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Tree species classification using within crown localization of waveform LiDAR attributes / Rosmarie Blomley in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)
[article]
Titre : Tree species classification using within crown localization of waveform LiDAR attributes Type de document : Article/Communication Auteurs : Rosmarie Blomley, Auteur ; Aarne Hovi, Auteur ; Martin Weinmann, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 142 - 156 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse multiéchelle
[Termes IGN] Betula pendula
[Termes IGN] betula pubescens
[Termes IGN] croissance des arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] espèce végétale
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] forêt boréale
[Termes IGN] Norvège
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] rotation d'objetRésumé : (Auteur) Since forest planning is increasingly taking an ecological, diversity-oriented perspective into account, remote sensing technologies are becoming ever more important in assessing existing resources with reduced manual effort. While the light detection and ranging (LiDAR) technology provides a good basis for predictions of tree height and biomass, tree species identification based on this type of data is particularly challenging in structurally heterogeneous forests. In this paper, we analyse existing approaches with respect to the geometrical scale of feature extraction (whole tree, within crown partitions or within laser footprint) and conclude that currently features are always extracted separately from the different scales. Since multi-scale approaches however have proven successful in other applications, we aim to utilize the within-tree-crown distribution of within-footprint signal characteristics as additional features. To do so, a spin image algorithm, originally devised for the extraction of 3D surface features in object recognition, is adapted. This algorithm relies on spinning an image plane around a defined axis, e.g. the tree stem, collecting the number of LiDAR returns or mean values of returns attributes per pixel as respective values. Based on this representation, spin image features are extracted that comprise only those components of highest variability among a given set of library trees. The relative performance and the combined improvement of these spin image features with respect to non-spatial statistical metrics of the waveform (WF) attributes are evaluated for the tree species classification of Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.) and Silver/Downy birch (Betula pendula Roth/Betula pubescens Ehrh.) in a boreal forest environment. This evaluation is performed for two WF LiDAR datasets that differ in footprint size, pulse density at ground, laser wavelength and pulse width. Furthermore, we evaluate the robustness of the proposed method with respect to internal parameters and tree size. The results reveal, that the consideration of the crown-internal distribution of within-footprint signal characteristics captured in spin image features improves the classification results in nearly all test cases Numéro de notice : A2017-724 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.08.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.08.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88409
in ISPRS Journal of photogrammetry and remote sensing > vol 133 (November 2017) . - pp 142 - 156[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017111 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017112 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017113 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt Adaptive and plastic responses of Quercus petraea populations to climate across Europe / Cuauhtémoc Saenz-Romero in Global change biology, vol 23 n° 7 (July 2017)
[article]
Titre : Adaptive and plastic responses of Quercus petraea populations to climate across Europe Type de document : Article/Communication Auteurs : Cuauhtémoc Saenz-Romero, Auteur ; Jean-Baptiste Lamy, Auteur ; Alexis Ducousso, Auteur ; Brigitte Musch, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 2831 - 2847 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] changement climatique
[Termes IGN] Danemark
[Termes IGN] forêt tempérée
[Termes IGN] France (administrative)
[Termes IGN] Hongrie
[Termes IGN] modèle de simulation
[Termes IGN] Norvège
[Termes IGN] Quercus sessiliflora
[Termes IGN] Turquie
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) How temperate forests will respond to climate change is uncertain; projections range from severe decline to increased growth. We conducted field tests of sessile oak (Quercus petraea), a widespread keystone European forest tree species, including more than 150 000 trees sourced from 116 geographically diverse populations. The tests were planted on 23 field sites in six European countries, in order to expose them to a wide range of climates, including sites reflecting future warmer and drier climates. By assessing tree height and survival, our objectives were twofold: (i) to identify the source of differential population responses to climate (genetic differentiation due to past divergent climatic selection vs. plastic responses to ongoing climate change) and (ii) to explore which climatic variables (temperature or precipitation) trigger the population responses. Tree growth and survival were modeled for contemporary climate and then projected using data from four regional climate models for years 2071–2100, using two greenhouse gas concentration trajectory scenarios each. Overall, results indicated a moderate response of tree height and survival to climate variation, with changes in dryness (either annual or during the growing season) explaining the major part of the response. While, on average, populations exhibited local adaptation, there was significant clinal population differentiation for height growth with winter temperature at the site of origin. The most moderate climate model (HIRHAM5-EC; rcp4.5) predicted minor decreases in height and survival, while the most extreme model (CCLM4-GEM2-ES; rcp8.5) predicted large decreases in survival and growth for southern and southeastern edge populations (Hungary and Turkey). Other nonmarginal populations with continental climates were predicted to be severely and negatively affected (Bercé, France), while populations at the contemporary northern limit (colder and humid maritime regions; Denmark and Norway) will probably not show large changes in growth and survival in response to climate change. Numéro de notice : A2017-676 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1111/gcb.13576 En ligne : http://doi.org/10.1111/gcb.13576 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87202
in Global change biology > vol 23 n° 7 (July 2017) . - pp 2831 - 2847[article]The influence of spatial scales on Red List composition: Forest species in Fennoscandia / Lise Tingstad in Global ecology and conservation, vol 11 (July 2017)
[article]
Titre : The influence of spatial scales on Red List composition: Forest species in Fennoscandia Type de document : Article/Communication Auteurs : Lise Tingstad, Auteur ; I. Gjerde, Auteur ; A. Dahlberg, Auteur ; J.A. Grytnes, Auteur Année de publication : 2017 Article en page(s) : pp 247 - 297 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation
[Termes IGN] aire de répartition
[Termes IGN] Fennoscandie
[Termes IGN] Finlande
[Termes IGN] forêt
[Termes IGN] Norvège
[Termes IGN] politique de conservation (biodiversité)
[Termes IGN] Suède
[Termes IGN] variation d'échelleRésumé : (auteur) National Red Lists are widely used prioritizing tools for nature conservation. However, status and trends of species vary with scale, and accounting for a larger spatial scale may provide complementary perspectives for nature conservation. We investigate effects of up-scaling and influence of wider-scale distribution patterns for composition of Red Lists.
