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A framework for group converging pattern mining using spatiotemporal trajectories / Bin Zhao in Geoinformatica, vol 24 n° 4 (October 2020)
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Titre : A framework for group converging pattern mining using spatiotemporal trajectories Type de document : Article/Communication Auteurs : Bin Zhao, Auteur ; Xintao Liu, Auteur ; Jinping Jia, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 745 - 776 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] analyse spatio-temporelle
[Termes IGN] base de données d'objets mobiles
[Termes IGN] base de données spatiotemporelles
[Termes IGN] comportement
[Termes IGN] convergence
[Termes IGN] exploration de données géographiques
[Termes IGN] jointure spatiale
[Termes IGN] objet mobile
[Termes IGN] reconnaissance de formesRésumé : (Auteur) A group event such as human and traffic congestion can be very roughly divided into three stages: converging stage before congestion, gathered stage when congestion happens, and dispersing stage that congestion disappears. It is of great interest in modeling and identifying converging behaviors before gathered events actually happen, which helps to proactively predict and handle potential public incidents such as serious stampedes. However, most of existing literature put too much emphasis on the second stage, only a few of them is dedicated to the first stage. In this paper, we propose a novel group pattern, namely converging, which refers to a group of moving objects converging from different directions during a certain period before gathered. To discover efficiently such converging patterns, we develop a framework for converging pattern mining (CPM) by examining how moving objects form clusters and the process of the “cluster containment”. The framework consists of three phases: snapshot cluster discovery phase, cluster containment join phase, and converging detection phase. As cluster containment mining is the key step, we develop three algorithms to discover cluster containment matches: a containment-join-algorithm, called SSCCJ, by using spatial proximity; a signature tree-based cluster-containment-join-algorithm, called STCCJ, which takes advantage of the cluster containment relations and signature techniques to filter enormous unqualified candidates in an efficient and effective way; and third, to keep the advantages of the above algorithms while avoiding their flaws, we further propose a signature quad-tree based cluster-containment-join algorithm, called SQTCCJ, which can identify efficiently matches by considering cluster spatial proximity as well as containment relations simultaneously. To assess the proposed methods, we redefine two evaluation metrics based on the concept of “Precision and Recall” in the field of information retrieval and the characteristics of converging patterns. We also propose a new indicator for measuring the duration of the converging stage in a group event. Finally, the effectiveness of the CPM and the efficiency of the mining algorithms are evaluated using three types of trajectory datasets, and the results show that the SQTCCJ algorithm demonstrates a superior performance. Numéro de notice : A2020-494 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00404-z Date de publication en ligne : 25/04/2020 En ligne : https://doi.org/10.1007/s10707-020-00404-z Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96114
in Geoinformatica > vol 24 n° 4 (October 2020) . - pp 745 - 776[article]Hierarchical instance recognition of individual roadside trees in environmentally complex urban areas from UAV laser scanning point clouds / Yongjun Wang in ISPRS International journal of geo-information, vol 9 n° 10 (October 2020)
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Titre : Hierarchical instance recognition of individual roadside trees in environmentally complex urban areas from UAV laser scanning point clouds Type de document : Article/Communication Auteurs : Yongjun Wang, Auteur ; Tengping Jiang, Auteur ; Jing Liu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 26 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme de filtrage
[Termes IGN] apprentissage profond
[Termes IGN] arbre hors forêt
[Termes IGN] arbre urbain
[Termes IGN] détection d'arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] gestion urbaine
[Termes IGN] image captée par drone
[Termes IGN] optimisation (mathématiques)
[Termes IGN] reconnaissance d'objets
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] voxel
