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Quantifying the influence of plot-level uncertainty in above ground biomass up scaling using remote sensing data in central Indian dry deciduous forest / Thangavelu Mayamanikandan in Geocarto international, vol 37 n° 12 ([01/07/2022])
[article]
Titre : Quantifying the influence of plot-level uncertainty in above ground biomass up scaling using remote sensing data in central Indian dry deciduous forest Type de document : Article/Communication Auteurs : Thangavelu Mayamanikandan, Auteur ; Suraj Reddy, Auteur ; Rakesh Fararoda, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 3489 - 3503 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse aérienne
[Termes IGN] forêt de feuillus
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] incertitude des données
[Termes IGN] Inde
[Termes IGN] placette d'échantillonnage
[Termes IGN] superposition d'imagesRésumé : (auteur) Accurate and reliable estimation of Above Ground Biomass (AGB) in tropical forests is much needed for net carbon assessments. The aim of the study is to determine the uncertainty in biomass estimation in terms of field plot size, shape and location error using field plot and remote sensing data in tropical dry deciduous forests of India. Detailed tree measurements and location mapping are performed in 13 (1 ha) plots and 1 a very large permanent plot of 32 ha and AGB is estimated using local volume equations. Remote sensing-based AGB estimated using a multiple linear regression model between the reflectance (Sentinel-2) and backscatter (Sentinel-1) with field AGB. The result shows relative root mean square error of the model decreased by approximately 50% with a plot size increase from 0.01 ha (64%) to 0.64 ha (14%). Furthermore, we also observed that the effect of global positioning system location errors in AGB modelling would be negated by increasing plot size. Numéro de notice : A2022-587 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1864029 Date de publication en ligne : 29/12/2020 En ligne : https://doi.org/10.1080/10106049.2020.1864029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101361
in Geocarto international > vol 37 n° 12 [01/07/2022] . - pp 3489 - 3503[article]Management or climate and which one has the greatest impact on forest soil’s protective value? A case study in Romanian mountains / Cosmin Cosofret in Forests, vol 13 n° 6 (June 2022)
[article]
Titre : Management or climate and which one has the greatest impact on forest soil’s protective value? A case study in Romanian mountains Type de document : Article/Communication Auteurs : Cosmin Cosofret, Auteur ; Gabriel Duduman, Auteur ; Ionut Barnoaiea, Auteur ; Olivier Bouriaud , Auteur Année de publication : 2022 Projets : 3-projet - voir note / Article en page(s) : n° 916 Note générale : bibliographie
C.C. acknowledges funding from the European H2020 Grant 817903 EFFECT and G.D., I.B. and O.B. acknowledge funding from the Ministry of Research, Innovation and Digitalization within Program 1—Development of national research and development system, Subprogram 1.2—Institutional Performance—RDI excellence funding projects, under contract no. 10PFE/2021.Langues : Anglais (eng) Descripteur : [Termes IGN] altitude
[Termes IGN] analyse comparative
[Termes IGN] biomasse forestière
[Termes IGN] changement climatique
[Termes IGN] gestion forestière
[Termes IGN] modèle de simulation
[Termes IGN] modélisation de la forêt
[Termes IGN] protection des forêts
[Termes IGN] protection des sols
[Termes IGN] Roumanie
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) The protective value of forests is expected to be affected by climate change. Applied forest management could absorb or enhance such an impact. In this context, we developed a new protective value index (PVI) that includes biometric and topographical indicators of forest stands. Using PVI and the LandClim model, we simulated 100 years with low- and high-intensity cuttings within three climate scenarios to analyze their influence on the protective value of forests included in the soil protection category. The management types had a low impact on PVI during the simulation period. However, the effects of moderate climate intensified in the second half of the simulation period. In contrast, the extreme climate had the highest impact on PVI and its variables throughout the whole period. The forest stands from lower elevation reached a higher protective value than intermediate and high elevation. Although the low-elevation forest stands are the most vulnerable to climate changes, the ongoing adaptation conducts to stands with higher protective value than stable forests from the higher elevation. The PVI is easily adaptable for different forest landscape models and can be widely applied to provide an integrated assessment of the forest protective value and the management measures to maintain or enhance it Numéro de notice : A2022-489 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f13060916 Date de publication en ligne : 12/06/2022 En ligne : https://doi.org/10.3390/f13060916 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100964
in Forests > vol 13 n° 6 (June 2022) . - n° 916[article]Uncertainty of biomass stocks in Spanish forests: a comprehensive comparison of allometric equations / Aitor Ameztegui in European Journal of Forest Research, vol 141 n° 3 (June 2022)
