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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)
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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 pointsRésumé : (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
in Remote sensing > vol 14 n° 8 (April-2 2022) . - n° 1892[article]Estimating forest attributes in airborne laser scanning based inventory using calibrated predictions from external models / Ana de Lera Garrido in Silva fennica, vol 56 n° 2 (April 2022)
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Titre : Estimating forest attributes in airborne laser scanning based inventory using calibrated predictions from external models Type de document : Article/Communication Auteurs : Ana de Lera Garrido, Auteur ; Terje Gobakken, Auteur ; Hans Ole Ørka, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 10695 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] étalonnage
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle de simulation
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] Norvège
[Termes IGN] parcelle forestière
[Termes IGN] placette d'échantillonnage
[Termes IGN] semis de points
[Termes IGN] volume en boisRésumé : (auteur) Forest management inventories assisted by airborne laser scanner data rely on predictive models traditionally constructed and applied based on data from the same area of interest. However, forest attributes can also be predicted using models constructed with data external to where the model is applied, both temporal and geographically. When external models are used, many factors influence the predictions’ accuracy and may cause systematic errors. In this study, volume, stem number, and dominant height were estimated using external model predictions calibrated using a reduced number of up-to-date local field plots or using predictions from reparametrized models. We assessed and compared the performance of three different calibration approaches for both temporally and spatially external models. Each of the three approaches was applied with different numbers of calibration plots in a simulation, and the accuracy was assessed using independent validation data. The primary findings were that local calibration reduced the relative mean difference in 89% of the cases, and the relative root mean squared error in 56% of the cases. Differences between application of temporally or spatially external models were minor, and when the number of local plots was small, calibration approaches based on the observed prediction errors on the up-to-date local field plots were better than using the reparametrized models. The results showed that the estimates resulting from calibrating external models with 20 plots were at the same level of accuracy as those resulting from a new inventory. Numéro de notice : A2022-367 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14214/sf.10695 Date de publication en ligne : 25/04/2022 En ligne : https://doi.org/10.14214/sf.10695 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100589
in Silva fennica > vol 56 n° 2 (April 2022) . - n° 10695[article]A stand-level growth and yield model for thinned and unthinned even-aged Scots pine forests in Norway / Christian Kuehne in Silva fennica, vol 56 n° 1 (January 2022)
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Titre : A stand-level growth and yield model for thinned and unthinned even-aged Scots pine forests in Norway Type de document : Article/Communication Auteurs : Christian Kuehne, Auteur ; J. Paul McLean, Auteur ; Kobra Maleki, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] branche (arbre)
[Termes IGN] éclaircie (sylviculture)
[Termes IGN] forêt équienne
[Termes IGN] gestion forestière
[Termes IGN] hauteur des arbres
[Termes IGN] modèle de croissance végétale
[Termes IGN] Norvège
[Termes IGN] Pinus sylvestris
[Termes IGN] rendement
[Termes IGN] surface terrière
[Termes IGN] volume en bois
[Vedettes matières IGN] SylvicultureRésumé : (auteur) Management of Scots pine (Pinus sylvestris L.) in Norway requires a forest growth and yield model suitable for describing stand dynamics of even-aged forests under contemporary climatic conditions with and without the effects of silvicultural thinning. A system of equations forming such a stand-level growth and yield model fitted to long-term experimental data is presented here. The growth and yield model consists of component equations for (i) dominant height, (ii) stem density (number of stems per hectare), (iii) total basal area, (iv) and total stem volume fitted simultaneously using seemingly unrelated regression. The component equations for stem density, basal area, and volume include a thinning modifier to forecast stand dynamics in thinned stands. It was shown that thinning significantly increased basal area and volume growth while reducing competition related mortality. No significant effect of thinning was found on dominant height. Model examination by means of various fit statistics indicated no obvious bias and improvement in prediction accuracy in comparison to existing models in general. An application of the developed stand-level model comparing different management scenarios exhibited plausible long-term behavior and we propose this is therefore suitable for national deployment. Numéro de notice : A2022-171 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.14214/sf.10627 Date de publication en ligne : 26/01/2022 En ligne : https://doi.org/10.14214/sf.10627 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99806
in Silva fennica > vol 56 n° 1 (January 2022) . - n° 1[article]A user-centric optimization of emergency map symbols to facilitate common operational picture / Tomasz Opach in Cartography and Geographic Information Science, vol 49 n° 2 (February 2022)
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Titre : A user-centric optimization of emergency map symbols to facilitate common operational picture Type de document : Article/Communication Auteurs : Tomasz Opach, Auteur ; Jan Ketil Rød, Auteur Année de publication : 2022 Article en page(s) : pp 134 - 153 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rédaction cartographique
[Termes IGN] cartographie d'urgence
[Termes IGN] entretien d'enquête
[Termes IGN] Norvège
