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Forest height estimation using a single-pass airborne L-band polarimetric and interferometric SAR system and tomographic techniques / Yue Huang in Remote sensing, Vol 13 n° 3 (February 2021)
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Titre : Forest height estimation using a single-pass airborne L-band polarimetric and interferometric SAR system and tomographic techniques Type de document : Article/Communication Auteurs : Yue Huang, Auteur ; Qiaoping Zhang, Auteur ; Laurent Ferro-Famil, Auteur Année de publication : 2021 Article en page(s) : n° 487 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes descripteurs IGN] Alberta (Canada)
[Termes descripteurs IGN] bande L
[Termes descripteurs IGN] forêt boréale
[Termes descripteurs IGN] hauteur des arbres
[Termes descripteurs IGN] interféromètrie par radar à antenne synthétique
[Termes descripteurs IGN] inventaire forestier (techniques et méthodes)
[Termes descripteurs IGN] modèle numérique de surface
[Termes descripteurs IGN] modèle numérique de terrain
[Termes descripteurs IGN] polarimétrie radar
[Termes descripteurs IGN] surveillance forestière
[Termes descripteurs IGN] tomographie radarRésumé : (auteur) This paper addresses forest height estimation for boreal forests at the test site of Edson in Alberta, Canada, using dual-baseline PolInSAR dataset measured by Intermap’s single-pass system. This particular dataset is acquired by using both ping-pong and non-ping-pong modes, which permit forming a dual-baseline TomoSAR configuration, i.e., an extreme configuration for tomographic processing. A tomographic approach, based on polarimetric Capon and MUSIC estimators, is proposed to estimate the elevation of tree top and of underlying ground, and hence forest height is estimated. The resulting forest DTM and DSM over the test site are validated against LiDAR-derived estimates, demonstrating the undeniable capability of the single-pass L-band PolInSAR system for forest monitoring. Numéro de notice : A2021-200 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs13030487 date de publication en ligne : 30/01/2021 En ligne : https://doi.org/10.3390/rs13030487 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97153
in Remote sensing > Vol 13 n° 3 (February 2021) . - n° 487[article]Monitoring tree-crown scale autumn leaf phenology in a temperate forest with an integration of PlanetScope and drone remote sensing observations / Shengbiao Wu in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)
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Titre : Monitoring tree-crown scale autumn leaf phenology in a temperate forest with an integration of PlanetScope and drone remote sensing observations Type de document : Article/Communication Auteurs : Shengbiao Wu, Auteur ; Jing Wang, Auteur ; Zhengbing Yan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 36 - 48 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] Chine
[Termes descripteurs IGN] forêt tempérée
[Termes descripteurs IGN] houppier
[Termes descripteurs IGN] image captée par drone
[Termes descripteurs IGN] image MODIS
[Termes descripteurs IGN] image PlanetScope
[Termes descripteurs IGN] phénologie
[Termes descripteurs IGN] photosynthèse
[Termes descripteurs IGN] série temporelle
[Termes descripteurs IGN] surveillance forestièreRésumé : (auteur) In temperate forests, autumn leaf phenology signals the end of leaf growing season and shows large variability across tree-crowns, which importantly mediates photosynthetic seasonality, hydrological regulation, and nutrient cycling of forest ecosystems. However, critical challenges remain with the monitoring of autumn leaf phenology at the tree-crown scale due to the lack of spatially explicit information for individual tree-crowns and high (spatial and temporal) resolution observations with nadir view. Recent availability of the PlanetScope constellation with a 3 m spatial resolution and near-daily nadir view coverage might help address these observational challenges, but remains underexplored. Here we developed an integration of PlanetScope with drone observations for improved monitoring of crown-scale autumn leaf phenology in a temperate forest in Northeast China. This integration includes: 1) visual identification of individual tree-crowns (and species) from drone observations; 2) extraction of time series of PlanetScope vegetation indices (VIs) for each identified tree-crown; 3) derivation of three metrics of autumn leaf phenology from the extracted VI time series, including the start of fall (SOF), middle of fall (MOF), and end of fall (EOF); and 4) accuracy assessments of the PlanetScope-derived phenology metrics with reference from local phenocams. Our results show that (1) the PlanetScope-drone integration captures large inter-crown phenological variations, with a range of 28 days, 25 days, and 30 days for SOF, MOF, and EOF, respectively, (2) the extracted crown-level phenology metrics strongly agree with those derived from local phenocams, with a root-mean-square-error (RMSE) of 4.1 days, 3.0 days and 5.4 days for SOF, MOF, and EOF, respectively, and (3) PlanetScope maps large variations in autumn leaf phenology over the entire forest landscape with spatially explicit information. These results demonstrate the ability of our proposed method in monitoring the large spatial heterogeneity of crown-scale autumn leaf phenology in the temperate forest, suggesting the potential of using high-resolution satellites to advance crown-scale phenology studies over large geographical areas. Numéro de notice : A2021-011 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.017 date de publication en ligne : 13/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.017 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96305
