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The delineation of tea gardens from high resolution digital orthoimages using mean-shift and supervised machine learning methods / Akhtar Jamil in Geocarto international, vol 36 n° 7 ([15/04/2021])
[article]
Titre : The delineation of tea gardens from high resolution digital orthoimages using mean-shift and supervised machine learning methods Type de document : Article/Communication Auteurs : Akhtar Jamil, Auteur ; Bulent Bayram, Auteur Année de publication : 2021 Article en page(s) : pp 758 - 772 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme de décalage moyen
[Termes IGN] analyse d'image orientée objet
[Termes IGN] apprentissage automatique
[Termes IGN] arbre de décision
[Termes IGN] Camellia sinensis
[Termes IGN] classification dirigée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par réseau neuronal
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] exploitation agricole
[Termes IGN] extraction de la végétation
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] orthoimage
[Termes IGN] segmentation hiérarchique
[Termes IGN] TurquieRésumé : (Auteur) Rize district is an important tea production site in Turkey, which is known for high quality tea. Determining the temporal changes is very crucial from the viewpoint of agricultural management and protection of tea areas. In addition, delineation of tea gardens using photogrammetric evaluation techniques for a single orthoimage takes approximately 8 h of labour work, which is both costly and time-consuming process. To overcome these issues, a method is proposed for demarcation of tea gardens from high-resolution orthoimages. In this article, a hierarchical object-based segmentation using mean-shift (MS) and supervised machine learning (ML) methods are investigated for delineation of tea gardens. First, the MS algorithm was applied to partition the images into homogeneous segments (objects) and then from each segment, various spectral, spatial and textural features were extracted. Finally, four most widely used supervised ML classifiers, support vector machine (SVM), artificial neural network (ANN), random forest (RF), and decision trees (DTs), were selected for classification of objects into tea gardens and other types of trees. Photogrammetrically evaluated tea garden borders were taken as reference data to evaluate the performance of the proposed methods. The experiments showed that all selected supervised classifiers were effective for delineation of the tea gardens from high-resolution images. Numéro de notice : A2021-293 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1622597 Date de publication en ligne : 19/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1622597 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97349
in Geocarto international > vol 36 n° 7 [15/04/2021] . - pp 758 - 772[article]Chemical interaction between Quercus pubescens and its companion species is not emphasized under drought stress / H. Hashoum in European Journal of Forest Research, vol 140 n° 2 (April 2021)
[article]
Titre : Chemical interaction between Quercus pubescens and its companion species is not emphasized under drought stress Type de document : Article/Communication Auteurs : H. Hashoum, Auteur ; J. Gavinet, Auteur ; T. Gauquelin, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 333 - 343 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biochimie
[Termes IGN] Cotinus coggygria
[Termes IGN] croissance des arbres
[Termes IGN] dynamique de la végétation
[Termes IGN] phytobiologie
[Termes IGN] Pinus halepensis
[Termes IGN] Quercus pubescens
[Termes IGN] régénération (sylviculture)
[Termes IGN] sécheresse
[Termes IGN] stress hydrique
[Vedettes matières IGN] ForesterieRésumé : (auteur) How plant–plant interactions will interact with global change drivers such as increased drought during the regeneration phase is a key question to forecast future vegetation dynamics. Chemical interaction and especially allelopathy and drought have been suggested to affect plant performance synergistically, i.e., that plant under drought stress would be more sensitive to allelochemicals and that exposure to allelopathic interactions could increase drought sensitivity through an inhibition of root development and mycorrhization. In this paper, we tested these hypotheses by using a controlled experiment with Quercus pubescens Mill. as a target species and three co-occurring species plus itself as source species. Allelopathic treatments consisted of annual provision of litter and monthly watering with green leaf aqueous extracts during two vegetation seasons starting