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Are pine-oak mixed stands in Mediterranean mountains more resilient to drought than their monospecific counterparts? / Francisco J. Muñoz-Gálvez in Forest ecology and management, vol 484 ([15/03/2021])
[article]
Titre : Are pine-oak mixed stands in Mediterranean mountains more resilient to drought than their monospecific counterparts? Type de document : Article/Communication Auteurs : Francisco J. Muñoz-Gálvez, Auteur ; Asier Herrero, Auteur ; Maria Esther Pérez-Corona, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 118955 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] changement climatique
[Termes IGN] croissance des arbres
[Termes IGN] Espagne
[Termes IGN] forêt méditerranéenne
[Termes IGN] gestion forestière
[Termes IGN] module linéaire
[Termes IGN] peuplement mélangé
[Termes IGN] Pinus sylvestris
[Termes IGN] Quercus pyrenaica
[Termes IGN] sécheresse
[Termes IGN] service écosystémique
[Termes IGN] vulnérabilité
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Climate change projections point to an increase in the intensity and frequency of extreme drought events with important negative impacts on forest functioning. Predicting these impacts constitutes a crucial challenge for forest managers and for the maintenance of ecosystem services supply. Promoting mixed stands seems a promising strategy for adapting forest ecosystems to ongoing climate change. However, some uncertainty exists regarding whether admixture can improve growth resilience to extreme drought events. Here, we aim to assess tree growth response to drought in mixed and monospecific stands of Pinus sylvestris L. and Quercus pyrenaica Willd. in central Spain. We built tree-ring chronologies and evaluated tree growth sensitivity to water availability and growth resilience components to extreme droughts using linear mixed models. We found contrasting species- and climate-specific responses to admixture. Q. pyrenaica growth was significantly higher in mixed than in monospecific stands, especially in years without water limitations, while P. sylvestris showed higher growth in mixed stands under dry conditions. However, our results showed a species-specific trade-off between resistance and recovery. While P. sylvestris showed higher resistance but lower recovery to drought events in mixed than monospecific stands, Q. pyrenaica showed higher recovery but lower resistance. This trade-off might explain the absence of admixture effects on species resilience. Our results highlight the importance of considering species-specific responses to water availability and associated trade-offs when evaluating admixture effects on drought vulnerability. Overall, we show a positive effect of admixture on the long-term growth stability in response to average climate conditions, but no effects in short-term resilience capacity to increasingly common extreme dry conditions. Consequently, admixture can promote forest productivity stability but should be carefully considered as a management solution for promoting the resilience of Mediterranean mountain forests to increasing aridity. Numéro de notice : A2021-264 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.118955 Date de publication en ligne : 25/01/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.118955 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97316
in Forest ecology and management > vol 484 [15/03/2021] . - n° 118955[article]Aggregating land-use polygons considering line features as separating map elements / Sven Gedicke in Cartography and Geographic Information Science, vol 48 n° 2 (March 2021)
[article]
Titre : Aggregating land-use polygons considering line features as separating map elements Type de document : Article/Communication Auteurs : Sven Gedicke, Auteur ; Johannes Oehrlein, Auteur ; Jan‐Henrik Haunert, Auteur Année de publication : 2021 Article en page(s) : pp 124 - 139 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] agrégation spatiale
[Termes IGN] algorithme du recuit simulé
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] méthode heuristique
[Termes IGN] optimisation (mathématiques)
[Termes IGN] réseau routier
[Termes IGN] utilisation du sol
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) Map generalization is the process of deriving small-scale target maps from a large-scale source map or database while preserving valuable information. In this paper we focus on topographic data, in particular areas of different land-use classes and line features representing the road network. When reducing the map scale, some areas need to be merged to larger composite regions. This process is known as area aggregation. Given a planar partition of areas, one usually aims to build geometrically compact regions of sufficient size while keeping class changes small. Since line features (e.g. roads) are perceived as separating elements in a map, we suggest integrating them into the process of area aggregation. Our aim is that boundaries of regions coincide with line features in such a way that strokes (i.e. chains of line features with small angles of deflection) are not broken into short sections. Complementing the criteria of compact regions and preserving land-use information, we consider this aim as a third criterion. Regarding all three criteria, we formalize an optimization problem and solve it with a heuristic approach using simulated annealing. Our evaluation is based on experiments with different parameter settings. In particular, we compare results of a baseline method that considers two criteria, namely compactness and class changes, with results of our new method that additionally considers our stroke-based criterion. Our results show that this third criterion can be substantially improved while keeping the quality with respect to the original two criteria on a similar level. Numéro de notice : A2021-180 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1851613 Date de publication en ligne : 26/01/2021 En ligne : https://doi.org/10.1080/15230406.2020.1851613 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97067