[article]
Titre : Uncertainty of biomass stocks in Spanish forests: a comprehensive comparison of allometric equations Type de document : Article/Communication Auteurs : Aitor Ameztegui, Auteur ; Marco Rodrigues, Auteur ; Victor Granda, Auteur Année de publication : 2022 Article en page(s) : pp 395 - 407 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse forestière
[Termes IGN] changement climatique
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données allométriques
[Termes IGN] écosystème forestier
[Termes IGN] Espagne
[Termes IGN] estimation statistique
[Termes IGN] Eucalyptus (genre)
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle de croissance végétale
[Termes IGN] Pinus pinaster
[Termes IGN] puits de carbone
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Biomass and carbon content are essential indicators for monitoring forest ecosystems and their role in climate action, but their estimation is not straightforward. A typical approach to solve these limitations has been the estimation of tree or stand biomass based on forest inventory data, using either allometric equations or biomass expansion factors. Many allometric equations exist, but very few studies have assessed how the calculation methods used may impact outcomes and how this impact depends on genera, functional group, climate or forest structural attributes. In this study we evaluate the differences in biomass estimates yielded by the most widely used biomass equations in Spain. We first quantify the discrepancies at tree level and among the main forest tree species. We observed that the divergences in carbon estimations between different equations increased with tree size, especially in the case of hardwoods and for diameters beyond the range used to calibrate the equations. At the plot level, we found considerable differences between the biomass values predicted using different methods (above 25% in one out of three plots), which constitutes a warning against the uncritical choice of equations to determine biomass or carbon values. The spatial representation of the differences revealed geographical patterns related to the dominance of fast-growing species such as Eucalyptus or Pinus pinaster, with a minor effect of forest structure, and almost no effect of climate. Finally, we observed that differences were mostly due to the data source rather than the modelling approach or equation used. Based on our results, BEF equations seem a valid and unbiased option to provide nation-level estimations of carbon balance, although local equations should preferably be used if they are available for the target area. Numéro de notice : A2022-416 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.1007/s10342-022-01444-w Date de publication en ligne : 09/04/2022 En ligne : https://doi.org/10.1007/s10342-022-01444-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100777
in European Journal of Forest Research > vol 141 n° 3 (June 2022) . - pp 395 - 407[article]Spatial-temporal variation of satellite-based gross primary production estimation in wheat-maize rotation area during 2000–2015 / Wenquan Xie in Geocarto international, vol 37 n° 9 ([15/05/2022])
[article]
Titre : Spatial-temporal variation of satellite-based gross primary production estimation in wheat-maize rotation area during 2000–2015 Type de document : Article/Communication Auteurs : Wenquan Xie, Auteur ; Huini Wang, Auteur ; Hong Chi, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2506 - 2523 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] blé (céréale)
[Termes IGN] Chine
[Termes IGN] image Terra-MODIS
[Termes IGN] maïs (céréale)
[Termes IGN] photosynthèse
[Termes IGN] production primaire brute
[Termes IGN] rotation de culture
[Termes IGN] série temporelle
[Termes IGN] variation temporelleRésumé : (auteur) North China Plain is the largest agricultural production center in China and wheat-maize rotation is a widespread cultivation practice in this area. As gross primary production (GPP) is a proxy of land productivity, research on its spatial-temporal dynamics helps understand the variation of grain production in wheat-maize rotation. Here, Moderate Resolution Imaging Spectroradiometer (MODIS) data and ground observation data were combined to drive Vegetation Photosynthesis Model (VPM) in GPP estimation over wheat-maize rotation area during 2000–2015. Annual GPP has increased by 540.95 g C m−2 year−1 from 2000 to 2015, while total annual GPP has grown ∼150% than that of 2000. Moreover, annual GPP showed an increasing trend in the consecutively wheat-maize rotation area between 2000 and 2015. A strong linear relationship between GPP estimates and grain production demonstrated the potential of using VPM model to evaluate grain production in wheat-maize rotation area of Henan province, China. Numéro de notice : A2022-566 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1822928 Date de publication en ligne : 24/09/2020 En ligne : https://doi.org/10.1080/10106049.2020.1822928 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101249
in Geocarto international > vol 37 n° 9 [15/05/2022] . - pp 2506 - 2523[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2022091 RAB Revue Centre de documentation En réserve L003 Disponible A continuous change tracker model for remote sensing time series reconstruction / Yangjian Zhang in Remote sensing, vol 14 n° 9 (May-1 2022)