from oak acorns. During the second vegetation season, a drought stress treatment was added on half of the seedlings. Allelopathy of co-occurring species reduced seedlings dimensions while Q. pubescens treatment increased it. During the second vegetation season, seedling growth rate and physiology were reduced by drought but poorly affected by allelopathic treatment. At the end of the experiment, drought stress and allelopathy from Cotinus coggygria and Pinus halepensis both reduced seedling biomass but had opposite effects on the root/shoot ratio. Drought and allelopathy did not interact significantly and, contrary to our hypothesis, there was a tendency of lower allelopathic effects under drought. Our results suggest that drought and allelopathy could additively alter seedling development, but the opposite effects of allelopathy and drought on the root/shoot ratio call for further experiments testing the interaction between these two factors. Numéro de notice : A2021-399 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-020-01337-w Date de publication en ligne : 25/11/2020 En ligne : https://doi.org/10.1007/s10342-020-01337-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97699
in European Journal of Forest Research > vol 140 n° 2 (April 2021) . - pp 333 - 343[article]A CNN approach to simultaneously count plants and detect plantation-rows from UAV imagery / Lucas Prado Osco in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)
[article]
Titre : A CNN approach to simultaneously count plants and detect plantation-rows from UAV imagery Type de document : Article/Communication Auteurs : Lucas Prado Osco, Auteur ; Mauro Dos Santos de Arruda, Auteur ; Diogo Nunes Gonçalves, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1 - 17 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage profond
[Termes IGN] carte agricole
[Termes IGN] Citrus sinensis
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] comptage
[Termes IGN] cultures
[Termes IGN] détection d'objet
[Termes IGN] extraction de la végétation
[Termes IGN] gestion durable
[Termes IGN] image captée par drone
[Termes IGN] maïs (céréale)
[Termes IGN] rendement agricoleRésumé : (auteur) Accurately mapping croplands is an important prerequisite for precision farming since it assists in field management, yield-prediction, and environmental management. Crops are sensitive to planting patterns and some have a limited capacity to compensate for gaps within a row. Optical imaging with sensors mounted on Unmanned Aerial Vehicles (UAV) is a cost-effective option for capturing images covering croplands nowadays. However, visual inspection of such images can be a challenging and biased task, specifically for detecting plants and rows on a one-step basis. Thus, developing an architecture capable of simultaneously extracting plant individually and plantation-rows from UAV-images is yet an important demand to support the management of agricultural systems. In this paper, we propose a novel deep learning method based on a Convolutional Neural Network (CNN) that simultaneously detects and geolocates plantation-rows while counting its plants considering highly-dense plantation configurations. The experimental setup was evaluated in (a) a cornfield (Zea mays L.) with different growth stages (i.e. recently planted and mature plants) and in a (b) Citrus orchard (Citrus Sinensis Pera). Both datasets characterize different plant density scenarios, in different locations, with different types of crops, and from different sensors and dates. This scheme was used to prove the robustness of the proposed approach, allowing a broader discussion of the method. A two-branch architecture was implemented in our CNN method, where the information obtained within the plantation-row is updated into the plant detection branch and retro-feed to the row branch; which are then refined by a Multi-Stage Refinement method. In the corn plantation datasets (with both growth phases – young and mature), our approach returned a mean absolute error (MAE) of 6.224 plants per image patch, a mean relative error (MRE) of 0.1038, precision and recall values of 0.856, and 0.905, respectively, and an F-measure equal to 0.876. These results were superior to the results from other deep networks (HRNet, Faster R-CNN, and RetinaNet) evaluated with the same task and dataset. For the plantation-row detection, our approach returned precision, recall, and F-measure scores of 0.913, 0.941, and 0.925, respectively. To test the robustness of our model with a different type of agriculture, we performed the same task in the citrus orchard dataset. It returned an MAE equal to 