 (15 March 2016)PermalinkMangrove forest characterization in Southeast Côte d’Ivoire / Isimemen Osemwegie in Open journal of forestry, vol 6 n° 3 (February 2016)PermalinkStatistical rigor in LiDAR-assisted estimation of aboveground forest biomass / Timothy G. Gregoire in Remote sensing of environment, vol 173 (February 2016)PermalinkEstimation of forest biomass using multivariate relevance vector regression / Alireza Sharifi in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 1 (January 2016)PermalinkRadar based classification prior to biomass retrieval from P-Band SAR data / Pierre-Louis Frison (2016)PermalinkInvestigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)PermalinkModeling the above and belowground biomass of planted and coppiced Eucalytpus globulus stands in NW Spain / Daniel J. Vega-Nieva in Annals of Forest Science, vol 72 n° 7 (October 2015)PermalinkAboveground-biomass estimation of a complex tropical forest in India using Lidar / Cédric Vega in Remote sensing, vol 7 n° 8 (August 2015)PermalinkEstimating forest biomass from TerraSAR-X stripmap radargrammetry / Svein Solberg in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)Permalink