We collated nationally red-listed forest species in Norway, Sweden and Finland, and extracted “Candidates for a Fennoscandian Red List” (CFRL), defined as species red-listed where they appear in the region. For each country, we compared composition of organism groups and forest type associations of species that were national CFRL to the nationally red-listed species not CFRL. European distribution patterns were compared to investigate how broader-scale distribution is reflected in national Red Lists.
Among the 4830 nationally red-listed forest species in Fennoscandia, 58% were CFRL. The fraction of species in the different forest type and species groups differed significantly between the two spatial scales for several groups, although the overall differences in composition were relatively small. Red-listed species had more confined distribution patterns, suggesting that many nationally red-listed species owe their status to being at the edge of their distribution range.
An up-scaling had a large effect on which species designated to a Red List, but a relatively small impact on which organism groups or forest types that contained most red-listed species. A regional perspective generated by compilation of national Red Lists can give valuable complementary information on the status of species and effects of scale.Numéro de notice : A2017-613 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.1016/j.gecco.2017.07.005 En ligne : https://doi.org/10.1016/j.gecco.2017.07.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86922
in Global ecology and conservation > vol 11 (July 2017) . - pp 247 - 297[article]Development of a sampling protocol for monitoring snow melt using photogrammetry / Guillaume Sutter (2017)
Titre : Development of a sampling protocol for monitoring snow melt using photogrammetry Type de document : Mémoire Auteurs : Guillaume Sutter, Auteur Editeur : Champs-sur-Marne : Ecole nationale des sciences géographiques ENSG Année de publication : 2017 Importance : 55 p. Note générale : Bibliographie
Rapport de projet pluridisciplinaire, cycle Ingénieur 2e annéeLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] acquisition d'images
[Termes IGN] analyse comparative
[Termes IGN] bassin hydrographique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] données spatiotemporelles
[Termes IGN] eau de fonte
[Termes IGN] lever topographique
[Termes IGN] manteau neigeux
[Termes IGN] modèle 3D du site
[Termes IGN] Norvège
[Termes IGN] précision des données
[Termes IGN] télémétrie laser terrestreIndex. décimale : PROJET Mémoires : Rapports de projet - stage des ingénieurs de 2e année Résumé : (Auteur) Dans un contexte de changement climatique, l’importance et la durée de la couverture neigeuse saisonnière dans les régions dominées par la neige, comme par exemple la Norvège, vont avoir des conséquences socio-économiques importantes. Le but du projet ESCYMO est de développer des outils de modélisation et des compétences terrain dans le domaine de l’hydrologie de la neige dans le but d’avoir une meilleure compréhension de ce mécanisme changeant. Dans le cadre de ce projet, mon rôle a tout d’abord été d’étudier la possibilité d’extraire un modèle 3D de la surface de la neige en utilisant la photogrammétrie, ensuite d’en déterminer un processus optimal et finalement trouver les sources d’erreurs du modèle afin d’améliorer le processus. Afin de répondre à ces questions, mon stage s’est divisé en deux périodes. La première période était un mois de travail terrain où nous avons collecté beaucoup de données à Finse, Norvège. Nous avons fait des acquisitions d’images, de GPS et de LIDAR et avons installé des appareils photos timelapse dans deux bassins-versants. La seconde période a pris place à l’Université d’Oslo où j’ai traité les données et créé les meilleurs modèles 3D à partir des images acquises. Le but du traitement est d’évaluer la précision d’un modèle photogrammétrique en le comparant à des modèles précis tels que les traces GPS ou les nuages LIDAR. Quand la précision d’un modèle a été évaluée, la seconde étape était de comparer différents modèles à différentes dates dans le but d’évaluer la vitesse de fonte de la neige ainsi que la profondeur de neige dans chacun des bassins-versants. Note de contenu :
INTRODUCTION
1. INTERNSHIP DESCRIPTION
1.1 General Description
1.2 Field work
2. DATA COLLECTION AND DATA PROCESSING
2.1 GPS
2.2 LIDAR
2.3 Photogrammetry
3. ANALYSIS AND INTERPRETATION
3.1 Analysis of a single model
3.2 Evolution of the precision with different parameters
3.3 Temporal dimension and comparison between models
4. CONTENTS
