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Digital aerial photogrammetry can efficiently support large-area forest inventories in Norway / Lars Johannes in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)
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Titre : Digital aerial photogrammetry can efficiently support large-area forest inventories in Norway Type de document : Article/Communication Auteurs : Lars Johannes, Auteur ; Johannes Breidenbach, Auteur ; Svein Solberg, Auteur ; Erik Naesset, Auteur ; Rasmus Astrup, Auteur Année de publication : 2017 Article en page(s) : pp 710 - 718 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] biomasse forestière
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Norvège
[Termes IGN] photogrammétrie aérienne
[Termes IGN] semis de points
[Termes IGN] surface terrière
[Termes IGN] volume en boisRésumé : (Auteur) The use of digital aerial photogrammetry (DAP) for forest inventory purposes has been widely studied and can produce comparable accuracy compared with airborne laser scanning (ALS) in small, homogeneous areas. However, the accuracy of DAP for large scale applications with heterogeneous terrain and forest vegetation has not yet been reported. In this study we examined the accuracy of timber volume, biomass and basal area prediction models based on DAP and national forest inventory (NFI) data on a large area in central Norway. Two separate point clouds were derived from aerial image acquisitions of 2010 and 2013. Vegetation heights were extracted by subtracting terrain elevation derived from ALS. A large number of NFI sample plots (483) measured between 2010 and 2014 were used as reference data to fit linear models for timber volume, biomass and basal area with height metrics derived from the DAP data as explanatory variables. Variables describing the heterogeneous environmental and image acquisition conditions were calculated and their influence on the model accuracy was tested. The results showed that forest parameter prediction using DAP works well when applied to a large area. The model fits of the timber volume, biomass and basal area models were good with R2 of 0.80, 0.81, 0.81 and RMSEs of 41.43 m3 ha−1 (55% of the mean observed value), 32.49 t ha−1 (47%), 5.19 m2 ha−1 (41%), respectively. Only a small proportion of the variation could be attributed to the heterogeneous conditions. The inclusion of the relative sun inclination led to an improvement of the model RMSEs by 2% of the mean observed values. The relatively low cost and stability across large areas make DAP an attractive source of auxiliary information for large scale forest inventories. Numéro de notice : A2017-905 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx027 En ligne : https://doi.org/10.1093/forestry/cpx027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93207
in Forestry, an international journal of forest research > vol 90 n° 5 (December 2017) . - pp 710 - 718[article]Effect of occupation time on the horizontal accuracy of a mapping-grade GNSS receiver under dense forest canopy / Robert J. McGaughey in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 12 (December 2017)
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Titre : Effect of occupation time on the horizontal accuracy of a mapping-grade GNSS receiver under dense forest canopy Type de document : Article/Communication Auteurs : Robert J. McGaughey, Auteur ; Kamal Ahmed, Auteur ; Hans-Erik Andersen, Auteur ; Stephen E. Reutebuch, Auteur Année de publication : 2017 Article en page(s) : PP 861 - 868 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] densité de la végétation
[Termes IGN] Etats-Unis
[Termes IGN] forêt
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] lever topographique
[Termes IGN] récepteur bifréquence
[Termes IGN] récepteur GPS
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) A mapping-grade dual frequency GNSS receiver was tested under dense forest canopy to determine the effect of occupation time on horizontal accuracy. The U.S. Forest Service Forest Inventory and Analysis unit in the Pacific Northwest has been using 32 of these units to collect over 7,000 plot locations since 2013. In this study, one-hour GNSS static occupations were collected at 33 ground-surveyed positions with Trimble GeoXH6000 mapping-grade and Javad Triumph1 survey-grade receivers. Rover files were differentially post-processed and horizontal accuracy of each post-processed position was computed. Results indicated that 1.85 m accuracy (n = 990) could be achieved with the GeoXH6000 receiver with 15-minute occupations; however, maximum horizontal error was 7.01 m. Increasing occupation time to 20 minutes did not result in a significant improvement in accuracy. No correlation was found between the horizontal precision of a post-processed position reported by the postprocessing software and the field-measured horizontal accuracy of the positions. Numéro de notice : A2017-805 Affiliation des auteurs : non IGN Thématique : FORET/POSITIONNEMENT Nature : Article DOI : 10.14358/PERS.83.12.861 En ligne : https://doi.org/10.14358/PERS.83.12.861 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89166
in Photogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 12 (December 2017) . - PP 861 - 868[article]Estimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications? / Fabian E. Fassnacht in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)
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Titre : Estimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications? Type de document : Article/Communication Auteurs : Fabian E. Fassnacht, Auteur ; Daniel Mangold, Auteur ; Jannika Schäfer, Auteur ; Markus Immitzer, Auteur Année de publication : 2017 Article en page(s) : pp 613 - 631 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] biomasse forestière
[Termes IGN] densité de la végétation
[Termes IGN] données lidar
[Termes IGN] espèce végétale
[Termes IGN] image à très haute résolution
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier (techniques et méthodes)
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) The estimation of various forest inventory attributes from high spatial resolution airborne remote sensing data has been widely examined and proved to be successful at the experimental level. Nevertheless, the operational use of these data in automated procedures to support forest inventories and forest management is still limited to a small number of cases. The reasons for this are high data costs, limited availability of remote sensing data over large areas and resistance from practitioners. In this review the main aim is to stimulate debate about spaceborne very high resolution stereo-imagery (VHRSI) as an alternative to airborne remote sensing data by presenting: (1) a case study on the retrieval of stand density, aboveground biomass and tree species using a set of easy-to-calculate variables obtained from VHRSI data combined with image processing and nonparametric classification and modelling approaches; and (2) the results of an expert opinion survey on the potential of VHRSI as compared with Light Detection and Ranging (LiDAR), hyperspectral and airborne digital imagery to derive a range of forest inventory attributes. In the case study, stand density was estimated with r² = 0.71 and RMSE = 156 trees (rel./norm. RMSE = 24.9 per cent/12.4 per cent), biomass with r² = 0.64 and RMSE of 36.7 t/ha (rel./norm. RMSE = 20.0 per cent/12.8 per cent) while tree species classifications with five species reached overall accuracies of 84.2 per cent (kappa = 0.81). These results were comparable to earlier studies in the same test site, obtained with more expensive airborne acquisitions. Expert opinions were more diverse for VHRSI and aerial photographs (Shannon index values of 0.94 and 0.97) than for LiDAR and hyperspectral data (Shannon index values 0.69 and 0.88). In our opinion, this reflects the current state-of-the-art in the application of VHRSI for automatically retrieving forest inventory attributes. The number of studies using these data is still limited, and the full potential of these datasets is not yet completely explored. Compared with LiDAR and hyperspectral data, which both mostly received high scores for forest inventory products matching the sensor systems’ strengths, VHRSI and aerial photographs received more homogeneous scores indicating their potential as multi-purpose instruments to collect forest inventory information. In summary, considering the simpler acquisition, reasonable price and the comparably easy data format and handling of VHRSI compared with other sensor types, we recommend further research on the application of these data for supporting operational forest inventories. Numéro de notice : A2017-902 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx014 En ligne : https://doi.org/10.1093/forestry/cpx014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93196
in Forestry, an international journal of forest research > vol 90 n° 5 (December 2017) . - pp 613 - 631[article]Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery / Jose Alan A. Castillo in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)
