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Monitoring spatiotemporal soil moisture changes in the subsurface of forest sites using electrical resistivity tomography (ERT) / Julian Fäth in Journal of Forestry Research, vol 33 n° 5 (October 2022)  

Public [article]  inJournal of Forestry Research > vol 33 n° 5 (October 2022) . - pp 1649 - 1662 Titre : Monitoring spatiotemporal soil moisture changes in the subsurface of forest sites using electrical resistivity tomography (ERT) Type de document : Article/Communication Auteurs : Julian Fäth, Auteur ; Julius Kunz, Auteur ; Christof Kneisel, Auteur Année de publication : 2022 Article en page(s) : pp 1649 - 1662 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Bavière (Allemagne) [Termes IGN] changement climatique [Termes IGN] détection de changement [Termes IGN] données spatiotemporelles [Termes IGN] écologie forestière [Termes IGN] forêt tempérée [Termes IGN] humidité du sol [Termes IGN] résistivité [Termes IGN] sécheresse [Termes IGN] série temporelle [Termes IGN] tomographie [Termes IGN] variation saisonnière Résumé : (auteur) The effects of drought on tree mortality at forest stands are not completely understood. For assessing their water supply, knowledge of the small-scale distribution of soil moisture as well as its temporal changes is a key issue in an era of climate change. However, traditional methods like taking soil samples or installing data loggers solely collect parameters of a single point or of a small soil volume. Electrical resistivity tomography (ERT) is a suitable method for monitoring soil moisture changes and has rarely been used in forests. This method was applied at two forest sites in Bavaria, Germany to obtain high-resolution data of temporal soil moisture variations. Geoelectrical measurements (2D and 3D) were conducted at both sites over several years (2015–2018/2020) and compared with soil moisture data (matric potential or volumetric water content) for the monitoring plots. The greatest variations in resistivity values that highly correlate with soil moisture data were found in the main rooting zone. Using the ERT data, temporal trends could be tracked in several dimensions, such as the interannual increase in the depth of influence from drought events and their duration, as well as rising resistivity values going along with decreasing soil moisture. The results reveal that resistivity changes are a good proxy for seasonal and interannual soil moisture variations. Therefore, 2D- and 3D-ERT are recommended as comparatively non-laborious methods for small-spatial scale monitoring of soil moisture changes in the main rooting zone and the underlying subsurface of forested sites. Higher spatial and temporal resolution allows a better understanding of the water supply for trees, especially in times of drought. Numéro de notice : A2022-778 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s11676-022-01498-x Date de publication en ligne : 18/06/2022 En ligne : https://doi.org/10.1007/s11676-022-01498-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101838 [article]

Tracing drought effects from the tree to the stand growth in temperate and Mediterranean forests: insights and consequences for forest ecology and management / Hans Pretzsch in European Journal of Forest Research, vol 141 n° 4 (August 2022)  