[Termes IGN] zone urbaineRésumé : (auteur) Individual tree segmentation is essential for many applications in city management and urban ecology. Light Detection and Ranging (LiDAR) system acquires accurate point clouds in a fast and environmentally-friendly manner, which enables single tree detection. However, the large number of object categories and occlusion from nearby objects in complex environment pose great challenges in urban tree inventory, resulting in omission or commission errors. Therefore, this paper addresses these challenges and increases the accuracy of individual tree segmentation by proposing an automated method for instance recognition urban roadside trees. The proposed algorithm was implemented of unmanned aerial vehicles laser scanning (UAV-LS) data. First, an improved filtering algorithm was developed to identify ground and non-ground points. Second, we extracted tree-like objects via labeling on non-ground points using a deep learning model with a few smaller modifications. Unlike only concentrating on the global features in previous method, the proposed method revises a pointwise semantic learning network to capture both the global and local information at multiple scales, significantly avoiding the information loss in local neighborhoods and reducing useless convolutional computations. Afterwards, the semantic representation is fed into a graph-structured optimization model, which obtains globally optimal classification results by constructing a weighted indirect graph and solving the optimization problem with graph-cuts. The segmented tree points were extracted and consolidated through a series of operations, and they were finally recognized by combining graph embedding learning with a structure-aware loss function and a supervoxel-based normalized cut segmentation method. Experimental results on two public datasets demonstrated that our framework achieved better performance in terms of classification accuracy and recognition ratio of tree. Numéro de notice : A2020-665 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9100595 Date de publication en ligne : 10/10/2020 En ligne : https://doi.org/10.3390/ijgi9100595 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96142
in ISPRS International journal of geo-information > vol 9 n° 10 (October 2020) . - 26 p.[article]Impact of INSAT-3D/3DR radiance data assimilation in predicting tropical cyclone Titli over the bay of Bengal / Raghu Nadimpalli in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)
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Titre : Impact of INSAT-3D/3DR radiance data assimilation in predicting tropical cyclone Titli over the bay of Bengal Type de document : Article/Communication Auteurs : Raghu Nadimpalli, Auteur ; Akhil Srivastava, Auteur ; V. S. Prasad, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 6945 - 6957 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Bengale, golfe du
[Termes IGN] cyclone
[Termes IGN] image INSAT-VHRR
[Termes IGN] interpolation
[Termes IGN] matrice de covariance
[Termes IGN] modèle de transfert radiatif
[Termes IGN] précipitation
[Termes IGN] prévision météorologique
[Termes IGN] radiance
[Termes IGN] zone intertropicaleRésumé : (auteur) This is the first study concerning the assimilation of the INSAT-3D/3DR radiance in the Hurricane Weather Research and Forecasting (HWRF) model and assesses its credibility to improve track, intensity, and precipitation forecasts of tropical cyclone (TC) Titli that occurred over the Bay of Bengal (BoB), which showed rapid intensification (RI) and weakening through its lifetime. The inbuilt Gridpoint Statistical Interpolation (GSI) method is used with a 3-D variational (3DVAR) configuration. Three sets of numerical experiments such as control (CNTL) (no assimilation), Global Telecommunication System (GTS) (observations from GTS network), and INSAT-3D/3DR (INSAT-3D/3DR sounder radiance data and GTS observations) were carried out with seven different initializations. The radiance analysis reproduced the initial vortex and the prominent synoptic scale features associated with TC Titli. The average root-mean-square errors (RMSE) of the analysis were relatively lower in the INSAT-3D/3DR compared to the CNTL and GTS. The HWRF performance is enhanced for track simulation, with improvements in mean landfall position errors by 40%–70% and 26%–52% for the INSAT-3D/3DR and GTS runs, respectively. The assimilation of radiance data has a positive impact on the simulation of warm core and thermodynamic structures, which has led to a more accurate intensity prediction (by 30–47%) over the CNTL. The assimilation run could realistically simulate the RI and weakening phases of the TC. A cold dry air intrusion is also observed when associated with the weakening. The study highlights the need to incorporate INSAT-3D/3DR radiances for improved TC predictions over the BoB basin. Numéro de notice : A2020-587 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2978211 Date de publication en ligne : 25/03/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2978211 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95915
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 10 (October 2020) . - pp 6945 - 6957[article]Increasing 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])
