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Wood decay detection in Norway spruce forests based on airborne hyperspectral and ALS data / Michele Dalponte in Remote sensing, vol 14 n° 8 (April-2 2022)  

Public [article]  inRemote sensing > vol 14 n° 8 (April-2 2022) . - n° 1892 Titre : Wood decay detection in Norway spruce forests based on airborne hyperspectral and ALS data Type de document : Article/Communication Auteurs : Michele Dalponte, Auteur ; Alvar J. I. Kallio, Auteur ; Hans Ole Ørka, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1892 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] bois sur pied [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] dépérissement [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] données lidar [Termes IGN] image hyperspectrale [Termes IGN] image infrarouge [Termes IGN] Norvège [Termes IGN] Perceptron multicouche [Termes IGN] Picea abies [Termes IGN] régression linéaire [Termes IGN] régression logistique [Termes IGN] santé des forêts [Termes IGN] semis de points Résumé : (auteur) Wood decay caused by pathogenic fungi in Norway spruce forests causes severe economic losses in the forestry sector, and currently no efficient methods exist to detect infected trees. The detection of wood decay could potentially lead to improvements in forest management and could help in reducing economic losses. In this study, airborne hyperspectral data were used to detect the presence of wood decay in the trees in two forest areas located in Etnedal (dataset I) and Gran (dataset II) municipalities, in southern Norway. The hyperspectral data used consisted of images acquired by two sensors operating in the VNIR and SWIR parts of the spectrum. Corresponding ground reference data were collected in Etnedal using a cut-to-length harvester while in Gran, field measurements were collected manually. Airborne laser scanning (ALS) data were used to detect the individual tree crowns (ITCs) in both sites. Different approaches to deal with pixels inside each ITC were considered: in particular, pixels were either aggregated to a unique value per ITC (i.e., mean, weighted mean, median, centermost pixel) or analyzed in an unaggregated way. Multiple classification methods were explored to predict rot presence: logistic regression, feed forward neural networks, and convolutional neural networks. The results showed that wood decay could be detected, even if with accuracy varying among the two datasets. The best results on the Etnedal dataset were obtained using a convolution neural network with the first five components of a principal component analysis as input (OA = 65.5%), while on the Gran dataset, the best result was obtained using LASSO with logistic regression and data aggregated using the weighted mean (OA = 61.4%). In general, the differences among aggregated and unaggregated data were small. Numéro de notice : A2022-352 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.3390/rs14081892 Date de publication en ligne : 14/04/2022 En ligne : https://doi.org/10.3390/rs14081892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100541 [article]

Biodiversity value and the optimal location of forest conservation sites in Southern Finland / Alvar J. I. Kallio in Ecological economics, vol 67 n° 2 (15 September 2008)  

Public [article]  inEcological economics > vol 67 n° 2 (15 September 2008) . - PP 232 - 243 Titre : Biodiversity value and the optimal location of forest conservation sites in Southern Finland Type de document : Article/Communication Auteurs : Alvar J. I. Kallio, Auteur ; I. Maarit, Auteur ; Ritta Hänninen, Auteur ; Nina Vainikainen, Auteur ; Sandra Luque, Auteur Année de publication : 2008 Article en page(s) : PP 232 - 243 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] allocation [Termes IGN] Finlande [Termes IGN] forêt [Termes IGN] habitat forestier [Termes IGN] indicateur de gestion forestière durable [Termes IGN] milieu naturel [Termes IGN] protection de la biodiversité [Vedettes matières IGN] Ecologie forestière Résumé : (Auteur) Safeguarding biodiversity has been one of the most important issues in environmental and forest policies since the 1990s. In Southern Finland, decisions concerning further actions for the preservation of forest biodiversity will be made in the coming years. To support policy making, we present a multi-regional model that is applicable in determining the economically optimal regional allocation of conservation sites. Three habitat quality models are evaluated to calculate habitat quality indices used as a surrogate for a biodiversity value in a forest sector model. The scenarios presented provide information about the economic impacts of conservation choices on the forest sector. The overall economic impacts of conservation depend on its scale and regional allocation. Conserving land with high biodiversity value can have less adverse impact on the forest sector than conservation of typical commercial forest sites. When optimizing conservation set-asides, we found that set-asides targeted to certain regions possessing higher/lower than average relative share of ecologically valuable land, caused lower/higher adverse economic impacts on the forest sector. Because it is expensive to search land suitable for conservation, these regions could be respectively favoured/avoided when asking forest owners to offer their land for the new conservation program in Southern Finland, which will be based on voluntariness. Numéro de notice : A2008-585 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.ecolecon.2008.05.005 En ligne : https://doi.org/10.1016/j.ecolecon.2008.05.005 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79823 [article]