in Cartography and Geographic Information Science > vol 48 n° 2 (March 2021) . - pp 124 - 139[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2021021 RAB Revue Centre de documentation En réserve L003 Disponible Analysis of plot-level volume increment models developed from machine learning methods applied to an uneven-aged mixed forest / Seyedeh Kosar Hamidi in Annals of Forest Science, vol 78 n° 1 (March 2021)
[article]
Titre : Analysis of plot-level volume increment models developed from machine learning methods applied to an uneven-aged mixed forest Type de document : Article/Communication Auteurs : Seyedeh Kosar Hamidi, Auteur ; Eric K. Zenner, Auteur ; Mahmoud Bayat, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 4 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Acer velutinum
[Termes IGN] Alnus cordata
[Termes IGN] analyse comparative
[Termes IGN] apprentissage automatique
[Termes IGN] Carpinus betulus
[Termes IGN] classification barycentrique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par réseau neuronal
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] dynamique de la végétation
[Termes IGN] écosystème forestier
[Termes IGN] Fagus orientalis
[Termes IGN] forêt inéquienne
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Iran
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle de simulation
[Termes IGN] peuplement mélangé
[Termes IGN] régression linéaire
[Termes IGN] volume en bois
[Vedettes matières IGN] SylvicultureRésumé : (auteur) Key message: We modeled 10-year net stand volume growth with four machine learning (ML) methods, i.e., artificial neural networks (ANN), support vector machines (SVM), random forests (RF), and nearest neighbor analysis (NN), and with linear regression analysis. Incorporating interactions of multiple variables, the ML methods ANN and SVM predicted nonlinear system behavior and unraveled complex relations with greater accuracy than regression analysis.
Context: Investigating the quantitative and qualitative characteristics of short-term forest dynamics is essential for testing whether the desired goals in forest-ecosystem conservation and restoration are achieved. Inventory data from the Jojadeh section of the Farim Forest located in the uneven-aged, mixed Hyrcanian Forest were used to model and predict 10-year net annual stand volume increment with new machine learning technologies.
Aims: The main objective of this study was to predict net annual stand volume increment as the preeminent factor of forest growth and yield models.
Methods: In the current study, volume increment was modeled from two consecutive inventories in 2003 and 2013 using four machine learning techniques that used physiographic data of the forest as input for model development: (i) artificial neural networks (ANN), (ii) support vector machines (SVM), (iii) random forests (RF), and (iv) nearest neighbor analysis (NN). Results from the various machine learning technologies were compared against results produced with regression analysis.
Results: ANNs and SVMs with a linear kernel function that incorporated field-measurements of terrain slope and aspect as input variables were able to predict plot-level volume increment with a greater accuracy (94%) than regression analysis (87%).
Conclusion: These results provide compelling evidence for the added utility of machine learning technologies for modeling plot-level volume increment in the context of forest dynamics and management.Numéro de notice : A2021-071 Affiliation des auteurs : non IGN Thématique : FORET/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01011-6 Date de publication en ligne : 12/01/2021 En ligne : https://doi.org/10.1007/s13595-020-01011-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96794
in Annals of Forest Science > vol 78 n° 1 (March 2021) . - n° 4[article]Comparison of two parameter recovery methods for the transformation of Pinus sylvestris yield tables into a diameter distribution model / Francisco Mauro in Annals of Forest Science, vol 78 n° 1 (March 2021)
[article]
Titre : Comparison of two parameter recovery methods for the transformation of Pinus sylvestris yield tables into a diameter distribution model Type de document : Article/Communication Auteurs : Francisco Mauro, Auteur ; Antonio Garcia-Abril, Auteur ; Esperanza Ayuga-Téllez, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 12 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] croissance des arbres
[Termes IGN] densité de la végétation
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] diamètre des arbres
[Termes IGN] distribution spatiale
[Termes IGN] Espagne
[Termes IGN] Pinus sylvestris
[Termes IGN] structure d'un peuplement forestier
[Vedettes matières IGN] SylvicultureRésumé : (auteur) Key message: We successfully transformed Pinus sylvestris yield tables into diameter distribution models. The best results were obtained with the parameter recovery method based on both mean and quadratic mean diameter, which explained 70% of the variability of frequencies by diameter classes and provided better results in the analysis of errors. On the other hand, the method based on stand density, dominant diameter and quadratic mean diameter explained less variability of frequencies by diameter classes (64.4%).
Context: Old datasets used to develop yield table models can be recovered to transform those yield tables into diameter distribution models that provide a more detailed description of size variability and forest structure.
Methods: We compared two different parameter recovery methods, one based on both mean and quadratic mean diameter and another one based on dominant diameter, stand density and quadratic mean diameter and used a set of 104 even aged plots to analyze the performance of the said methods for the transformation of Pinus sylvestris L yield tables in central Spain into a diameter distribution model.
