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A deep learning framework based on generative adversarial networks and vision transformer for complex wetland classification using limited training samples / Ali Jamali in International journal of applied Earth observation and geoinformation, vol 115 (December 2022)
[article]
Titre : A deep learning framework based on generative adversarial networks and vision transformer for complex wetland classification using limited training samples Type de document : Article/Communication Auteurs : Ali Jamali, Auteur ; Masoud Mahdianpari, Auteur ; fariba Mohammadimanesh, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 103095 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage profond
[Termes IGN] Canada
[Termes IGN] carte thématique
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] réseau antagoniste génératif
[Termes IGN] zone humideRésumé : (auteur) Wetlands have long been recognized among the most critical ecosystems globally, yet their numbers quickly diminish due to human activities and climate change. Thus, large-scale wetland monitoring is essential to provide efficient spatial and temporal insights for resource management and conservation plans. However, the main challenge is the lack of enough reference data for accurate large-scale wetland mapping. As such, the main objective of this study was to investigate the efficient deep-learning models for generating high-resolution and temporally rich training datasets for wetland mapping. The Sentinel-1 and Sentinel-2 satellites from the European Copernicus program deliver radar and optical data at a high temporal and spatial resolution. These Earth observations provide a unique source of information for more precise wetland mapping from space. The second objective was to investigate the efficiency of vision transformers for complex landscape mapping. As such, we proposed a 3D Generative Adversarial Network (3D GAN) to best achieve these two objectives of synthesizing training data and a Vision Transformer model for large-scale wetland classification. The proposed approach was tested in three different study areas of Saint John, Sussex, and Fredericton, New Brunswick, Canada. The results showed the ability of the 3D GAN to stimulate and increase the number of training data and, as a result, increase the accuracy of wetland classification. The quantitative results also demonstrated the capability of jointly using data augmentation, 3D GAN, and Vision Transformer models with overall accuracy, average accuracy, and Kappa index of 75.61%, 73.4%, and 71.87%, respectively, using a disjoint data sampling strategy. Therefore, the proposed deep learning method opens a new window for large-scale remote sensing wetland classification. Numéro de notice : A2022-828 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.103095 Date de publication en ligne : 08/11/2022 En ligne : https://doi.org/10.1016/j.jag.2022.103095 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102012
in International journal of applied Earth observation and geoinformation > vol 115 (December 2022) . - n° 103095[article]A semi-automatic method for extraction of urban features by integrating aerial images and LIDAR data and comparing its performance in areas with different feature structures (case study: comparison of the method performance in Isfahan and Toronto) / Masoud Azad in Applied geomatics, vol 14 n° 4 (December 2022)
[article]
Titre : A semi-automatic method for extraction of urban features by integrating aerial images and LIDAR data and comparing its performance in areas with different feature structures (case study: comparison of the method performance in Isfahan and Toronto) Type de document : Article/Communication Auteurs : Masoud Azad, Auteur ; Farshid Farnood Ahmadi, Auteur Année de publication : 2022 Article en page(s) : pp 589 - 607 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] détection d'objet
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de la végétation
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] extraction semi-automatique
[Termes IGN] image aérienne
[Termes IGN] Iran
[Termes IGN] modèle numérique de terrain
[Termes IGN] segmentation d'image
[Termes IGN] seuillage
[Termes IGN] Toronto
