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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 IGN] arbre urbain [Termes IGN] dommage matériel [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] peuplement forestier [Termes IGN] tempête [Termes IGN] Toscane (Italie) [Termes 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 Affiliation des auteurs : non IGN 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]

A meta-analysis and review of the literature on the k-Nearest Neighbors technique for forestry applications that use remotely sensed data / Gherardo Chirici in Remote sensing of environment, vol 176 (April 2016)  

Public [article]  inRemote sensing of environment > vol 176 (April 2016) . - pp 282 - 294 Titre : A meta-analysis and review of the literature on the k-Nearest Neighbors technique for forestry applications that use remotely sensed data Type de document : Article/Communication Auteurs : Gherardo Chirici, Auteur ; Matteo Mura, Auteur ; Daniel McInerney, Auteur ; Nicolas Py , Auteur ; Erkki Tomppo, Auteur ; Lars T. Waser, Auteur ; Davide Travaglini, Auteur ; Ronald E. McRoberts, Auteur Année de publication : 2016 Article en page(s) : pp 282 - 294 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] classification barycentrique [Termes IGN] forêt [Termes IGN] image aérienne [Termes IGN] image satellite [Termes IGN] plus proche voisin, algorithme du Résumé : (auteur) The k-Nearest Neighbors (k-NN) technique is a popular method for producing spatially contiguous predictions of forest attributes by combining field and remotely sensed data. In the framework of Working Group 2 of COST Action FP1001, we reviewed the scientific literature for forestry applications of k-NN. Information available in scientific publications on this topic was used to populate a database that was then used as the basis for a meta-analysis. We extracted qualitative and quantitative information from 260 experimental tests described in 148 scientific papers. The papers represented a geographic range of 26 countries and a temporal range from 1981 to 2013. Firstly, we describe the literature search and the information extracted and analyzed. Secondly, we report the results of the meta-analysis, especially with respect to estimation accuracies reported for k-NN applications for different configurations, different forest environments, and different input information. We also provide a summary of results that may reasonably be expected for those planning a k-NN application using remotely sensed data from different sensors and for different forest attributes. Finally, we identify some methodological publications that have advanced the state of the science with respect to k-NN. Numéro de notice : A2016--196 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2016.02.001 Date de publication en ligne : 13/02/2016 En ligne : https://doi.org/10.1016/j.rse.2016.02.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91859 [article]