in ISPRS Journal of photogrammetry and remote sensing > vol 171 (January 2021) . - pp 36 - 48[article]Réservation
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Titre : SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery Type de document : Article/Communication Auteurs : Marie Ballère, Auteur ; Alexandre Bouvet, Auteur ; Stéphane Mermoz, Auteur ; Thuy Le Toan, Auteur ; Thierry Koleck, Auteur ; Caroline Bedeau, Auteur ; Mathilde André, Auteur ; Elodie Forestier, Auteur ; Pierre-Louis Frison , Auteur ; Cédric Lardeux, Auteur
Année de publication : 2021 Projets : 1-Pas de projet / Article en page(s) : n° 112159 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes descripteurs IGN] forêt tropicale
[Termes descripteurs IGN] Guyane (département français)
[Termes descripteurs IGN] image radar moirée
[Termes descripteurs IGN] image Sentinel-SAR
[Termes descripteurs IGN] surveillance forestière
[Termes descripteurs IGN] temps réelRésumé : (auteur) French Guiana forests cover 8 million hectares. With 98% of emerged land covered by forests, French Guiana is the area with the highest proportion of forest cover in the world. These forests are home to an exceptionally rich and diverse wealth of biodiversity that is both vulnerable and under threat due to high levels of pressure from human activity. As part of the French territory, French Guiana benefits from determined and continuous national efforts in the preservation of biodiversity and the environmental functionalities of ecosystems. The loss and fragmentation of forest cover caused by gold mining (legal and illegal), smallholder agriculture and forest exploitation, are considered as small-scale disturbances, although representing strong effects to vulnerable natural habitats, landscapes, and local populations. To monitor forest management programs and combat illegal deforestation and forest opening near-real time alerts system based on remote sensing data are required. For this large territory under frequent cloud cover, Synthetic-Aperture Radar (SAR) data appear to be the best adapted. In this paper, a method for forest alerts in a near-real time context based on Sentinel-1 data over the whole of French Guiana (83,534 km2) was developed and evaluated. The assessment was conducted for 2 years between 2016 and 2018 and includes comparisons with reference data provided by French Guiana forest organizations and comparisons with the existing University of Maryland Global Land Analysis and Discovery Forest Alerts datasets based on Landsat data. The reference datasets include 1,867 plots covering 2,124.5 ha of gold mining, smallholder agriculture and forest exploitation. The validation results showed high user accuracies (96.2%) and producer accuracies (81.5%) for forest loss detection, with the latter much higher than for optical forest alerts (36.4%). The forest alerts maps were also compared in terms of detection timing, showing systematic temporal delays of up to one year in the optical method compared to the SAR method. These results highlight the benefits of SAR over optical imagery for forest alerts detection in French Guiana. Finally, the potential of the SAR method applied to tropical forests is discussed. The SAR-based map of this study is available on http://cesbiomass.net/. Numéro de notice : A2021-066 Affiliation des auteurs : UGE-LaSTIG+Ext (2020- ) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2020.112159 date de publication en ligne : 05/11/2020 En ligne : https://doi.org/10.1016/j.rse.2020.112159 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96937
in Remote sensing of environment > Vol 252 (January 2021) . - n° 112159[article]Recent growth trends of conifers across Western Europe are controlled by thermal and water constraints and favored by forest heterogeneity / Clémentine Ols in Science of the total environment, vol 742 ([10/11/2020])
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Titre : Recent growth trends of conifers across Western Europe are controlled by thermal and water constraints and favored by forest heterogeneity Type de document : Article/Communication Auteurs : Clémentine Ols , Auteur ; Jean-Christophe Hervé (1961-2017)
, Auteur ; Jean-Daniel Bontemps
, Auteur
Année de publication : 2020 Projets : ARBRE/GRECOFOR-CC / Bontemps, Jean-Daniel Article en page(s) : n° 140453 Note générale : bibliographie