[Termes IGN] représentation cartographique
[Termes IGN] secours d'urgence
[Termes IGN] sémiologie graphique
[Termes IGN] symbole graphique
[Termes IGN] utilisateur
[Termes IGN] visualisation cartographiqueRésumé : (auteur) Common operational understanding among engaged emergency responders is facilitated through shared operational pictures during crisis situations. Sharing is typically achieved through interactive tools, either desktop or web-based, in which map displays play an essential role. That role can be further strengthened if (1) agreed emergency symbols that are used in map-based interactive tools are sufficient to encode multifaceted operational information visually; and (2) the symbols are legible and meaningful for the diverse users of those tools. The authors revisited official emergency map symbols in use in Norway and reconsidered them against current requirements. To this end, they first conducted several meetings with stakeholders to elicit adequate revision requirements. Next, the reconsideration included the extension of the symbol set, symbol modification, and grouping. After the reconsideration, emergency management officers and specialists were interviewed. The interviews confirmed the agreement with the symbol categorization, extension of the symbols, and their modifications. The interviewees also made numerous suggestions to be considered in a follow-up study. Moreover, two concepts – symbol standardization and symbol harmonization – were proposed. Numéro de notice : A2022-137 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2021.1994469 Date de publication en ligne : 13/12/2021 En ligne : https://doi.org/10.1080/15230406.2021.1994469 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99758
in Cartography and Geographic Information Science > vol 49 n° 2 (February 2022) . - pp 134 - 153[article]Above-ground biomass change estimation using national forest inventory data with Sentinel-2 and Landsat / Stefano Puliti in Remote sensing of environment, vol 265 (November 2021)
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Titre : Above-ground biomass change estimation using national forest inventory data with Sentinel-2 and Landsat Type de document : Article/Communication Auteurs : Stefano Puliti, Auteur ; Johannes Breidenbach, Auteur ; Johannes Schumacher, Auteur ; Marius Hauglin, Auteur ; T.F. Klingenberg, Auteur ; Rasmus Astrup, Auteur Année de publication : 2021 Article en page(s) : n° 112644 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] biomasse aérienne
[Termes IGN] estimation statistique
[Termes IGN] forêt boréale
[Termes IGN] image Landsat
[Termes IGN] image Sentinel-MSI
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Norvège
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] puits de carbone
[Termes IGN] surveillance forestièreRésumé : (auteur) This study aimed at estimating total forest above-ground net change (ΔAGB; Gg) over five years (2014–2019) based on model-assisted estimation utilizing freely available satellite imagery. The study was conducted for a boreal forest area (approx. 1.4 Mha) in Norway where bi-temporal national forest inventory (NFI), Sentinel-2, and Landsat data were available. Biomass change was modelled based on a direct approach. The precision of estimates using only the NFI data in a basic expansion estimator was compared to four different alternative model-assisted estimates using 1) Sentinel-2 or Landsat data, and 2) using bi- or uni-temporal remotely sensed data. We found that spaceborne optical data improved the precision of the purely field-based estimates by a factor of up to three. The most precise estimates were found for the model-assisted estimation using bi-temporal Sentinel-2 (standard error; SE = 1.7 Gg). However, the decrease in precision when using Landsat data was small (SE = 1.92 Gg). We also found that ΔAGB could be precisely estimated when remotely sensed data were available only at the end of the monitoring period. We conclude that satellite optical data can considerably improve ΔAGB estimates, when repeated and coincident field data are available. The free availability, global coverage, frequent update, and long-term time horizon make data from programs such as Sentinel-2 and Landsat a valuable data source for consistent and durable monitoring of forest carbon dynamics. Numéro de notice : A2021-938 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112644 Date de publication en ligne : 25/08/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112644 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99746
in Remote sensing of environment > vol 265 (November 2021) . - n° 112644[article]Quantifying historical landscape change with repeat photography: an accuracy assessment of geospatial data obtained through monoplotting / Ulrike Bayr in International journal of geographical information science IJGIS, vol 35 n° 10 (October 2021)
PermalinkLarge-area inventory of species composition using airborne laser scanning and hyperspectral data / Hans Ole Ørka in Silva fennica, vol 55 n° 4 (September 2021)
PermalinkModels 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)
PermalinkA compilation of snow cover datasets for Svalbard: A multi-sensor, multi-model study / Hannah Vickers in Remote sensing, vol 13 n°10 (May-2 2021)
PermalinkMapping seasonal agricultural land use types using deep learning on Sentinel-2 image time series / Misganu Debella-Gilo in Remote sensing, Vol 13 n° 2 (January-2 2021)
PermalinkStand-level mortality models for Nordic boreal forests / Jouni Siipilehto in Silva fennica, vol 54 n° 5 (December 2020)
PermalinkCadastral development in Norway: the need for improvement / Leiv Bjarte Mjøs in Survey review, vol 52 n° 375 (November 2020)
PermalinkIncreasing Cervidae populations have variable impacts on habitat suitability for threatened forest plant and lichen species / James D.M. Speed in Forest ecology and management, vol 473 ([01/10/2020])
PermalinkA century of National Forest Inventory in Norway – informing past, present, and future decisions / Johannes Breidenbach in Forest ecosystems, vol 7 (2020)
PermalinkMapping forest age using National Forest Inventory, airborne laser scanning, and Sentinel-2 data / Johannes Schumacher in Forest ecosystems, vol 7 (2020)
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