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Titre : Increasing Cervidae populations have variable impacts on habitat suitability for threatened forest plant and lichen species Type de document : Article/Communication Auteurs : James D.M. Speed, Auteur ; Gunnar Austrheim, Auteur ; Mika Bendiksby, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 10 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Cervidae
[Termes IGN] écosystème forestier
[Termes IGN] flore forestière
[Termes IGN] forêt boréale
[Termes IGN] habitat forestier
[Termes IGN] lichen
[Termes IGN] Norvège
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Large herbivores play a key role in temperate and boreal forest ecosystems. Cervidae (deer) population densities and community structure have undergone drastic changes in many parts of the world over the past decades, often with deer populations increasing. Many studies show impacts of Cervidae on multiple ecosystem properties, including vegetation and biodiversity, at local spatial scales. At larger spatial scales, however, impacts of changing Cervidae populations on forest ecosystems are less known. Although both abiotic and biotic dimensions contribute to shaping species’ niches, abiotic variables are generally given prominence when modelling species habitats and ranges. This is despite biotic changes, including changes in trophic structure, being an important component of global environmental change. In this study, we examined the potential contribution of Cervidae densities to the habitat suitability for rare plant and lichen species across the temperate and boreal forests of Norway, where cervid densities have increased over the past 60 years. We also examined how these changes in herbivore communities may have shaped habitat suitability for rare lichens and plants and discuss the results in light of continuing shifts in herbivore assemblages. We ran habitat suitability models for 47 species of rare plants and lichens, which were selected based on herbivory reported as a criterion for placement on the national red list for species. Climate (temperature and precipitation), forest (forest type and productivity), soil pH and Cervidae densities (moose Alces alces, red deer Cervus elaphus and roe deer Capreolus capreolus) were used as independent variables. Densities of one or more of the three Cervidae species were inferred to be associated with the distribution of 14 (ten lichen, one bryophyte and three vascular plant species) of these 47 species. We found a range of habitat suitability associations with Cervidae densities, including positive, negative and hump-backed responses. Increases in Cervidae densities over the past 60 years may have led to different spatial trends in habitat suitability across the 14 species. Our results suggest that Cervidae densities are associated with the distribution of rare forest plant and lichen species differently at large spatial scales; experimental studies should test the causality of these associations. If causal, this implies that Cervidae management should find a balance between high and low densities to conserve several plant and lichen species. The preponderance of epiphytic lichens species, for which habitat suitability was associated with Cervidae densities, calls for field studies to focus on Cervidae impacts on forest lichens. Numéro de notice : A2020-622 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.1016/j.foreco.2020.118286 Date de publication en ligne : 20/06/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118286 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96018
in Forest ecology and management > vol 473 [01/10/2020] . - 10 p.[article]Integrated processing of ground- and space-based GPS observations: improving GPS satellite orbits observed with sparse ground networks / Wen Huang in Journal of geodesy, vol 94 n° 10 (October 2020)
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Titre : Integrated processing of ground- and space-based GPS observations: improving GPS satellite orbits observed with sparse ground networks Type de document : Article/Communication Auteurs : Wen Huang, Auteur ; Benjamin Männel, Auteur ; Pierre Sakic-Kieffer, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 13 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Techniques orbitales
[Termes IGN] modèle d'orbite
[Termes IGN] orbite basse
[Termes IGN] orbite précise
[Termes IGN] orbitographie
[Termes IGN] orbitographie par GNSS
[Termes IGN] récepteur GPS