corrigendum : https://doi.org/10.1016/j.scitotenv.2020.143185Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] changement climatique
[Termes descripteurs IGN] croissance végétale
[Termes descripteurs IGN] inventaire forestier national (données France)
[Termes descripteurs IGN] modèle de croissance
[Termes descripteurs IGN] pinophyta
[Termes descripteurs IGN] surveillance forestière
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Tree growing conditions are changing rapidly in the face of climate change. Capturing tree-growth response to such changes across environmental contexts and tree species calls for a continuous forest monitoring over space. Based on >10,000 tree-ring measurements sampled across the systematic grid of the continuous French national forest inventory (NFI) over the 2006–2016 period, we evaluated the radial growth trends of eight conifer tree species prevalent in European forests across their native and introduced ranges and various bioclimatic contexts (n = 16 forest systems). For each forest system, radial increments were filtered out from tree, plot, soil and climatic normal influences to isolate environment-driven growth signals and quantify residual time-series. Associated growth trends across forest systems were then confronted against environmental variables (e.g. short-term averages and trends in seasonal climate). Trends for a given species were systematically more positive in cooler contexts (higher elevations or northern distribution margins) than in warmer contexts (plains). Decreases and increases in precipitation regimes were found to be associated with negative and positive tree growth trends, respectively. Remarkably, positive growth trends were mainly observed for native forest systems (7/9) and negative trends for introduced systems (5/7). Native forests showed a more heterogeneous forest structure as compared to introduced forests that, in line with observed positive dependence of tree growth trends onto both water availability and forest heterogeneity, appears to modulate the competitive pressure on water resource with ongoing summer maximum temperature increase. Over a short annually-resolved study period, we were able to capture tree growth responses coherent with climate change across diverse forest ecosystems. With ongoing accumulation of data, the continuous French NFI hence arises as powerful support to monitoring climate change effects on forests. Numéro de notice : A2020-509 Affiliation des auteurs : LIF (2012-2019) Autre URL associée : vers HAL Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.scitotenv.2020.140453 date de publication en ligne : 23/06/2020 En ligne : https://doi.org/10.1016/j.scitotenv.2020.140453 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95767
in Science of the total environment > vol 742 [10/11/2020] . - n° 140453[article]Documents numériques
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Recent growth trends of conifers ... Annexes - pdf auteurAdobe Acrobat PDFWide-area near-real-time monitoring of tropical forest degradation and deforestation using Sentinel-1 / Dirk Hoekman in Remote sensing, vol 12 n° 19 (October 2020)
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Titre : Wide-area near-real-time monitoring of tropical forest degradation and deforestation using Sentinel-1 Type de document : Article/Communication Auteurs : Dirk Hoekman, Auteur ; Boris Kooij, Auteur ; Marcela J. Quiñones, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 32 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] Amazonie
[Termes descripteurs IGN] Bornéo, île de
[Termes descripteurs IGN] déboisement
[Termes descripteurs IGN] dégradation de l'environnement
[Termes descripteurs IGN] détection de changement
[Termes descripteurs IGN] forêt tropicale
[Termes descripteurs IGN] image radar
[Termes descripteurs IGN] image Sentinel-SAR
[Termes descripteurs IGN] image TerraSAR-X
[Termes descripteurs IGN] modèle physique
[Termes descripteurs IGN] série temporelle
[Termes descripteurs IGN] surveillance forestière
[Termes descripteurs IGN] tourbièreRésumé : (auteur) The use of Sentinel-1 (S1) radar for wide-area, near-real-time (NRT) tropical-forest-change monitoring is discussed, with particular attention to forest degradation and deforestation. Since forest change can relate to processes ranging from high-impact, large-scale conversion to low-impact, selective logging, and can occur in sites having variable topographic and environmental properties such as mountain slopes and wetlands, a single approach is insufficient. The system introduced here combines time-series analysis of small objects identified in S1 data, i.e., segments containing linear features and apparent small-scale disturbances. A physical model is introduced for quantifying the size of small (upper-) canopy gaps. Deforestation detection was evaluated for several forest landscapes in the Amazon and Borneo. Using the default system settings, the false alarm rate (FAR) is very low (less than 1%), and the missed detection rate (MDR) varies between 1.9% ± 