1.409 citrus-trees per patch, MRE of 0.0615, precision of 0.922, recall of 0.911, and F-measure of 0.965. For the citrus plantation-row detection, our approach resulted in precision, recall, and F-measure scores equal to 0.965, 0.970, and 0.964, respectively. The proposed method achieved state-of-the-art performance for counting and geolocating plants and plant-rows in UAV images from different types of crops. The method proposed here may be applied to future decision-making models and could contribute to the sustainable management of agricultural systems. Numéro de notice : A2021-205 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.024 Date de publication en ligne : 13/02/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.024 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97171
in ISPRS Journal of photogrammetry and remote sensing > vol 174 (April 2021) . - pp 1 - 17[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2021041 SL Revue Centre de documentation Revues en salle Disponible 081-2021043 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021042 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Four-year-performance of oak and pine seedlings following mechanical site preparation with lightweight excavators / Noé Dumas in Silva fennica, vol 55 n° 2 (April 2021)
[article]
Titre : Four-year-performance of oak and pine seedlings following mechanical site preparation with lightweight excavators Type de document : Article/Communication Auteurs : Noé Dumas, Auteur ; Mathieu Dassot , Auteur ; Jonathan Pitaud, Auteur ; Lucie Arnaudet, Auteur ; Claudine Richter, Auteur ; Catherine Collet, Auteur Année de publication : 2021 Projets : 3-projet - voir note / Article en page(s) : n° 10409 Note générale : bibliographie
This study was supported by the Ministère de l’Agriculture et de l’Alimentation (agreements E13/2010, E21/2013, E09/2017), the Région Grand-Est (agreement Alsace 871-10-C1) and the Agence de l’Environnement et la Maîtrise de l’Energie (Capsol project).Langues : Anglais (eng) Descripteur : [Termes IGN] contrôle de la végétation
[Termes IGN] Pinus (genre)
[Termes IGN] plantation forestière
[Termes IGN] Pteridium aquilinum
[Termes IGN] Quercus sessiliflora
[Termes IGN] régénération (sylviculture)
[Vedettes matières IGN] ForesterieRésumé : (auteur) Mechanical site preparation methods that used tools mounted on lightweight excavators and that provided localised intensive preparation were tested in eight experimental sites across France where the vegetation was dominated either by Molinia caerulea (L.) Moench or Pteridium aquilinum (L.) Kuhn. Two lightweight tools (Deep Scarifier: DS; Deep Scarifier followed by Multifunction Subsoiler: DS+MS) were tested in pine (Pinus sylvestris L., Pinus nigra var. corsicana (Loudon) Hyl. or Pinus pinaster Aiton) and oak (Quercus petraea (Matt.) Liebl. or Quercus robur L.) plantations. Regional methods commonly used locally (herbicide, disk harrow, mouldboard plow) and experimental methods (repeated herbicide application; untreated control) were used as references in the experiments. Neighbouring vegetation cover, seedling survival, height and basal diameter were assessed over three to five years after plantation. For pines growing in M. caerulea, seedling diameter after four years was 37% and 98% greater in DS and DS+MS, respectively, than in the untreated control. For pines growing in P. aquilinum, it was 62% and 107% greater in the same treatments. For oak, diameter was only 4% and 15% greater in M. caerulea, and 13% and 25% greater in P. aquilinum, in the same treatments. For pines, the survival rate after four years was 26% and 32% higher in M. caerulea and 64% and 70% higher in P. aquilinum, in the same treatments. For oak, it was 3% and 29% higher in M. caerulea and 37% and 31% higher in P. aquilinum. Herbicide, when applied for three or four years after planting, provided the best growth performances for pines growing in M. caerulea and P. aquilinum and for oaks growing in P. aquilinum. For these species and site combinations, DS+MS and DS treatments reduced the neighbouring vegetation cover for one to four years following site preparation. Numéro de notice : A2021-936 Affiliation des auteurs : IGN+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14214/sf.10409 Date de publication en ligne : 29/04/2021 En ligne : https://doi.org/10.14214/sf.10409 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99545
in Silva fennica > vol 55 n° 2 (April 2021) . - n° 10409[article]Streams and rural abandonment are related to the summer activity of the invasive pest Drosophila suzukii in protected European forests / Alberto Maceda-Veiga in Forest ecology and management, vol 485 ([01/04/2021])