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Titre : Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery Type de document : Article/Communication Auteurs : Jose Alan A. Castillo, Auteur ; Armando A. Apan, Auteur ; Tek N. Maraseni, Auteur ; Severino G. Salmo, Auteur Année de publication : 2017 Article en page(s) : pp 70 - 85 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] biomasse aérienne
[Termes IGN] carte d'utilisation du sol
[Termes IGN] déboisement
[Termes IGN] estimation statistique
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] indice de végétation
[Termes IGN] mangrove
[Termes IGN] modèle de simulation
[Termes IGN] Philippines
[Termes IGN] régression linéaire
[Termes IGN] rétrodiffusion
[Termes IGN] variable biophysique (végétation)Résumé : (Auteur) The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82–0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8–28.5 Mg ha−1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement non-forest land uses, especially with the inclusion of elevation data. The study demonstrates encouraging results in biomass mapping of mangroves and other coastal land uses in the tropics using the freely accessible and relatively high-resolution Sentinel imagery. Numéro de notice : A2017-730 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.10.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.10.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88428
in ISPRS Journal of photogrammetry and remote sensing > vol 134 (December 2017) . - pp 70 - 85[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017121 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017122 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017123 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt Mapping and estimating land change between 2001 and 2013 in a heterogeneous landscape in West Africa: Loss of forestlands and capacity building opportunities / Hèou Maléki Badjana in International journal of applied Earth observation and geoinformation, vol 63 (December 2017)
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Titre : Mapping and estimating land change between 2001 and 2013 in a heterogeneous landscape in West Africa: Loss of forestlands and capacity building opportunities Type de document : Article/Communication Auteurs : Hèou Maléki Badjana, Auteur ; Pontus Olofsson, Auteur ; Curtis E. Woodcock, Auteur ; Jörg Helmschrot, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 15 - 23 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Afrique occidentale
[Termes IGN] analyse diachronique
[Termes IGN] Bénin
[Termes IGN] changement d'occupation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] déboisement
[Termes IGN] forêt
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-OLI
[Termes IGN] logiciel libre
[Termes IGN] occupation du sol
[Termes IGN] Orfeo Tool Box
[Termes IGN] QGIS
[Termes IGN] TogoRésumé : (auteur) In West Africa, accurate classification of land cover and land change remains a big challenge due to the patchy and heterogeneous nature of the landscape. Limited data availability, human resources and technical capacities, further exacerbate the challenge. The result is a region that is among the more understudied areas in the world, which in turn has resulted in a lack of appropriate information required for sustainable natural resources management. The objective of this paper is to explore open source software and easy-to-implement approaches to mapping and estimation of land change that are transferrable to local institutions to increase capacity in the region, and to provide updated information on the regional land surface dynamics. To achieve these objectives, stable land cover and land change between 2001 and 2013 in the Kara River Basin in Togo and Benin were mapped by direct multitemporal classification of Landsat data by parameterization and evaluation of two machine-learning algorithms. Areas of land cover and change were estimated by application of an unbiased estimator to sample data following international guidelines. A prerequisite for all tools and methods was implementation in an open source environment, and adherence to international guidelines for reporting land surface activities. Findings include a recommendation of the Random Forests algorithm as implemented in Orfeo Toolbox, and a stratified estimation protocol − all executed in the QGIS graphical use interface. It was found that despite an estimated reforestation of 10,0727 ± 3480 ha (95% confidence interval), the combined rate of forest and savannah loss amounted to 56,271 ± 9405 ha (representing a 16% loss of the forestlands present in 2001), resulting in a rather sharp net loss of forestlands in the study area. These dynamics had not been estimated prior to this study, and the results will provide useful information for decision making pertaining to natural resources management, land management planning, and the implementation of the United Nations Collaborative Programme on Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (UN-REDD). Numéro de notice : A2017-411 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2017.07.006 En ligne : https://doi.org/10.1016/j.jag.2017.07.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86298