[Termes IGN] zone urbaineRésumé : (auteur) In this article, a new feature detection approach based on integration of LiDAR data and visible images in the form of a semi-automatic method has been proposed. In this approach, a two-step method for feature detection was developed using object-based analysis in order to increase the level of automation and level of accuracy in the detection process. The first step is providing a method for integration of two data sources for detection process by maintaining independency between image data and LiDAR altimetric data. In this step, the feature detection process is started based on image data and for detecting areas that detection properly is not done, LiDAR altimetric data is used. In the second step, a new method for detection of vegetation is implemented. Of the characteristics of this method is that there is no need to use the infrared band in the image data and also there is no need for LiDAR intensity data. The implemented method in the recent step is based on the new indices developed for detection of vegetation using three visible bands (red, green, and blue). The results of applying the method on two sample data sets show that the proposed approach and developed indices have the lowest dependency on the type and region of imaging and about each input image data includes visible bands (red, green, and blue) along with LiDAR data (that both data have a high spatial resolution), feature detection process is done with acceptable accuracy. Only thresholds depend on image data and change about different images. The changes are very small. Therefore, using the mean of these thresholds, despite may not be optimal for all image data, but generally is useful and for different images is efficient. In the case of many accessible images from Iran, the thresholds determined optimally by the trial-and-error method, the changes were very small. About the image data of Toronto and Iran which great changes were expected in the thresholds, the optimal thresholds showed very small changes. The results of this research demonstrated that the proposed method can successfully detect urban features (include vegetation, road, and building) with different shapes. Evaluation process showed that the overall accuracy, kappa coefficient, producer’s accuracy, and user’s accuracy of the proposed method about vegetation are 97%, 92%, 96%, and 94%, respectively. Also, the producer’s accuracy, user’s accuracy, and kappa coefficient about the building class are 94%, 95%, and 91%, respectively. About the road class these parameters are 95%, 89%, and 91%. Numéro de notice : A2022-892 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-022-00455-x Date de publication en ligne : 10/08/2022 En ligne : https://doi.org/10.1007/s12518-022-00455-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102239
in Applied geomatics > vol 14 n° 4 (December 2022) . - pp 589 - 607[article]Simulating multiple urban land use changes by integrating transportation accessibility and a vector-based cellular automata: a case study on city of Toronto / Xiaocong Xu in Geo-spatial Information Science, vol 25 n° 3 (October 2022)
[article]
Titre : Simulating multiple urban land use changes by integrating transportation accessibility and a vector-based cellular automata: a case study on city of Toronto Type de document : Article/Communication Auteurs : Xiaocong Xu, Auteur ; Dachuan Zhang, Auteur ; Xiaoping Liu, Auteur ; Jinpei Ou, Auteur ; Xinxin Wu, Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] accessibilité
[Termes IGN] automate cellulaire
[Termes IGN] changement d'occupation du sol
[Termes IGN] durée de trajet
[Termes IGN] modèle de simulation
[Termes IGN] outil d'aide à la décision
[Termes IGN] Toronto
[Termes IGN] transport collectifRésumé : (auteur) The accessibility provided by the transportation system plays an essential role in driving urban growth and urban functional land use changes. Conventional studies on land use simulation usually simplified the accessibility as proximities and adopted the grid-based simulation strategy, leading to the insufficiencies of characterizing spatial geometry of land parcels and simulating subtle land use changes among urban functional types. To overcome these limitations, an Accessibility-interacted Vector-based Cellular Automata (A-VCA) model was proposed for the better simulation of realistic land use change among different urban functional types. The accessibility at both local and zonal scales derived from actual travel time data was considered as a key driver of fine-scale urban land use changes and was integrated into the vector-based CA simulation process. The proposed A-VCA model was tested through the simulation of urban land use changes in the City of Toronto, Canada, during 2012–2016. A vector-based CA without considering the driving factor of accessibility (VCA) and a popular grid-based CA model (Future Land Use Simulation, FLUS) were also implemented for comparisons. The simulation results reveal that the proposed A-VCA model is capable of simulating fine-scale urban land use changes with satisfactory accuracy and good morphological feature (kappa = 0.907, figure of merit = 0.283, and cumulative producer’s accuracy = 72.83% ± 1.535%). The comparison also shows significant outperformance of the A-VCA model against the VCA and FLUS models, suggesting the effectiveness of the accessibility-interactive mechanism and vector-based simulation strategy. The proposed model provides new tools for a better simulation of fine-scale land use changes and can be used in assisting the formulation of urban and transportation planning. Numéro de notice : A2022-451 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1080/10095020.2022.2043730 Date de publication en ligne : 16/03/2022 En ligne : https://doi.org/10.1080/10095020.2022.2043730 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100397