[Termes IGN] station GPSRésumé : (auteur) The precise orbit determination (POD) of Global Navigation Satellite System (GNSS) satellites and low Earth orbiters (LEOs) are usually performed independently. It is a potential way to improve the GNSS orbits by integrating LEOs onboard observations into the processing, especially for the developing GNSS, e.g., Galileo with a sparse sensor station network and Beidou with a regional distributed operating network. In recent years, few studies combined the processing of ground- and space-based GNSS observations. The integrated POD of GPS satellites and seven LEOs, including GRACE-A/B, OSTM/Jason-2, Jason-3 and, Swarm-A/B/C, is discussed in this study. GPS code and phase observations obtained by onboard GPS receivers of LEOs and ground-based receivers of the International GNSS Service (IGS) tracking network are used together in one least-squares adjustment. The POD solutions of the integrated processing with different subsets of LEOs and ground stations are analyzed in detail. The derived GPS satellite orbits are validated by comparing with the official IGS products and internal comparison based on the differences of overlapping orbits and satellite positions at the day-boundary epoch. The differences between the GPS satellite orbits derived based on a 26-station network and the official IGS products decrease from 37.5 to 23.9 mm (34% improvement) in 1D-mean RMS when adding seven LEOs. Both the number of the space-based observations and the LEO orbit geometry affect the GPS satellite orbits derived in the integrated processing. In this study, the latter one is proved to be more critical. By including three LEOs in three different orbital planes, the GPS satellite orbits improve more than from adding seven well-selected additional stations to the network. Experiments with a ten-station and regional network show an improvement of the GPS satellite orbits from about 25 cm to less than five centimeters in 1D-mean RMS after integrating the seven LEOs. Numéro de notice : A2020-630 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01424-1 Date de publication en ligne : 10/10/2020 En ligne : https://doi.org/10.1007/s00190-020-01424-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96049
in Journal of geodesy > vol 94 n° 10 (October 2020) . - 13 p.[article]A LiDAR aiding ambiguity resolution method using fuzzy one-to-many feature matching / Chuang Qian in Journal of geodesy, vol 94 n° 10 (October 2020)
PermalinkMapping wetland using the object-based stacked generalization method based on multi-temporal optical and SAR data / Yaotong Cai in International journal of applied Earth observation and geoinformation, vol 92 (October 2020)
PermalinkA multi-frequency and multi-GNSS method for the retrieval of the ionospheric TEC and intraday variability of receiver DCBs / Min Li in Journal of geodesy, vol 94 n° 10 (October 2020)
PermalinkNetwork-constrained bivariate clustering method for detecting urban black holes and volcanoes / Qiliang Liu in International journal of geographical information science IJGIS, vol 34 n° 10 (October 2020)
PermalinkA preliminary exploration of the cooling effect of tree shade in urban landscapes / Qiuyan Yu in International journal of applied Earth observation and geoinformation, vol 92 (October 2020)
PermalinkRasterisation-based progressive photon mapping / Iordanis Evangelou in The Visual Computer, vol 36 n° 10 - 12 (October 2020)
PermalinkRoad network simplification for location-based services / Abdeltawab M. Hendawi in Geoinformatica, vol 24 n° 4 (October 2020)
PermalinkSpatio-temporal relationship between land cover and land surface temperature in urban areas: A case study in Geneva and Paris / Xu Ge in ISPRS International journal of geo-information, vol 9 n° 10 (October 2020)
PermalinkTowards dynamic forest trafficability prediction using open spatial data, hydrological modelling and sensor technology / Aura Salmivaara in Forestry, an international journal of forest research, vol 93 n° 5 (October 2020)
PermalinkTree species classification using structural features derived from terrestrial laser scanning / Louise Terryn in ISPRS Journal of photogrammetry and remote sensing, vol 168 (October 2020)
PermalinkUncertainty of forested wetland maps derived from aerial photography / Stephen P. Prisley in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 10 (October 2020)
PermalinkWide-area near-real-time monitoring of tropical forest degradation and deforestation using Sentinel-1 / Dirk Hoekman in Remote sensing, vol 12 n° 19 (October-1 2020)
PermalinkBackground tropospheric delay in geosynchronous synthetic aperture radar / Dexin Li in Remote sensing, vol 12 n° 18 (September-2 2020)
PermalinkAnalysis of chlorophyll concentration in potato crop by coupling continuous wavelet transform and spectral variable optimization / Ning Liu in Remote sensing, vol 12 n° 17 (September-1 2020)
PermalinkApplication of 30-meter global digital elevation models for compensating rational polynomial coefficients biases / Amin Alizadeh Naeini in Geocarto international, vol 35 n° 12 ([01/09/2020])
PermalinkApplication of UAV photogrammetry with LiDAR data to facilitate the estimation of tree locations and DBH values for high-value timber species in Northern Japanese mixed-wood forests / Kyaw Thu Moe in Remote sensing, vol 12 n° 17 (September-1 2020)
PermalinkApplying multi-temporal Landsat satellite data and Markov-cellular automata to predict forest cover change and forest degradation of sundarban reserve forest, Bangladesh / Mohammad Emran Hasan in Forests, vol 11 n° 9 (September 2020)