in International journal of applied Earth observation and geoinformation > vol 63 (December 2017) . - pp 15 - 23[article]Remotely sensed forest habitat structures improve regional species conservation / Christian Reichsteiner in Remote sensing in ecology and conservation, vol 3 n° 4 (December 2017)
PermalinkStand-level wind damage can be assessed using diachronic photogrammetric canopy height models / Jean-Pierre Renaud in Annals of Forest Science, vol 74 n° 4 (December 2017)
PermalinkTerrestrial laser scanning reveals differences in crown structure of Fagus sylvatica in mixed vs. pure European forests / Ignacio Barbeito in Forest ecology and management, vol 405 (1 December 2017)
PermalinkWaste heaps left by historical Zn-Pb ore mining are hotspots of species diversity of beech forest understory vegetation / Marcin W. Woch in Science of the total environment, vol 599 - 600 (December 2017)
PermalinkMicrotopography and ecology of pit-mound structures in second-growth versus old-growth forests / Audrey Barker Plotkin in Forest ecology and management, vol 404 (15 November 2017)
PermalinkAn examination of diameter density prediction with k-NN and airborne lidar / Jacob L. Strunk in Forests, vol 8 n° 11 (November 2017)
PermalinkContinuum of floristic composition between two plant communities – Carici elongatae-Alnetum and Fraxino-Alnetum / Natalia Czapiewska in Forest research papers, vol 78 n° 4 (November 2017)
PermalinkFusing microwave and optical satellite observations to simultaneously retrieve surface soil moisture, vegetation water content, and surface soil roughness / Yohei Sawada in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)
PermalinkHabitat connectivity affects specialist species richness more than generalists in veteran trees / Anne Sverdrup-Thygeson in Forest ecology and management, vol 403 (1 November 2017)
PermalinkImproved atmospheric correction and chlorophyll-a remote sensing models for turbid waters in a dusty environment / Maryam R. Al Shehhi in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)
PermalinkMapping the height and spatial cover of features beneath the forest canopy at small-scales using airborne scanning discrete return Lidar / Matthew Sumnall in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)
PermalinkTree species classification using within crown localization of waveform LiDAR attributes / Rosmarie Blomley in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)
PermalinkAdapter les itinéraires sylvicoles pour atténuer les effets du changement climatique. Résultats pour la chênaie sessiliflore française à partir des réseaux d’expérimentations sylvicoles / François Lebourgeois in Revue forestière française, vol 69 n° 1 (octobre 2017)
PermalinkEnhancing plant diversity and mitigating BVOC emissions of urban green spaces through the introduction of ornamental tree species / Yuan Ren in Urban Forestry & Urban Greening, vol 27 (October 2017)
PermalinkHyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables / Sakari Tuominen in Silva fennica, vol 51 n° 5 (2017)
PermalinkMulti-model estimation of understorey shrub, herb and moss cover in temperate forest stands by laser scanner data / Hooman Latifi in Forestry, an international journal of forest research, vol 90 n° 4 (October 2017)
PermalinkQuelle est la fiabilité de l’estimation visuelle des catégories de diamètre lors des descriptions des peuplements ? / Sylvain Gaudin in Revue forestière française, vol 69 n° 1 (octobre 2017)
PermalinkSignificant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests / Jing Liu in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)
PermalinkStand-volume estimation from multi-source data for coppiced and high forest Eucalyptus spp. silvicultural systems in KwaZulu-Natal, South Africa / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)
PermalinkStrong gradients in forest sensitivity to climate change revealed by dynamics of forest fire cycles in the post Little Ice Age Era / Igor Drobyshev in Journal of geophysical research : Biogeosciences, vol 122 n° 10 (October 2017)
PermalinkSurvie des semis de ligneux pionniers dans les lits fluviaux : approche in et ex situ des facteurs de contrôle abiotiques et biologiques des espèces Populus nigra et Salix alba / Coraline Lise Wintenberger in Géomorphologie, vol 23 ([01/10/2017])
