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Weak relationships of continuous forest management intensity and remotely sensed stand structural complexity in temperate mountain forests / Thomas Asbeck in European Journal of Forest Research, vol 140 n° 3 (June 2021)  

Public [article]  inEuropean Journal of Forest Research > vol 140 n° 3 (June 2021) . - pp 721 - 731 Titre : Weak relationships of continuous forest management intensity and remotely sensed stand structural complexity in temperate mountain forests Type de document : Article/Communication Auteurs : Thomas Asbeck, Auteur ; Julian Frey, Auteur Année de publication : 2021 Article en page(s) : pp 721 - 731 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Abies alba [Termes IGN] composition d'un peuplement forestier [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Forêt-Noire, massif de la [Termes IGN] gestion forestière durable [Termes IGN] modélisation de la forêt [Termes IGN] Picea abies [Termes IGN] semis de points [Termes IGN] structure d'un peuplement forestier Résumé : (auteur) Understanding the relationship of stand structural complexity and forest management is relevant to create desired stand structures by adapting management strategies under changing disturbance scenarios and climatic conditions. To overcome difficulties in differentiating between strict categories of silvicultural practices and to describe the impact of forest management more appropriate, we used a continuous indicator of forest management intensity (ForMI). The ForMI consists of three components including volumes of natural deadwood, non-native tree species and harvested trees. There are a great number of approaches to quantify stand structure; here we used the recently established stand structural complexity index (SSCI) which represents a density-dependent as well as vertical measure of complexity based on the distribution of points in 3D space inventoried by terrestrial laser scanning. The data collection took place in 135 one-hectare plots managed under close-to-nature forest management (CTNFM) located in the Black Forest, Germany. We build generalized additive models to test the relationship of the SSCI with the ForMI. The model results did not prove a significant relationship between the SSCI and the ForMI, but components of the ForMI showed significant relationships to the SSCI. Our results indicate that the relationship between stand structural complexity and forest management intensity is, while plausible, not trivial to demonstrate. We conclude that forest managers have a relatively wide range of choices in CTNFM to adapt forests within a similar range of management intensity as presented here to future challenges, since management intensity does not change the forest structure drastically. Numéro de notice : A2021-431 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s10342-021-01361-4 Date de publication en ligne : 13/02/2021 En ligne : https://doi.org/10.1007/s10342-021-01361-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97793 [article]

Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks / Felix Schiefer in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 170 (December 2020) . - pp 205-215 Titre : Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks Type de document : Article/Communication Auteurs : Felix Schiefer, Auteur ; Teja Kattenborn, Auteur ; Annett Frick, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 205-215 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage profond [Termes IGN] arbre (flore) [Termes IGN] carte forestière [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] espèce végétale [Termes IGN] Forêt-Noire, massif de la [Termes IGN] image à haute résolution [Termes IGN] image captée par drone [Termes IGN] image RVB [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] inventaire forestier local [Termes IGN] segmentation sémantique [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) The use of unmanned aerial vehicles (UAVs) in vegetation remote sensing allows a time-flexible and cost-effective acquisition of very high-resolution imagery. Still, current methods for the mapping of forest tree species do not exploit the respective, rich spatial information. Here, we assessed the potential of convolutional neural networks (CNNs) and very high-resolution RGB imagery from UAVs for the mapping of tree species in temperate forests. We used multicopter UAVs to obtain very high-resolution ( Numéro de notice : A2020-706 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.015 Date de publication en ligne : 03/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.015 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96236 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2020121	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Modeling soil erosion after mechanized logging operations on steep terrain in the Northern Black Forest, Germany / Julian Haas in European Journal of Forest Research, vol 139 n°4 (August 2020)  

Public [article]  inEuropean Journal of Forest Research > vol 139 n°4 (August 2020) . - pp 549 – 565 Titre : Modeling soil erosion after mechanized logging operations on steep terrain in the Northern Black Forest, Germany Type de document : Article/Communication Auteurs : Julian Haas, Auteur ; Helmer Schack-Kirchner, Auteur ; Friederike Lang, Auteur Année de publication : 2020 Article en page(s) : pp 549 – 565 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] érosion [Termes IGN] exploitation forestière [Termes IGN] foresterie [Termes IGN] Forêt-Noire, massif de la [Termes IGN] pente [Termes IGN] ruissellement [Termes IGN] sédiment [Vedettes matières IGN] Sylviculture Résumé : (auteur) Climate change makes it necessary to re-evaluate the erosion potential of forest infrastructure. We used the Forest Service WEPP interfaces (FS WEPP) to compare soil erosion potentials of two competing logging practices in steep terrain in the Northern Black Forest, Germany: (1) Felling with harvesters and logging with forwarders in slope line with optional traction supporting winches. (2) Felling by chainsaw, logging with a cable winch, and further transport of logs via forest dirt roads. After forest harvest we measured erosion, runoff, and DOC concentration in runoff from 50 m sections of two machine tracks, two cable tracks, and a dirt road for 2 years. The erosion measurements were used to validate FS WEPP management options and a regionally adjusted CLIGEN input file. With these parameterizations we compared the erosion potential of the two practices on subcatchment scale by modeling return periods and total sediment export with FS WEPP. Model results show that logging operations with heavy machinery in slope line are less prone to soil erosion than logging operations including winch logging and additional dirt roads. The former produces less sediment in its worst-case configuration than the latter in its most moderate configuration by a factor of two. Model results also show that erosion prevention benefits from long periods of 10 years between two harvests. Numéro de notice : A2020-426 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10342-020-01269-5 Date de publication en ligne : 11/03/2020 En ligne : https://doi.org/10.1007/s10342-020-01269-5 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95491 [article]