Public [article]  inEuropean Journal of Forest Research > vol 141 n° 4 (August 2022) . - pp 727 - 751 Titre : Tracing drought effects from the tree to the stand growth in temperate and Mediterranean forests: insights and consequences for forest ecology and management Type de document : Article/Communication Auteurs : Hans Pretzsch, Auteur ; Miren del Rio, Auteur ; Rüdiger Grote, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 727 - 751 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Bavière (Allemagne) [Termes IGN] coefficient de Gini [Termes IGN] croissance des arbres [Termes IGN] écologie forestière [Termes IGN] Espagne [Termes IGN] Fagus sylvatica [Termes IGN] forêt méditerranéenne [Termes IGN] forêt tempérée [Termes IGN] gestion forestière [Termes IGN] mortalité [Termes IGN] Picea abies [Termes IGN] sécheresse [Termes IGN] stress hydrique [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) How drought affects tree and stand growth is an old question, but is getting unprecedented relevance in view of climate change. Stress effects related to drought have been mostly studied at the individual tree level, mostly investigating dominant trees and using their responses as indicator for the impact at the stand level. However, findings at tree and stand level may differ, as the stand responses include interactions and feedbacks that may buffer or aggravate what is observed at the individual tree level. Here, we trace drought effects on growth and development from tree to the stand scale. Therefore, we analyse annually measured data from long-term experiments in temperate and Mediterranean forests. With this analysis, we aim to disclose how well results of dominant tree growth reflect stand-level behaviour, hypothesizing that drought resistance of dominant trees’ can strongly deviate from the overall sensitivity of the stand. First, we theoretically derive how drought responses at the stand level emerge from the tree-level behaviour, thereby considering that potential drought resistance of individual trees is modulated by acclimation and tree–tree interactions at the stand level and that the overall stress response at the stand level results from species-specific and size-dependent individual tree growth and mortality. Second, reviewing respective peer-reviewed literature (24 papers) and complementing findings by own measurements (22 experiments) from temperate and Mediterranean monospecific and mixed-species forests, we are able to reveal main causes for deviations of tree-level and stand-level findings regarding drought stress responses. Using a long-term experiment in Norway spruce (Picea abies (L.) KARST.) and European beech (Fagus sylvatica L.), we provide evidence that the species-dependent and size-dependent reactions matter and how the size–frequency distribution affects the scaling. We show by examples that tree-level derived results may overestimate growth losses by 25%. Third, we investigate the development of the growth dominance coefficient based on measurements gathered at the Bavarian forest climate stations. We show that drought changes stand biomass partitioning in favour of small trees, reduce social differentiation, and homogenize the vertical structure of forests. Finally, we discuss the drought-related consequences of the social class-specific growth reaction patterns for inventory and monitoring and highlight the importance of these findings for understanding site-specific stand dynamics, for forest modelling, and for silvicultural management. Numéro de notice : A2022-640 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10342-022-01451-x Date de publication en ligne : 07/05/2022 En ligne : https://doi.org/10.1007/s10342-022-01451-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101447 [article]

Drought impacts in forest canopy and deciduous tree saplings in Central European forests / Mirela Beloiu in Forest ecology and management, vol 509 (April-1 2022)  

Public [article]  inForest ecology and management > vol 509 (April-1 2022) . - n° 120075 Titre : Drought impacts in forest canopy and deciduous tree saplings in Central European forests Type de document : Article/Communication Auteurs : Mirela Beloiu, Auteur ; Reinhold Stahlmann, Auteur ; Carl Beierkuhnlein, Auteur Année de publication : 2022 Article en page(s) : n° 120075 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Bavière (Allemagne) [Termes IGN] bois mort [Termes IGN] canopée [Termes IGN] dendrométrie [Termes IGN] données de terrain [Termes IGN] écosystème forestier [Termes IGN] jeune arbre [Termes IGN] mortalité [Termes IGN] peuplement mélangé [Termes IGN] phénomène climatique extrême [Termes IGN] Pinophyta [Termes IGN] régénération (sylviculture) [Termes IGN] résilience écologique [Termes IGN] sécheresse [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Forests worldwide are increasingly exposed to extreme weather events. Drought deteriorates the health, structure, and functioning of forests, which can lead to reduced diversity, decreased productivity, and increased tree mortality. Therefore, it is an urgent need to assess the impact of drought on tree species. Due to differences in tree physiology, saplings and mature trees are likely to respond specifically to drought conditions. In contrast to mature trees, little is known about the response of saplings to drought. Here, we combine in-situ field measurements for saplings of deciduous tree species with remote sensing for forest canopy to assess drought damage, recovery, and sapling mortality patterns during a centennial drought (2018, 2019) and beyond (2020). We measured 2051 saplings out of 214 plots in Central Germany. Forest canopy health was assessed using 10 × 10 m resolution satellite observations for the same locations. We (1) demonstrate that forest canopy exhibits long-lasting drought-induced effects, (2) show that saplings have a remarkable capacity to recover from drought and survive a subsequent drought, (3) demonstrate that reduced sapling recovery leads to their mortality, (4) reveal that drought damage on saplings increases from pioneer to non-pioneer species, and mortality is ranking from Sorbus aucuparia > Sambucus nigra > Fraxinus excelsior, Acer campestre, Frangula alnus > Ulmus glabra > Carpinus betulus > Betula pendula, Fagus sylvatica > Acer pseudoplatanus > Quercus petraea > Corylus avellana, Crataegus spp., > Prunus avium, Quercus robur; and (5) link drought response to site conditions, indicating that species diversity and winter precipitation as relevant indicators of tree health. If periods of drought become more frequent, as expected, this could negatively impact mid-term forest recovery, alter long-term tree species assemblages and reduce biodiversity and functional resilience of forest ecosystems. We suggest that models of forest response to drought should differentiate between the forest canopy and understory and also consider species-specific responses as we found a broad spectrum of responses within the same plant functional type of deciduous tree species in terms of drought damage and recovery. Numéro de notice : A2022-191 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120075 Date de publication en ligne : 12/02/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120075 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99947 [article]