CONCLUSIONNuméro de notice : 22842 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Mémoire de projet pluridisciplinaire Organisme de stage : Université d'Oslo Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89086 Réservation
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Development of a sampling protocolAdobe Acrobat PDF The effects of temporal differences between map and ground data on map-assisted estimates of forest area and biomass / Ronald E. McRoberts in Annals of Forest Science, vol 73 n° 4 (December 2016)
[article]
Titre : The effects of temporal differences between map and ground data on map-assisted estimates of forest area and biomass Type de document : Article/Communication Auteurs : Ronald E. McRoberts, Auteur ; Erik Naesset, Auteur ; Terje Gobakken, Auteur Année de publication : 2016 Article en page(s) : pp 839 - 847 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] biomasse
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] estimation statistique
[Termes IGN] forêt
[Termes IGN] image Landsat
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Minnesota (Etats-Unis)
[Termes IGN] Norvège
[Termes IGN] régression
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Key message : When areas of interest experience little change, remote sensing-based maps whose dates deviate from ground data can still substantially enhance precision. However, when change is substantial, deviations in dates reduce the utility of such maps for this purpose.
Context : Remote sensing-based maps are well-established as means of increasing the precision of estimates of forest inventory parameters. The general practice is to use maps whose dates correspond closely to the dates of ground data. However, as national forest inventories move to continuous inventories, deviations between map and ground data dates increase.
Aims : The aim was to assess the degree to which remote sensing-based maps can be used to increase the precision of estimates despite differences between map and ground data dates.
Methods : For study areas in the USA and Norway, maps were constructed for each of two dates, and model-assisted regression estimators were used to estimate inventory parameters using ground data whose dates differed by as much as 11 years from the map dates.
Results : For the Minnesota study area that had little change, 7-year differences in dates had little effect on the precision of estimates of proportion forest area. For the Norwegian study area that experienced considerable change, 11-year differences in dates had a detrimental effect on the precision of estimates of mean biomass per unit area.
Conclusions : The effects of differences in map and ground data dates were less important than temporal change in the study area.Numéro de notice : A2016--168 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-015-0485-6 Date de publication en ligne : 12/05/2015 En ligne : https://doi.org/10.1007/s13595-015-0485-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87210
in Annals of Forest Science > vol 73 n° 4 (December 2016) . - pp 839 - 847[article]A method for automated snow avalanche debris detection through use of synthetic aperture radar (SAR) imaging / Hannah Vickers in Earth and space science, vol 3 n° 11 (November 2016)PermalinkA functional regression model for inventories supported by aerial laser scanner data or photogrammetric point clouds / Magnussen, Steen in Remote sensing of environment, vol 184 (October 2016)PermalinkLong-term vegetation dynamics and land-use history: Providing a baseline for conservation strategies in protected Alnus glutinosa swamp woodlands / Brith Natlandsmyr in Forest ecology and management, vol 372 (15 July 2016)PermalinkNew 3D Map Solution Covering Norway / Kenneth Øyen-Eriksen in GIM international [en ligne], vol 30 n° 6 (June 2016)PermalinkTree species identity mediates mechanisms of top soil carbon sequestration in a Norway spruce and European beech mixed forest / Enrique Andivia in Annals of Forest Science, vol 73 n° 2 (June 2016)PermalinkPermalinkLes grands arcs de méridien du XIXème [dix-neuvième] siècle et la forme de la Terre / James Lequeux in XYZ, n° 145 (décembre 2015 - février 2016)PermalinkTemporal stability of X-band single-pass InSAR heights in a spruce forest: effects of acquisition properties and season / Svein Solberg in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkAssessing forest inventory information obtained from different inventory approaches and remote sensing data sources / Even Bergseng in Annals of Forest Science, vol 72 n° 1 (January 2015)PermalinkEstimating forest biomass from TerraSAR-X stripmap radargrammetry / Svein Solberg in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)Permalink