in Geo-spatial Information Science > vol 25 n° 3 (October 2022)[article]Large-area high spatial resolution albedo retrievals from remote sensing for use in assessing the impact of wildfire soot deposition on high mountain snow and ice melt / André Bertoncini in Remote sensing of environment, vol 278 (September 2022)
[article]
Titre : Large-area high spatial resolution albedo retrievals from remote sensing for use in assessing the impact of wildfire soot deposition on high mountain snow and ice melt Type de document : Article/Communication Auteurs : André Bertoncini, Auteur ; Caroline Aubry-Wake, Auteur ; John W. Pomeroy, Auteur Année de publication : 2022 Article en page(s) : n° 113101 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] albedo
[Termes IGN] Colombie-Britannique (Canada)
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] fonte des glaces
[Termes IGN] glacier
[Termes IGN] Google Earth Engine
[Termes IGN] image Sentinel-MSI
[Termes IGN] image SRTM
[Termes IGN] image Terra-MODIS
[Termes IGN] incendie de forêt
[Termes IGN] montagne
[Termes IGN] neige
[Termes IGN] pouvoir de résolution radiométriqueRésumé : (auteur) Soot deposition from wildfires decreases snow and ice albedo and increases the absorption of shortwave radiation, which advances and accelerates melt. Soot deposition also induces algal growth, which further decreases snow and ice albedo. In recent years, increasingly severe and widespread wildfire activity has occurred in western Canada in association with climate change. In the summers of 2017 and 2018, westerly winds transported smoke from extensive record-breaking wildfires in British Columbia eastward to the Canadian Rockies, where substantial amounts of soot were deposited on high mountain glaciers, snowfields, and icefields. Several studies have addressed the problem of soot deposition on snow and ice, but the spatiotemporal resolution applied has not been compatible with studying mountain icefields that are extensive but contain substantial internal variability and have dynamical albedos. This study evaluates spatial patterns in the albedo decrease and net shortwave radiation (K*) increase caused by soot from intense wildfires in Western Canada deposited on the Columbia Icefield (151 km2), Canadian Rockies, during 2017 and 2018. Twelve Sentinel-2 images were used to generate high spatial resolution albedo retrievals during four summers (2017 to 2020) using a MODIS bidirectional reflectance distribution function (BRDF) model, which was employed to model the snow and ice reflectance anisotropy. Remote sensing estimates were evaluated using site-measured albedo on the icefield's Athabasca Glacier tongue, resulting in a R2, mean bias, and root mean square error (RMSE) of 0.68, 0.019, and 0.026, respectively. The biggest inter-annual spatially averaged soot-induced albedo declines were of 0.148 and 0.050 (2018 to 2020) for southeast-facing glaciers and the snow plateau, respectively. The highest inter-annual spatially-averaged soot-induced shortwave radiative forcing was 203 W/m2 for southeast-facing glaciers (2018 to 2020) and 106 W/m2 for the snow plateau (2017 to 2020). These findings indicate that snow albedo responded rapidly to and recovered rapidly from soot deposition. However, ice albedo remained low the year after fire, and this was likely related to a bio-albedo feedback involving microorganisms. Snow and ice K* were highest during low albedo years, especially for south-facing glaciers. These large-scale effects accelerated melt of the Columbia Icefield. The findings highlight the importance of using large-area high spatial resolution albedo estimates to analyze the effect of wildfire soot deposition on snow and ice albedo and K* on icefields, which is not possible using other approaches. Numéro de notice : A2022-466 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113101 Date de publication en ligne : 30/05/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113101 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100800
in Remote sensing of environment > vol 278 (September 2022) . - n° 113101[article]Modeling merchantable wood volume using airborne LiDAR metrics and historical forest inventory plots at a provincial scale / Antoine Leboeuf in Forests, vol 13 n° 7 (July 2022)
[article]