Results: The parameter recovery method based on both mean and quadratic mean diameter explained 70% of the variability of frequencies by diameter classes and provided better results than the method based on stand density, dominant diameter and quadratic mean diameter that explained 64.4% of the variability of frequencies by diameter classes. However, more important than the method itself were the errors that propagated from the models predicting the different variables used in the parameter recovery.
Conclusion: Based on the results from the analysis of errors by diameter classes, the method using both mean and quadratic mean diameter outperformed the method using dominant diameter, stand density and quadratic mean diameter and is the best option to transform P. sylvestris yield tables into diameter distribution models.Numéro de notice : A2021-164 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-021-01028-5 Date de publication en ligne : 28/01/2021 En ligne : https://doi.org/10.1007/s13595-021-01028-5 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97094
in Annals of Forest Science > vol 78 n° 1 (March 2021) . - n° 12[article]Detection of subpixel targets on hyperspectral remote sensing imagery based on background endmember extraction / Xiaorui Song in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)
[article]
Titre : Detection of subpixel targets on hyperspectral remote sensing imagery based on background endmember extraction Type de document : Article/Communication Auteurs : Xiaorui Song, Auteur ; Ling Zou, Auteur ; Lingda Wu, Auteur Année de publication : 2021 Article en page(s) : pp 2365 - 2377 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] détection de cible
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] image à basse résolution
[Termes IGN] image hyperspectrale
[Termes IGN] méthode robuste
[Termes IGN] précision infrapixellaireRésumé : (Auteur) The low spatial resolution associated with imaging spectrometers has caused subpixel target detection to become a special problem in hyperspectral image (HSI) processing that poses considerable challenges. In subpixel target detection, the size of the target is smaller than that of a pixel, making the spatial information of the target almost useless so that a detection algorithm must rely on the spectral information of the image. To address this problem, this article proposes a subpixel target detection algorithm for hyperspectral remote sensing imagery based on background endmember extraction. First, we propose a background endmember extraction algorithm based on robust nonnegative dictionary learning to obtain the background endmember spectrum of the image. Next, we construct a hyperspectral subpixel target detector based on pixel reconstruction (HSPRD) to perform pixel-by-pixel target detection on the image to be tested using the background endmember spectral matrix and the spectra of known ground targets. Finally, the subpixel target detection results are obtained. The experimental results show that, compared with other existing subpixel target detection methods, the algorithm proposed here can provide the optimum target detection results for both synthetic and real-world data sets. Numéro de notice : A2021-217 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1109/TGRS.2020.3002461 Date de publication en ligne : 24/06/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3002461 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97209
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 3 (March 2021) . - pp 2365 - 2377[article]Development and assessment of rainwater harvesting suitability map using analytical hierarchy process, GIS and RS techniques / Khaled S. Balkhair in Geocarto international, vol 36 n° 4 ([01/03/2021])PermalinkEuropean beech leads to more bioactive humus forms but stronger mineral soil acidification as Norway spruce and Scots pine – Results of a repeated site assessment after 63 and 82 years of forest conversion in Central Germany / Florian Achilles in Forest ecology and management, vol 483 ([01/03/2021])PermalinkFamous charts and forgotten fragments: exploring correlations in early Portuguese nautical cartography / Bruno Almeida in International journal of cartography, vol 7 n° 1 (March 2021)PermalinkA multi-criteria analysis of forest restoration strategies to improve the ecosystem services supply: an application in Central Italy / Alessandro Paletto in Annals of Forest Science, vol 78 n° 1 (March 2021)PermalinkRecent increase in European forest harvests as based on area estimates (Ceccherini et al. 2020a) not confirmed in the French case / Nicolas Picard in Annals of Forest Science, vol 78 n° 1 (March 2021)PermalinkSpatial multi-criteria evaluation in 3D context: suitability analysis of urban vertical development / Kendra Munn in Cartography and Geographic Information Science, vol 48 n° 2 (March 2021)PermalinkSuitability assessment of urban land use in Dalian, China using PNN and GIS / Ziqian Kang in Natural Hazards, vol 106 n° 1 (March 2021)PermalinkTopological integration of BIM and geospatial water utility networks across the building envelope / Thomas Gilbert in Computers, Environment and Urban Systems, vol 86 (March 2021)PermalinkIntegrating runoff map of a spatially distributed model and thematic layers for identifying potential rainwater harvesting suitability sites using GIS techniques / Hamid Karimi in Geocarto international, vol 36 n° 3 ([15/02/2021])PermalinkAn improved ant colony optimization-based algorithm for user-centric multi-objective path planning for ubiquitous environments / Zohreh Masoumi in Geocarto international, vol 36 n° 2 ([01/02/2021])Permalink