1.1% and 18.6% ± 1.0% (90% confidence level). For peatland landscapes, short radar detection delays up to several weeks due to high levels of soil moisture may occur, while, in comparison, for optical systems, detection delays up to 10 months were found due to cloud cover. In peat swamp forests, narrow linear canopy gaps (road and canal systems) could be detected with an overall accuracy of 85.5%, including many gaps barely visible on hi-res SPOT-6/7 images, which were used for validation. Compared to optical data, subtle degradation signals are easier to detect and are not quickly lost over time due to fast re-vegetation. Although it is possible to estimate an effective forest-cover loss, for example, due to selective logging, and results are spatiotemporally consistent with Sentinel-2 and TerraSAR-X reference data, quantitative validation without extensive field data and/or large hi-res radar datasets, such as TerraSAR-X, remains a challenge. Numéro de notice : A2020-633 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs12193263 date de publication en ligne : 08/10/2020 En ligne : https://doi.org/10.3390/rs12193263 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96056
in Remote sensing > vol 12 n° 19 (October 2020) . - 32 p.[article]Using machine learning to synthesize spatiotemporal data for modelling DBH-height and DBH-height-age relationships in boreal forests / Jiaxin Chen in Forest ecology and management, Vol 466 (15 June 2020)
PermalinkAnalysing the quality of Swiss National Forest Inventory measurements of woody species richness / Berthold Traub in Forest ecosystems, vol 7 (2020)
PermalinkYear-to-year crown condition poorly contributes to ring width variations of beech trees in French ICP level I network / Clara Tallieu in Forest ecology and management, Vol 465 (1st June 2020)
PermalinkLa croissance des forêts et les changements environnementaux / François Lebourgeois in Sciences, eaux & territoires, n° 33 (avril 2020)
PermalinkAssessing the shape accuracy of coarse resolution burned area identifications / Michael L. Humber in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
PermalinkRegional-scale forest mapping over fragmented landscapes using global forest products and Landsat time series classification / Viktor Myroniuk in Remote sensing, vol 12 n° 1 (January 2020)
PermalinkAutomated fusion of forest airborne and terrestrial point clouds through canopy density analysis / Wenxia Dai in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)
PermalinkLe point de vue de l'Inventaire Forestier National (IFN) [sic] / François Morneau in Rendez-vous techniques, n° 58-59-60 ([01/09/2019])
PermalinkMonitoring the structure of forest restoration plantations with a drone-lidar system / D.R.A. Almeida in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)
PermalinkNear real-time deforestation detection in Malaysia and Indonesia using change vector analysis with three sensors / Pauline Perbet in International Journal of Remote Sensing IJRS, vol 40 n°19 (February 2019)
PermalinkÉvaluation de la dégradation des forêts primaires par télédétection dans un espace de front pionnier consolidé d’Amazonie orientale (Paragominas) / Ali Fadhil Hasan (2019)
PermalinkCan forest structural diversity be a response to anthropogenic stress? A case study in old-growth fir Abies alba Mill. stands / Rafał Podlaski in Annals of Forest Science [en ligne], vol 75 n° 4 (December 2018)
PermalinkPotential of Sentinel-1 data for monitoring temperate mixed forest phenology / Pierre-Louis Frison in Remote sensing, vol 10 n° 12 (December 2018)
PermalinkEstimation of forest above-ground biomass by geographically weighted regression and machine learning with Sentinel imagery / Lin Chen in Forests, vol 9 n° 10 (October 2018)
PermalinkManaging tree species diversity and ecosystem functions through coexistence mechanisms / Thomas Cordonnier in Annals of Forest Science [en ligne], vol 75 n° 3 (September 2018)
PermalinkDigital aerial photogrammetry for assessing cumulative spruce budworm defoliation and enhancing forest inventories at a landscape-level / Tristan R.H. Goodbody in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)
PermalinkIntra-annual phenology for detecting understory plant invasion in urban forests / Kunwar K. Singh in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)
PermalinkConception d’une méthode radar de suivi bimensuel des déforestations et d’une méthode optique de classification d’occupation des sols / Luc Baudoux (2018)
PermalinkAdapter les itinéraires sylvicoles pour atténuer les effets du changement climatique. Résultats pour la chênaie sessiliflore française à partir des réseaux d’expérimentations sylvicoles / François Lebourgeois in Revue forestière française [en ligne], vol 69 n° 1 (octobre 2017)
PermalinkCrown bulk density and fuel moisture dynamics in Pinus pinaster stands are neither modified by thinning nor captured by the Forest Fire Weather Index / Marc Soler Martin in Annals of Forest Science [en ligne], vol 74 n° 3 (September 2017)
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