Titre : Modeling merchantable wood volume using airborne LiDAR metrics and historical forest inventory plots at a provincial scale Type de document : Article/Communication Auteurs : Antoine Leboeuf, Auteur ; Martin Riopel, Auteur ; Dave Munger, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 985 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] densité du bois
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] parcelle forestière
[Termes IGN] placette d'échantillonnage
[Termes IGN] Québec (Canada)
[Termes IGN] semis de points
[Termes IGN] volume en boisRésumé : (auteur) So far, large-scale projects aiming to map forest attributes using aerial LiDAR data have been developed using ground sample plots acquired synchronously with LiDAR. No large projects have been developed using aerial LiDAR acquired independent of ground sample plot datasets. The goal of this study was to develop and validate large-scale parametric merchantable wood volume estimation models using existing historical ground sample plots. The models can be applied to large LiDAR datasets to map merchantable wood volume as a 10 × 10 m raster. The study demonstrated that a relative density index (RDI) based on a self-thinning equation and dominant height were suitable variables that can be calculated both for ground sample plots and LiDAR datasets. The resulting volume raster showed sound accuracy rates when compared to validation zones: R², 82.25%; RMSE, 13.7 m3/ha; and bias, −4.09 m3/ha. The results show that ground sample plot datasets acquired synchronously with LiDAR can be used to calculate the RDI and dominant height. These variables can consequently be used to map forest attributes over a large area with a high level of accuracy, thus not requiring the implementation of new costly sample plots. Numéro de notice : A2022-547 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f13070985 Date de publication en ligne : 23/06/2022 En ligne : https://doi.org/10.3390/f13070985 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101132
in Forests > vol 13 n° 7 (July 2022) . - n° 985[article]Temporal transitions of demographic dot maps / Jeff Allen in International journal of cartography, vol 8 n° 2 (July 2022)PermalinkDetecting spatiotemporal traffic events using geosocial media data / Shishuo Xu in Computers, Environment and Urban Systems, vol 94 (June 2022)PermalinkEfficient calculation of distance transform on discrete global grid systems / Meysam Kazemi in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)PermalinkA geospatial workflow for the assessment of public transit system performance using near real-time data / Anastassios Dardas in Transactions in GIS, vol 26 n° 4 (June 2022)PermalinkCharacterizing stream morphological features important for fish habitat using airborne laser scanning data / Spencer Dakin Kuiper in Remote sensing of environment, vol 272 (April 2022)PermalinkConstruction d’un plugin QGIS de détection d’îlots de chaleur urbains à partir d’images satellitaires de type optique / Houssayn Meriche (2022)PermalinkPermalinkModeling post-logging height growth of black spruce-dominated boreal forests by combining airborne LiDAR and time since harvest maps / Batistin Bour in Forest ecology and management, vol 502 (December-15 2021)PermalinkIntegration of heterogeneous terrain data into Discrete Global Grid Systems / Mingke Li in Cartography and Geographic Information Science, vol 48 n° 6 (October 2021)PermalinkEvaluating the potential of cybercartography in facilitating indigenous self-determination: A case study with the Hupačasath first nation / Dexter Robson in Cartographica, vol 56 n° 3 (Fall 2021)PermalinkGIS-based logic scoring of preference method for urban densification suitability analysis / Shuoge Shen in Computers, Environment and Urban Systems, vol 89 (September 2021)PermalinkAnomalous variations of air temperature prior to earthquakes / Irfan Mahmood in Geocarto international, vol 36 n° 12 ([01/07/2021])PermalinkEvaluating the suitability of multi-scale terrain attribute calculation approaches for seabed mapping applications / Benjamin Misiuk in Marine geodesy, vol 44 n° 4 (July 2021)PermalinkFlood depth mapping in street photos with image processing and deep neural networks / Bahareh Alizadeh Kharazi in Computers, Environment and Urban Systems, vol 88 (July 2021)PermalinkGIS.LSP: A soft computing logic method and tool for geospatial suitability analysis / Shuoge Shen in Transactions in GIS, Vol 25 n° 3 (June 2021)PermalinkModel-based estimation of forest canopy height and biomass in the Canadian boreal forest using radar, LiDAR, and optical remote sensing / Michael L. 