PermalinkBenefits of non-tidal loading applied at distinct levels in VLBI analysis / Matthias Glomsda in Journal of geodesy, vol 94 n° 9 (September 2020)
PermalinkCarbon stocks, partitioning, and wood composition in short-rotation forestry system under reduced planting spacing / Felipe Schwerz in Annals of Forest Science, vol 77 n° 3 (September 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)
PermalinkClimate–growth relationships at the transition between Fagus sylvatica and Pinus mugo forest communities in a Mediterranean mountain / Chiara Calderano in Annals of Forest Science, vol 77 n° 3 (September 2020)
PermalinkCO2 fertilization, transpiration deficit and vegetation period drive the response of mixed broadleaved forests to a changing climate in Wallonia / Louis de Wergifosse in Annals of Forest Science, vol 77 n° 3 (September 2020)
PermalinkComparing pedestrians’ gaze behavior in desktop and in real environments / Weihua Dong in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)
PermalinkCrater detection and registration of planetary images through marked point processes, multiscale decomposition, and region-based analysis / David Solarna in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)
PermalinkDeriving a frozen area fraction from Metop ASCAT backscatter based on Sentinel-1 / Helena Bergstedt in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)
PermalinkEvaluation of crop mapping on fragmented and complex slope farmlands through random forest and object-oriented analysis using unmanned aerial vehicles / Re-Yang Lee in Geocarto international, vol 35 n° 12 ([01/09/2020])
PermalinkGeo-environment risk assessment in Zhengzhou City, China / Chuanming Ma in Geomatics, Natural Hazards and Risk, vol 11 n° 1 (2020)
PermalinkGNSS scale determination using calibrated receiver and Galileo satellite antenna patterns / Arturo Villiger in Journal of geodesy, vol 94 n° 9 (September 2020)
PermalinkGRACE-FO precise orbit determination and gravity recovery / Z. Kang in Journal of geodesy, vol 94 n° 9 (September 2020)
PermalinkHyperspectral unmixing using orthogonal sparse prior-based autoencoder with hyper-laplacian loss and data-driven outlier detection / Zeyang Dou in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)
PermalinkIlluminating the spatio-temporal evolution of the 2008–2009 Qaidam earthquake sequence with the joint use of Insar time series and teleseismic data / Simon Daout in Remote sensing, vol 12 n° 17 (September-1 2020)
PermalinkImpact of extreme weather events on urban human flow: A perspective from location-based service data / Zhenhua Chen in Computers, Environment and Urban Systems, vol 83 (September 2020)
PermalinkLocal color and morphological image feature based vegetation identification and its application to human environment street view vegetation mapping, or how green is our county? / Istvan G. Lauko in Geo-spatial Information Science, vol 23 n° 3 (September 2020)
PermalinkLocal terrain modification method considering physical feature constraints for vector elements / Jiangfeng She in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)
PermalinkMapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat, Random Forest, and Google Earth Engine / Aparna R. Phalke in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)
PermalinkMultiscale supervised kernel dictionary learning for SAR target recognition / Lei Tao in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)
PermalinkUne nouvelle colonne dans la salle hypostyle de Karnak : Récit d'une méthode de restitution / Yves Egels in XYZ, n° 164 (septembre 2020)
PermalinkA novel algorithm to estimate phytoplankton carbon concentration in inland lakes using Sentinel-3 OLCI images / Heng Lyu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)
PermalinkPhysical, chemical and mechanical wood properties of Pinus nigra growing in Portugal / Alexandra Dias in Annals of Forest Science, vol 77 n° 3 (September 2020)
PermalinkRecognition of building group patterns using graph convolutional network / Rong Zhao in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)
PermalinkA semantic graph database for the interoperability of 3D GIS data / Eva Savina Malinverni in Applied geomatics, vol 12 n° 3 (September 2020)
PermalinkA spaceborne SAR-based procedure to support the detection of landslides / Giuseppe Esposito in Natural Hazards and Earth System Sciences, vol 20 n° 9 (September 2020)
PermalinkA spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery / Bo Yang in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)
PermalinkUse of Bayesian modeling to determine the effects of meteorological conditions, prescribed burn season, and tree characteristics on litterfall of pinus nigra and pinus pinaster stands / Juncal Espinosa in Forests, vol 11 n° 9 (September 2020)
PermalinkUsing OpenStreetMap data and machine learning to generate socio-economic indicators / Daniel Feldmeyer in ISPRS International journal of geo-information, vol 9 n° 9 (September 2020)
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