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sciences de la vie
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Sciences biologiques Sciences naturelles >> Spécialistes des sciences de la vie Vie (biologie) >>Terme(s) spécifique(s) : Mycologie Biologie Botanique Sciences de la santé Zoologie Equiv. LCSH : Life sciences |
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Automated street tree inventory using mobile LiDAR point clouds based on Hough transform and active contours / Amir Hossein Safaie in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)
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[article]
Titre : Automated street tree inventory using mobile LiDAR point clouds based on Hough transform and active contours Type de document : Article/Communication Auteurs : Amir Hossein Safaie, Auteur ; Heidar Rastiveis, Auteur ; Alireza Shams, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 19 - 34 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre remarquable
[Termes IGN] arbre urbain
[Termes IGN] détection d'arbres
[Termes IGN] détection de contours
[Termes IGN] diagramme de Voronoï
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] sécurité routière
[Termes IGN] semis de points
[Termes IGN] transformation de HoughRésumé : (auteur) Trees are important road-side objects, and their geometric information plays an essential role in road studies and safety analyses. This paper proposes an efficient method for the automated creation of a road-side tree inventory using Mobile Terrestrial Lidar System (MTLS) point clouds. In the proposed method ground points are filtered through preprocessing to reduce processing time. Next, tree trunks are detected by performing a Hough Transform (HT) algorithm on several generated raster images from the point clouds. By initiating an approximate area of a tree’s foliage through a Voronoi Tessellation (VT) algorithm, the accurate boundary of the foliage is identified by applying Active Contour (AC) models. By extracting the points within this foliage boundary the geometric characteristics of each tree are obtained. This method was evaluated with two sample point clouds from different MTLS systems, and the algorithm correctly extracted all of the trees from both datasets. Additionally, comparing the calculated parameters with manually observed measures, the accuracy of the obtained geometric parameters were promising. Numéro de notice : A2021-206 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.026 Date de publication en ligne : 14/02/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.026 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97183
in ISPRS Journal of photogrammetry and remote sensing > vol 174 (April 2021) . - pp 19 - 34[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 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)
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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)
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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)
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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]Geovisualization of COVID-19: State of the art and opportunities / Yu Lan in Cartographica, vol 56 n° 1 (Spring 2021)
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Titre : Geovisualization of COVID-19: State of the art and opportunities Type de document : Article/Communication Auteurs : Yu Lan, Auteur ; Michael R. Desjardins, Auteur ; Alexander Hohl, Auteur ; Eric Delmelle, Auteur Année de publication : 2021 Article en page(s) : pp 2 - 13 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de groupement
[Termes IGN] carte interactive
[Termes IGN] carte thématique
[Termes IGN] cube espace-temps
[Termes IGN] données spatiotemporelles
[Termes IGN] Etats-Unis
[Termes IGN] maladie virale
[Termes IGN] modèle dynamique
[Termes IGN] variation saisonnière
[Termes IGN] WebSIG
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Mapping the prevalence and spread of infectious diseases has never been more critical than during the COVID-19 pandemic. A plethora of Web-based GIS dashboards have been created that incorporate basic GIS functionality; these dashboards have served as platforms for rapid data sharing and real-time information, ultimately facilitating decision making. However, many of them have merely focused on presenting and monitoring cumulative or daily incidence of COVID-19 data, disregarding the temporal dimension. In this paper, we review the usefulness of GIS-based dashboards for mapping the prevalence of COVID-19, but also missed opportunities to emphasize the temporal component of the disease (cyclicity, seasonality). We suggest that advanced geovisualization techniques can be used to integrate the temporal component in interactive animated maps illustrating (a) the daily relative risk and the number of days a geographic region has been in a disease cluster, (b) the ratio between the observed and expected number of cases over time, and (c) mortality count dynamics in a space–time cube. We illustrate these approaches by using COVID-19 cases and death counts across the U.S. at the county level from 25 January 2020 to 1 October 2020. We discuss how each of these visualization approaches can promote the understanding of important public health concepts applied to the pandemic such as risk, spread, and mortality. Finally, we suggest future avenues to promote research at the intersection of space–time visualization and infectious diseases. Numéro de notice : A2021-409 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3138/cart-2020-0027 Date de publication en ligne : 15/03/2021 En ligne : https://doi.org/10.3138/cart-2020-0027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97730
in Cartographica > vol 56 n° 1 (Spring 2021) . - pp 2 - 13[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 031-2021011 SL Revue Centre de documentation Revues en salle Disponible Models for integrating and identifying the effect of senescence on individual tree survival probability for Norway spruce / Jouni Siipilehto in Silva fennica, vol 55 n° 2 (April 2021)
PermalinkStreams 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])
PermalinkThe impact of drought stress on the height growth of young norway spruce full-sib and half-sib clonal trials in Sweden and Finland / Haleh Hayatgheibi in Forests, vol 12 n° 4 (April 2021)
PermalinkTree 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)
PermalinkAnalyse et consolidation des résultats sur les estimations de superficie du couvert forestier et de ses changements entre 2000 et 2016 en république du Congo / Suspense Averti Ifo in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)
PermalinkCartographie de l’occupation du sol du Gabon en 2015, changements entre 2010 et 2015 / Farrel Nzigou Boucka in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)
PermalinkDétection des zones de dégradation et de régénération de la couverture végétale dans le sud du Sénégal à travers l'analyse des tendances de séries temporelles MODIS NDVI et des changements d'occupation des sols à partir d'images LANDSAT / Boubacar Solly in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)
PermalinkApplication of thermal imaging and hyperspectral remote sensing for crop water deficit stress monitoring / Gopal Krishna in Geocarto international, vol 36 n° 5 ([15/03/2021])
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])
PermalinkEarly detection of forest stress from European spruce bark beetle attack, and a new vegetation index: Normalized distance red & SWIR (NDRS) / Langning Huo in Remote sensing of environment, Vol 255 (March 2021)
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