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A synthesis / Ahmed Laamrani in Forests, vol 11 n°11 (November 2020)PermalinkEffects of radiometric correction on cover type and spatial resolution for modeling plot level forest attributes using multispectral airborne LiDAR data / Wai Yeung Yan in ISPRS Journal of photogrammetry and remote sensing, vol 169 (November 2020)PermalinkRiver ice segmentation with deep learning / Abhineet Singh in IEEE Transactions on geoscience and remote sensing, vol 58 n° 11 (November 2020)PermalinkUsing climate-sensitive 3D city modeling to analyze outdoor thermal comfort in urban areas / Rabeeh Hosseinihaghighi in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)PermalinkOpenStreetMap quality assessment using unsupervised machine learning methods / Kent T. Jacobs in Transactions in GIS, Vol 24 n° 5 (October 2020)PermalinkChloroplast haplotypes of Northern red oak (Quercus rubra L.) stands in Germany suggest their origin from Northeastern Canada / Jeremias Götz in Forests, vol 11 n° 9 (September 2020)PermalinkDecolonizing world heritage maps using indigenous toponyms, stories, and interpretive attributes / Mark Palmer in Cartographica, vol 55 n° 3 (Fall 2020)PermalinkPermalinkNEAT approach for testing and validation of geospatial network agent-based model processes: case study of influenza spread / Taylor Anderson in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)PermalinkAux sources institutionnelles de l’enregistrement et du cadastre fonciers au Québec / Francis Roy in XYZ, n° 164 (septembre 2020)PermalinkEvaluating the potential of red spruce (Picea rubens Sarg.) to persist under climate change using historic provenance trials in eastern Canada / Wushuang Li in Forest ecology and management, Vol 466 (15 June 2020)PermalinkUsing machine learning to synthesize spatiotemporal data for modelling DBH-height and DBH-height-age relationships in boreal forests / Jiaxin Chen in Forest ecology and management, Vol 466 (15 June 2020)PermalinkLes États-Unis remplacent le NAD83 par le NATRF2022 : ce que cela signifie pour le Canada / Caroline Erickson in Geomatica, vol 74 n° 1 (Mars 2020)PermalinkTree annotations in LiDAR data using point densities and convolutional neural networks / Ananya Gupta in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)PermalinkPhotogrammetric Bathymetry for the Canadian Arctic / Matus Hodul in Marine geodesy, Vol 43 n° 1 (January 2020)PermalinkPredicting carbon accumulation in temperate forests of Ontario, Canada using a LiDAR-initialized growth-and-yield model / Paulina T. Marczak in Remote sensing, vol 12 n° 1 (January 2020)PermalinkA systematic evaluation of influence of image selection process on remote sensing-based burn severity indices in North American boreal forest and tundra ecosystems / Dong Chen in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)PermalinkCombining machine learning and compact polarimetry for estimating soil moisture from C-Band SAR data / Emanuele Santi in Remote sensing, Vol 11 n° 20 (October-2 2019)PermalinkMapping dead forest cover using a deep convolutional neural network and digital aerial photography / Jean-Daniel Sylvain in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)PermalinkThe utility of terrestrial photogrammetry for assessment of tree volume and taper in boreal mixedwood forests / Christopher Mulverhill in Annals of Forest Science, Vol 76 n° 3 (September 2019)PermalinkComparison of three algorithms to estimate tree stem diameter from terrestrial laser scanner data / Joris Ravaglia in Forests, vol 10 n° 7 (July 2019)PermalinkExploitation of deep learning in the automatic detection of cracks on paved roads / Won Mo Jung in Geomatica, vol 73 n° 2 (June 2019)PermalinkA four‐dimensional agent‐based model: A case study of forest‐fire smoke propagation / Alex Smith in Transactions in GIS, vol 23 n° 3 (June 2019)PermalinkWood quality of black spruce and balsam fir trees defoliated by spruce budworm: A case study in the boreal forest of Quebec, Canada / Carlos Paixao in Forest ecology and management, vol 437 (1 April 2019)PermalinkChilling and forcing temperatures interact to predict the onset of wood formation in Northern Hemisphere conifers / Nicolas Delpierre in Global change biology, vol 25 n° 3 (March 2019)PermalinkDeep mapping gentrification in a large Canadian city using deep learning and Google Street View / Lazar Ilic in Plos one, vol 14 n° 3 (March 2019)PermalinkDigital preservation, social history, and the Quon Sang Lung Laundry building : a case study from Fort Macleod, Alberta, Canada / Peter Dawson in Applied geomatics, vol 10 n° 4 (December 2018)PermalinkMapping experience: Age and indigeneity as mediating factors in users’ experiences with the Algonquian linguistic atlas / Adam Stone in Cartographica, vol 53 n° 4 (Winter 2018)PermalinkTowards operational marker-free registration of terrestrial lidar data in forests / Jean-François Tremblay in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)PermalinkUsing Network Segments in the Visualization of Urban Isochrones / Jeff Allen in Cartographica, vol 53 n° 4 (Winter 2018)PermalinkA new algorithm