PermalinkThe potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas / Emanuele Santi in Remote sensing of environment, vol 200 (October 2017)
PermalinkVariance of light-related foliar traits across spatial and temporal scales in the Mediterranean evergreen Olea europaea L. / Adrián G. Escribano-Rocafort in Perspectives in Plant Ecology, Evolution and Systematics, vol 28 (October 2017)
PermalinkWind loads and competition for light sculpt trees into self-similar structures / Christophe Eloy in Nature communications, vol 8 (2017)
PermalinkTree size thresholds produce biased estimates of forest biomass dynamics / Eric B. Searle in Forest ecology and management, vol 400 (15 September 2017)
PermalinkUnderstanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications / Amanda Veloso in Remote sensing of environment, vol 199 (15 September 2017)
PermalinkBiodiversity effects on ecosystem functioning in a 15-year grassland experiment: patterns, mechanisms, and open questions / Wolfgang W. Weisser in Basic and Applied Ecology, vol 23 (September 2017)
PermalinkCrown bulk density and fuel moisture dynamics in Pinus pinaster stands are neither modified by thinning nor captured by the Forest Fire Weather Index / Marc Soler Martin in Annals of Forest Science, vol 74 n° 3 (September 2017)
PermalinkEvaluation de variables limnologiques grâce à des images Landsat / Danielle Teixeira Alves Da Silva in Géomatique expert, n° 118 (septembre - octobre 2017)
PermalinkForest canopy height estimation using satellite laser altimetry : a case study in the Western Ghats, India / S.M. Ghosh in Applied geomatics, vol 9 n° 3 (September 2017)
PermalinkForest change detection in incomplete satellite images with deep neural networks / Salman H. Khan in IEEE Transactions on geoscience and remote sensing, vol 55 n° 9 (September 2017)
PermalinkFunctional response trait analysis improves climate sensitivity estimation in beech forests at a trailing edge / Éva Salamon-Albert in Forests, vol 8 n° 9 (September 2017)
PermalinkImproving the prediction of African savanna vegetation variables using time series of MODIS products / Miriam Tsalyuk in ISPRS Journal of photogrammetry and remote sensing, vol 131 (September 2017)
PermalinkInventaire faune, flore et habitats sur la zone humide de Petelin (Corbelin et Veyrins-Thuellin, Nord-Isère) / Alexandre Gauthier in Lo Parvi, n° 25 (2017)
PermalinkA mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform / Bangqian Chen in ISPRS Journal of photogrammetry and remote sensing, vol 131 (September 2017)
PermalinkA Markov chain model for simulating wood supply from any-aged forest management based on national forest inventory (NFI) data / Jari Vauhkonen in Forests, vol 8 n° 9 (September 2017)
PermalinkQuantifying the sources of epistemic uncertainty in model predictions of insect disturbances in an uncertain climate / David R. Gray in Annals of Forest Science, vol 74 n° 3 (September 2017)
PermalinkA spatial dataset of forest mensuration collected in black pine plantations in central Italy / Paolo Cantiani in Annals of Forest Science, vol 74 n° 3 (September 2017)
PermalinkSpatiotemporal analyses of urban vegetation structural attributes using multitemporal Landsat TM data and field measurements / Zhibin Ren in Annals of Forest Science, vol 74 n° 3 (September 2017)
PermalinkUnsupervised domain adaptation for early detection of drought stress in hyperspectral images / P. Schmitter in ISPRS Journal of photogrammetry and remote sensing, vol 131 (September 2017)
PermalinkAutomatic mapping of forest stands based on three-dimensional point clouds derived from terrestrial laser-scanning / Tim Ritter in Forests, vol 8 n° 8 (August 2017)
PermalinkEvaluation of seasonal variations of remotely sensed leaf area index over five evergreen coniferous forests / Rong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)
PermalinkHybrid three-phase estimators for large-area forest inventory using ground plots, airborne lidar, and space lidar / Sören Holm in Remote sensing of environment, vol 197 (August 2017)
PermalinkImage matching as a data source for forest inventory – Comparison of semi-global matching and next-generation automatic terrain extraction algorithms in a typical managed boreal forest environment / Mari Kukkonen in International journal of applied Earth observation and geoinformation, vol 60 (August 2017)
PermalinkImproving Finnish multi-source national forest inventory by 3D aerial imaging / Sakari Tuominen in Silva fennica, vol 51 n° 4 (2017)
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