[article]
Titre : A continuous change tracker model for remote sensing time series reconstruction Type de document : Article/Communication Auteurs : Yangjian Zhang, Auteur ; Li Wang, Auteur ; Yuanhuizi He, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 2280 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme de filtrage
[Termes IGN] analyse harmonique
[Termes IGN] compression d'image
[Termes IGN] détection de changement
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] Leaf Area Index
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] phénologie
[Termes IGN] production primaire brute
[Termes IGN] reconstruction d'image
[Termes IGN] réflectance de surface
[Termes IGN] série temporelleRésumé : (auteur) It is hard for current time series reconstruction methods to achieve the balance of high-precision time series reconstruction and explanation of the model mechanism. The goal of this paper is to improve the reconstruction accuracy with a well-explained time series model. Thus, we developed a function-based model, the CCTM (Continuous Change Tracker Model) model, that can achieve high precision in time series reconstruction by tracking the time series variation rate. The goal of this paper is to provide a new solution for high-precision time series reconstruction and related applications. To test the reconstruction effects, the model was applied to four types of datasets: normalized difference vegetation index (NDVI), gross primary productivity (GPP), leaf area index (LAI), and MODIS surface reflectance (MSR). Several new observations are as follows. First, the CCTM model is well explained and based on the second-order derivative theorem, which divides the yearly time series into four variation types including uniform variations, decelerated variations, accelerated variations, and short-periodical variations, and each variation type is represented by a designed function. Second, the CCTM model provides much better reconstruction results than the Harmonic model on the NDVI, GPP, MSR, and LAI datasets for the seasonal segment reconstruction. The combined use of the Savitzky–Golay filter and the CCTM model is better than the combinations of the Savitzky–Golay filter with other models. Third, the Harmonic model has the best trend-fitting ability on the yearly time series dataset, with the highest R-Square and the lowest RMSE among the four function fitting models. However, with seasonal piecewise fitting, the four models all achieved high accuracy, and the CCTM performs the best. Fourth, the CCTM model should also be applied to time series image compression, two compression patterns with 24 coefficients and 6 coefficients respectively are proposed. The daily MSR dataset can achieve a compression ratio of 15 by using the 6-coefficients method. Finally, the CCTM model also has the potential to be applied to change detection, trend analysis, and phenology and seasonal characteristics extractions. Numéro de notice : A2022-384 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14092280 Date de publication en ligne : 09/05/2022 En ligne : https://doi.org/10.3390/rs14092280 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100662
in Remote sensing > vol 14 n° 9 (May-1 2022) . - n° 2280[article]Aboveground biomass of salt-marsh vegetation in coastal wetlands: Sample expansion of in situ hyperspectral and Sentinel-2 data using a generative adversarial network / Chen Chen in Remote sensing of environment, vol 270 (March 2022)PermalinkAre northern German Scots pine plantations climate smart? The impact of large-scale conifer planting on climate, soil and the water cycle / Christoph Leuschner in Forest ecology and management, vol 507 (March-1 2022)PermalinkAssessing the dependencies of scots pine (Pinus sylvestris L.) structural characteristics and internal wood property variation / Ville Kankare in Forests, vol 13 n° 3 (March 2022)PermalinkChanges of tree stem biomass in European forests since 1950 / Aleksandr Lebedev in Journal of forest science, vol 68 n° 3 (March 2022)PermalinkEstimating aboveground biomass of urban forest trees with dual-source UAV acquired point clouds / Jiayuan Lin in Urban Forestry & Urban Greening, vol 69 (March 2022)PermalinkAboveground biomass estimation of an agro-pastoral ecology in semi-arid Bundelkhand region of India from Landsat data: a comparison of support vector machine and traditional regression models / Dibyendu Deb in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkAnalysis of spatio-temporal changes in forest biomass in China / Weiyi Xu in Journal of Forestry Research, vol 33 n° 1 (February 2022)PermalinkFive decades of ground flora changes in a temperate forest: The good, the bad and the ambiguous in biodiversity terms / K.J. Kirby in Forest ecology and management, vol 505 (February-1 2022)PermalinkSurvival time and mortality rate of regeneration in the deep shade of a primeval beech forest / R. Petrovska in European Journal of Forest Research, vol 141 n° 1 (February 2022)PermalinkCombined use of Sentinel-1 and Sentinel-2 data for improving above-ground biomass estimation / Narissara Nuthammachot in Geocarto international, vol 37 n° 2 ([15/01/2022])Permalink