predicting the end of growth at five evergreen conifer forests based on nighttime temperature and the enhanced vegetation index / Huanhuan Yuan in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)PermalinkA new method for 3D individual tree extraction using multispectral airborne LiDAR point clouds / Wenxia Dai in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)PermalinkObject-based crop classification using multi-temporal SPOT-5 imagery and textural features with a Random Forest classifier / Huanxue Zhang in Geocarto international, vol 33 n° 10 (October 2018)PermalinkDigital aerial photogrammetry for assessing cumulative spruce budworm defoliation and enhancing forest inventories at a landscape-level / Tristan R.H. Goodbody in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkLa propriété en 3D : état des lieux / Anonyme in Géomatique expert, n° 123 (juillet - août 2018)PermalinkParametric bootstrap estimators for hybrid inference in forest inventories / Mathieu Fortin in Forestry, an international journal of forest research, vol 91 n° 3 (July 2018)PermalinkPredicting hardwood quality and its evolution over time in Quebec's forests / Hughes Power in Forestry, an international journal of forest research, vol 91 n° 3 (July 2018)PermalinkPost-1980 shifts in the sensitivity of boreal tree growth to North Atlantic Ocean dynamics and seasonal climate / Clémentine Ols in Global and Planetary Change, vol 165 (June 2018)PermalinkLiDAR, a technology to assist with smart cities and climate change resilience: a case study in an urban metropolis / Ryan Garnett in ISPRS International journal of geo-information, vol 7 n° 5 (May 2018)Permalink3D building model-assisted snapshot positioning algorithm / Rakesh Kumar in GPS solutions, vol 21 n° 4 (October 2017)PermalinkTree size thresholds produce biased estimates of forest biomass dynamics / Eric B. Searle in Forest ecology and management, vol 400 (15 September 2017)PermalinkNorthern conifer forest species classification using multispectral data acquired from an unmanned aerial vehicle / Steven E. Franklin in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 7 (July 2017)PermalinkCode Grey : mapping healthcare service deserts in Hamilton, Ontario and the impact on senior populations / Kristin M. Dosen in Cartographica, vol 52 n° 2 (Summer 2017)PermalinkGPS coordinate time series measurements in Ontario and Quebec, Canada / Hadis Samadi Alinia in Journal of geodesy, vol 91 n° 6 (June 2017)PermalinkNRC Remote clock secure dissemination of traceable time / Marina Gertsvolf in Inside GNSS, vol 12 n° 3 (May - June 2017)PermalinkPan-sharpening of Landsat-8 images and its application in calculating vegetation greenness and canopy water contents / Khan Rubayet Rahaman in ISPRS International journal of geo-information, vol 6 n° 6 (June 2017)PermalinkEstimating benefits to Canada and the world : the canadian spatial reference system precise point positioning service / Calvin Klatt in Geomatica, vol 71 n° 1 (March 2017)PermalinkPermalinkPermalinkPermalinkSVM et réseaux neuronaux convolutifs pour la classification de scènes urbaines / Amaury Zarzelli (2017)PermalinkDEM Fusion of elevation REST API data in support of rapid flood modelling / Heather McGrath in Geomatica, vol 70 n° 4 (December 2016)PermalinkExamining view angle effects on leaf N estimation in wheat using field reflectance spectroscopy / Xiao Song in ISPRS Journal of photogrammetry and remote sensing, vol 122 (December 2016)PermalinkTechnical considerations for modernizing Nova Scotia’s Coordinate Referencing System / Jason Bond in Geomatica, vol 70 n° 2 (June 2016)PermalinkThe Canadian Geodetic Vertical Datum of 2013 (CGVD2013) / Marc Véronneau in Geomatica, vol 70 n° 1 (March 2016)PermalinkPermalinkDéveloppement d’applications Android en réalité augmentée pour atténuer les risques liés aux séismes / Hugo Baltz (2016)PermalinkSpatially constrained clustering of ecological units to facilitate the design of integrated water monitoring networks in the St. Lawrence Basin / M.D. Adams in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)PermalinkInSAR assessment of surface deformations in urban coastal terrains associated with groundwater dynamics / Jonathan C. L. Normand in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)PermalinkModernization of the Nova Scotia coordinate referencing system through active control technology / Jason Bond in Geomatica, vol 69 n° 4 (December 2015)PermalinkA multi-sensor approach : geohazard management on the Canadian national railway corridor / Ryan Kromer in GIM international [en ligne], vol 29 n° 12 (December 2015)PermalinkResidual vegetation patches within natural boreal wild fires: Characterizing by pattern metrics, land cover expec tations and proximity to firebreak features / Yikalo H. Araya in Geomatica, vol 69 n° 4 (December 2015)Permalink