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European Forest Types: toward an automated classification / Francesca Giannetti in Annals of Forest Science [en ligne], vol 75 n° 1 (March 2018)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 75 n° 1 (March 2018) Titre : European Forest Types: toward an automated classification Type de document : Article/Communication Auteurs : Francesca Giannetti, Auteur ; Anna Barbati, Auteur ; Leone Davide Mancini, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] algorithme de comparaison [Termes descripteurs IGN] base de règles [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] classification pixellaire [Termes descripteurs IGN] Europe (géographie physique) [Termes descripteurs IGN] Fagus (genre) [Termes descripteurs IGN] milieu naturel [Termes descripteurs IGN] système d'information forestier [Termes descripteurs IGN] système d'information géographique [Termes descripteurs IGN] système expert [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) Key message: The outcome of the present study leads to the application of a spatially explicit rule-based expert system (RBES) algorithm aimed at automatically classifying forest areas according to the European Forest Types (EFT) system of nomenclature at pan-European scale level. With the RBES, the EFT system of nomenclature can be now easily implemented for objective, replicable, and automatic classification of field plots for forest inventories or spatial units (pixels or polygons) for thematic mapping. Context: Forest Types classification systems are aimed at stratifying forest habitats. Since 2006, a common scheme for classifying European forests into 14 categories and 78 types (European Forest Types, EFT) exists. Aims: This work presents an innovative method and automated classification system that, in an objective and replicable way, can accurately classify a given forest habitat according to the EFT system of nomenclature. Methods: A rule-based expert system (RBES) was adopted as a transparent approach after comparison with the well-known Random Forest (RF) classification system. The experiment was carried out based on the information acquired in the field in 2010 ICP level I plots in 17 European countries. The accuracy of the automated classification is evaluated by comparison with an independent classification of the ICP plots into EFT carried out during the BioSoil project field survey. Finally, the RBES automated classifier was tested also for a pixel-based classification of a pan-European distribution map of beech-dominated forests. Results: The RBES successfully classified 94% of the plots, against a 92% obtained with RF. When applied to the mapped domain, the accuracy obtained with the RBES for the beech forest map classification was equal to 95%. Conclusion: The RBES algorithm successfully automatically classified field plots and map pixels on the basis of the EFT system of nomenclature. The EFT system of nomenclature can be now easily and objectively implemented in operative transnational European forest monitoring programs. Numéro de notice : A2018-318 Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-017-0674-6 date de publication en ligne : 03/01/2018 En ligne : https://doi.org/10.1007/s13595-017-0674-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90450 [article]

Assessing forest windthrow damage using single-date, post-event airborne laser scanning data / Gherardo Chirici in Forestry, an international journal of forest research, vol 91 n° 1 (January 2018)  

Public [article]  inForestry, an international journal of forest research > vol 91 n° 1 (January 2018) . - pp 27 - 37 Titre : Assessing forest windthrow damage using single-date, post-event airborne laser scanning data Type de document : Article/Communication Auteurs : Gherardo Chirici, Auteur ; Francesca Bottalico, Auteur ; Francesca Giannetti, Auteur ; Barbara Del Perugia, Auteur ; Davide Travaglini, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 27 - 37 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] arbre urbain [Termes descripteurs IGN] dommage matériel [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] peuplement forestier [Termes descripteurs IGN] tempête [Termes descripteurs IGN] Toscane (Italie) [Termes descripteurs IGN] zone urbaine Résumé : (Auteur) One of many possible climate change effects in temperate areas is the increase of frequency and severity of windstorms; thus, fast and cost efficient new methods are needed to evaluate wind-induced damages in forests. We present a method for assessing windstorm damages in forest landscapes based on a two-stage sampling strategy using single-date, post-event airborne laser scanning (ALS) data. ALS data are used for delineating damaged forest stands and for an initial evaluation of the volume of fallen trees. The total volume of fallen trees is then estimated using a two-stage model-assisted approach, where variables from ALS are used as auxiliary information in the difference estimator. In the first stage, a sample of the delineated forest stands is selected, and in the second stage the within-stand damages are estimated by means of line intercept sampling (LIS). The proposed method produces maps of windthrown areas, estimates of forest damages in terms of the total volume of fallen trees, and the uncertainty of the estimates. A case study is presented for a large windstorm that struck the Tuscany Region of Italy the night of the 4th and the 5th of March 2015 and caused extensive damages to trees in both forest and urban areas. The pure field-based estimates from LIS and the ALS-based estimates of stand-level fallen wood were very similar. Our positive results demonstrate the utility of the single-date approach for a fast assessment of windthrow damages in forest stands which is especially useful when pre-event ALS data are not available. Numéro de notice : A2018-630 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx029 date de publication en ligne : 06/07/2017 En ligne : https://doi.org/10.1093/forestry/cpx029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93215 [article]