[article]
Titre : Streams and rural abandonment are related to the summer activity of the invasive pest Drosophila suzukii in protected European forests Type de document : Article/Communication Auteurs : Alberto Maceda-Veiga, Auteur ; Sergio Albacete, Auteur ; Miguel Carles-Tolrá, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 118942 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] aire protégée
[Termes IGN] Castanea (genre)
[Termes IGN] cours d'eau
[Termes IGN] diptère
[Termes IGN] Espagne
[Termes IGN] foresterie
[Termes IGN] habitat forestier
[Termes IGN] insecte nuisible
[Termes IGN] interaction spatiale
[Termes IGN] migration rurale
[Termes IGN] structure d'un peuplement forestier
[Vedettes matières IGN] SylvicultureRésumé : (auteur) Protected native-forested areas may be occupied by fruit pests, and so, studies exploring the biotic and abiotic determinants of fruit-pest abundance in forested areas may reduce damages in crops and wild forest frugivores. The Spotted Wing Drosophila (SWD) Drosophila suzukii is an economically important fruit pest in many temperate regions around the world. During the dry summer in northwestern Spain, we assessed 24 native riparian and 32 non-riparian chestnut forest patches as non-crop habitats for the SWD. We surveyed chestnut forests in 2017 and found a positive association between spatial proximity of forest patches to streams and SWD captures, which led us to study in 2019 the stream-SWD associations in greater detail. We explored whether native-insect communities and changes in vegetation structure related to rural abandonment were associated with variation in SWD captures, while accounting for the effects of covariates, including stream distance. There were no significant associations in the riparian and non-riparian-habitat surveys between the captures of SWDs and those of native insects, including 22 families of flies and 10 families of parasitic wasps. However, captures of SWDs and of other drosophilid flies were positively related to each other and the direction of the association was reversed by stream distance, which suggests the potential role of streams in regulating interactions among non-riparian insects, including SWD. We also found correlative evidence that degraded riparian forests and the abandonment of traditional forest practices in chestnut forests may be contributing to the spread of SWD. Given the numbers of SWDs in our forest samples were similar to values in August in crop areas, it is advisable that future studies address the impacts of SWD invasion on native forest frugivores, which have been overlooked in studies of this widely distributed invasive species. Numéro de notice : A2021-265 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.118942 Date de publication en ligne : 30/01/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.118942 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97318
in Forest ecology and management > vol 485 [01/04/2021] . - n° 118942[article]Tree extraction and estimation of walnut structure parameters using airborne LiDAR data / Javier Estornell in International journal of applied Earth observation and geoinformation, vol 96 (April 2021)PermalinkAre 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])PermalinkTerrestrial laser scanning intensity captures diurnal variation in leaf water potential / S. Junttila in Remote sensing of environment, Vol 255 (March 2021)PermalinkAnalysis 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)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])PermalinkIs the seasonal variation in frost resistance and plant performance in four oak species affected by changing temperatures? / Maggie Preißer in Forests, vol 12 n° 3 (March 2021)PermalinkKeeping mixtures of Norway spruce and birch in production forests: insights from survey data / Emma Hölmstrom in Scandinavian journal of forest research, vol 36 n° 2-3 ([01/03/2021])PermalinkModeling size-density trajectories of even-aged ash (Fraxinus excelsior L.) stands in France. A baseline to assess the impact of Chalara ash dieback / Noël Le Goff in Annals of Forest Science, vol 78 n° 1 (March 2021)PermalinkSearch for top‐down and bottom‐up drivers of latitudinal trends in insect herbivory in oak trees in Europe / Elena Valdés-Correcher in Global ecology and biogeography, vol 30 n° 3 (March 2021)PermalinkSecondary metabolites in leaves of hybrid aspen are affected by the competitive status and early thinning in dense coppices / Linda Rusalepp in Annals of Forest Science, vol 78 n° 1 (March 2021)Permalink