A combination of convolutional and graph neural networks for regularized road surface extraction / Jingjing Yan in IEEE Transactions on geoscience and remote sensing, vol 60 n° 2 (February 2022)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 60 n° 2 (February 2022) . - n° 4409113 Titre : A combination of convolutional and graph neural networks for regularized road surface extraction Type de document : Article/Communication Auteurs : Jingjing Yan, Auteur ; Shunping Ji, Auteur ; Yao Wei, Auteur Année de publication : 2022 Article en page(s) : n° 4409113 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Bavière (Allemagne) [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection de contours [Termes IGN] extraction de traits caractéristiques [Termes IGN] extraction du réseau routier [Termes IGN] image aérienne [Termes IGN] jeu de données [Termes IGN] optimisation (mathématiques) [Termes IGN] régression [Termes IGN] réseau neuronal de graphes [Termes IGN] Wuhan (Chine) Résumé : (auteur) Road surface extraction from high-resolution remote sensing images has many engineering applications; however, extracting regularized and smooth road surface maps that reach the human delineation level is a very challenging task, and substantial and time-consuming manual work is usually unavoidable. In this article, to solve this problem, we propose a novel regularized road surface extraction framework by introducing a graph neural network (GNN) for processing the road graph that is preconstructed from the easily accessible road centerlines. The proposed framework formulates the road surface extraction problem as two-sided width inference of the road graph and consists of a convolutional neural network (CNN)-based feature extractor and a GNN model for vertex attribute adjustment. The CNN extracts the high-level abstract features of each vertex in the graph as the input of the GNN and also the road boundary features that allow us to distinguish roads from the background. The GNN propagates and aggregates the features of the vertices in the graph to achieve global optimization of the regression of the regularized widths of the vertices. At the same time, a biased centerline map can also be corrected based on the width prediction result. To the best of the authors’ knowledge, this is the first study to have introduced a GNN to regularized human-level road surface extraction. The proposed method was evaluated on four diverse datasets, and the results show that the proposed method comprehensively outperforms the recent CNN-based segmentation methods and other regularization methods in the intersection over union (IoU) and smoothness score, and a visual check shows that a majority of the prediction results of the proposed method approach the human delineation level. Numéro de notice : A2022-297 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2022.3151688 Date de publication en ligne : 15/02/2022 En ligne : https://doi.org/10.1109/TGRS.2022.3151688 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100355 [article]

Spatiotemporal fusion modelling using STARFM: Examples of Landsat 8 and Sentinel-2 NDVI in Bavaria / Maninder Singh Dhillon in Remote sensing, vol 14 n° 3 (February-1 2022)  

Public [article]  inRemote sensing > vol 14 n° 3 (February-1 2022) . - n° 677 Titre : Spatiotemporal fusion modelling using STARFM: Examples of Landsat 8 and Sentinel-2 NDVI in Bavaria Type de document : Article/Communication Auteurs : Maninder Singh Dhillon, Auteur ; Thorsten Dahms, Auteur ; Carina Kübert-Flock, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 677 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Bavière (Allemagne) [Termes IGN] carte d'occupation du sol [Termes IGN] fusion de données [Termes IGN] image Landsat-8 [Termes IGN] image Sentinel-MSI [Termes IGN] image Terra-MODIS [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] pouvoir de résolution géométrique [Termes IGN] réflectance [Termes IGN] surveillance de la végétation [Termes IGN] utilisation du sol Résumé : (auteur) The increasing availability and variety of global satellite products provide a new level of data with different spatial, temporal, and spectral resolutions; however, identifying the most suited resolution for a specific application consumes increasingly more time and computation effort. The region’s cloud coverage additionally influences the choice of the best trade-off between spatial and temporal resolution, and different pixel sizes of remote sensing (RS) data may hinder the accurate monitoring of different land cover (LC) classes such as agriculture, forest, grassland, water, urban, and natural-seminatural. To investigate the importance of RS data for these LC classes, the present study fuses NDVIs of two high spatial resolution data (high pair) (Landsat (30 m, 16 days; L) and Sentinel-2 (10 m, 5–6 days; S), with four low spatial resolution data (low pair) (MOD13Q1 (250 m, 16 days), MCD43A4 (500 m, one day), MOD09GQ (250 m, one-day), and MOD09Q1 (250 m, eight day)) using the spatial and temporal adaptive reflectance fusion model (STARFM), which fills regions’ cloud or shadow gaps without losing spatial information. These eight synthetic NDVI STARFM products (2: high pair multiply 4: low pair) offer a spatial resolution of 10 or 30 m and temporal resolution of 1, 8, or 16 days for the entire state of Bavaria (Germany) in 2019. Due to their higher revisit frequency and more cloud and shadow-free scenes (S = 13, L = 9), Sentinel-2 (overall R2 = 0.71, and RMSE = 0.11) synthetic NDVI products provide more accurate results than Landsat (overall R2 = 0.61, and RMSE = 0.13). Likewise, for the agriculture class, synthetic products obtained using Sentinel-2 resulted in higher accuracy than Landsat except for L-MOD13Q1 (R2 = 0.62, RMSE = 0.11), resulting in similar accuracy preciseness as S-MOD13Q1 (R2 = 0.68, RMSE = 0.13). Similarly, comparing L-MOD13Q1 (R2 = 0.60, RMSE = 0.05) and S-MOD13Q1 (R2 = 0.52, RMSE = 0.09) for the forest class, the former resulted in higher accuracy and precision than the latter. Conclusively, both L-MOD13Q1 and S-MOD13Q1 are suitable for agricultural and forest monitoring; however, the spatial resolution of 30 m and low storage capacity makes L-MOD13Q1 more prominent and faster than that of S-MOD13Q1 with the 10-m spatial resolution. Numéro de notice : A2022-124 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14030677 Date de publication en ligne : 31/01/2022 En ligne : https://doi.org/10.3390/rs14030677 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99687 [article]

Early detection of spruce vitality loss with hyperspectral data: Results of an experimental study in Bavaria, Germany / Kathrin Einzmann in Remote sensing of environment, vol 266 (December 2021)  

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Shining light on danger / Anonyme in GEO: Geoconnexion international, Vol 20 n° 5 (Autumn 2021)

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Remotely sensing the species of individual trees / Yifang Shi (2020)  

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Accurate modelling of canopy traits from seasonal Sentinel-2 imagery based on the vertical distribution of leaf traits / Tawanda W. Gara in ISPRS Journal of photogrammetry and remote sensing, vol 157 (November 2019)  

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Mapping leaf chlorophyll content from Sentinel-2 and RapidEye data in spruce stands using the invertible forest reflectance model / Roshanak Darvishzadeh in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)  

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CNN-based dense image matching for aerial remote sensing images / Shunping Ji in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 6 (June 2019)  

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Variation of leaf angle distribution quantified by terrestrial LiDAR in natural European beech forest / Jing Liu in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)  

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Simultaneous chain-forming and generalization of road networks / Susanne Wenzel in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)  

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Estimation and uncertainty of the mixing effects on Scots pine—European beech productivity from national forest inventories data / Sonia Condés in Forests, vol 9 n° 9 (September 2018)  

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Adaptive stopping criterion for top-down segmentation of ALS point clouds in temperate coniferous forests / Nina Amiri in ISPRS Journal of photogrammetry and remote sensing, vol 141 (July 2018)  

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