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An original method for tree species classification using multitemporal multispectral and hyperspectral satellite data / Olga Grigorieva in Silva fennica, vol 54 n° 2 (March 2020)
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Titre : An original method for tree species classification using multitemporal multispectral and hyperspectral satellite data Type de document : Article/Communication Auteurs : Olga Grigorieva, Auteur ; Olga Brovkina, Auteur ; Alisher Saidov, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Betula (genre)
[Termes IGN] carte forestière
[Termes IGN] classification
[Termes IGN] erreur de classification
[Termes IGN] image hyperspectrale
[Termes IGN] image Landsat-OLI
[Termes IGN] image multibande
[Termes IGN] phénologie
[Termes IGN] Pinus (genre)
[Termes IGN] réflectance spectrale
[Termes IGN] République Tchèque
[Termes IGN] Russie
[Termes IGN] signature spectrale
[Termes IGN] variation saisonnièreRésumé : (auteur) his study proposes an original method for tree species classification by satellite remote sensing. The method uses multitemporal multispectral (Landsat OLI) and hyperspectral (Resurs-P) data acquired from determined vegetation periods. The method is based on an original database of spectral features taking into account seasonal variations of tree species spectra. Changes in the spectral signatures of forest classes are analyzed and new spectral–temporal features are created for the classification. Study sites are located in the Czech Republic and northwest (NW) Russia. The differences in spectral reflectance between tree species are shown as statistically significant in the sub-seasons of spring, first half of summer, and main autumn for both study sites. Most of the errors are related to the classification of deciduous species and misclassification of birch as pine (NW Russia site), pine as mixture of pine and spruce, and pine as mixture of spruce and beech (Czech site). Forest species are mapped with accuracy as high as 80% (NW Russia site) and 81% (Czech site). The classification using multitemporal multispectral data has a kappa coefficient 1.7 times higher than does that of classification using a single multispectral image and 1.3 times greater than that of the classification using single hyperspectral images. Potentially, classification accuracy can be improved by the method when applying multitemporal satellite hyperspectral data, such as in using new, near-future products EnMap and/or HyspIRI with high revisit time. Numéro de notice : A2020-324 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14214/sf.10143 Date de publication en ligne : 02/03/2020 En ligne : https://doi.org/10.14214/sf.10143 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95198
in Silva fennica > vol 54 n° 2 (March 2020)[article]Assessment of salt marsh change on Assateague Island National Seashore between 1962 and 2016 / Anthony Campbell in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 3 (March 2020)
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Titre : Assessment of salt marsh change on Assateague Island National Seashore between 1962 and 2016 Type de document : Article/Communication Auteurs : Anthony Campbell, Auteur ; Yeqiao Wang, Auteur Année de publication : 2020 Article en page(s) : pp 187 - 194 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse diachronique
[Termes IGN] approche hiérarchique
[Termes IGN] Atlantique (océan)
[Termes IGN] biodiversité
[Termes IGN] cartographie thématique
[Termes IGN] détection de changement
[Termes IGN] Etats-Unis
[Termes IGN] image à très haute résolution
[Termes IGN] image satellite
[Termes IGN] lidar bathymétrique
[Termes IGN] littoral
[Termes IGN] marais salant
[Termes IGN] montée du niveau de la mer
[Termes IGN] service écosystémique
[Termes IGN] surveillance du littoralRésumé : (auteur) Salt marshes provide extensive ecosystem services, including high biodiversity, denitrification, and wave attenuation. In the mid-Atlantic, sea level rise is predicted to affect salt marsh ecosystems severely. This study mapped the entirety of Assateague Island with Very High Resolution satellite imagery and object-based methods to determine an accurate salt marsh baseline for change analysis. Topobathy-metric light detection and ranging was used to map the salt marsh and model expected tidal effects. The satellite imagery, collected in 2016 and classified at two hierarchical thematic schemes, were compared to determine appropriate thematic richness. Change analysis between this 2016 map and both a manually delineated 1962 salt marsh extent and image classification of the island from 1994 determined rates off change. The study found that from 1962 to 1994, salt marsh expanded by 4.01 ha/year, and from 1994 to 2016 salt marsh was lost at a rate of -3.4 ha/ year. The study found that salt marsh composition, (percent vegetated salt marsh) was significantly influenced by elevation, the length of mosquito ditches, and starting salt marsh composition. The study illustrates the importance of remote sensing monitoring for understanding site-specific changes to salt marsh environments and the barrier island system. Numéro de notice : A2020-148 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.3.187 Date de publication en ligne : 01/03/2020 En ligne : https://doi.org/10.14358/PERS.86.3.187 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94777
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 3 (March 2020) . - pp 187 - 194[article]Clinal variation along precipitation gradients in Patagonian temperate forests: unravelling demographic and selection signatures in three Nothofagus spp. / Carolina Soliani in Annals of Forest Science, Vol 77 n° 1 (March 2020)
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Titre : Clinal variation along precipitation gradients in Patagonian temperate forests: unravelling demographic and selection signatures in three Nothofagus spp. Type de document : Article/Communication Auteurs : Carolina Soliani, Auteur ; Maria Marta Azpilicueta, Auteur ; Maria Veronica Arana, Auteur ; Paula Marchelli, Auteur Année de publication : 2020 Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] forêt tempérée
[Termes IGN] génétique forestière
[Termes IGN] Nothofagus (genre)
[Termes IGN] nothofagus pumilio
[Termes IGN] Patagonie
[Termes IGN] Pléistocène
[Termes IGN] précipitation
[Termes IGN] prévision
[Termes IGN] sécheresse
[Termes IGN] stress hydrique
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Key message: Past demographic changes and current selection pressures determine the genetic variation displayed by Nothofagus species along rainfall gradients. Based on the diversity trends observed at candidate genes associated to drought stress, we inferred a differential species’ adaptive potential.
Context: Clinal genetic variation in natural populations could reflect either recent demographic history or the evolution of adapted genotypes along heterogeneous environments.
Aims: We describe genetic variation patterns in three Nothofagus species of South American temperate forests, growing along steep rainfall gradients. Our hypothesis is that the selection pressure along this gradient reinforces the genetic structure previously shaped by Pleistocene climate oscillations.
Methods: We screened variation along gradients at putative adaptive markers: candidate genes involved in response to drought, and EST-SSRs linked to drought stress genes. Genomic SSRs (gSSRs) were used to decouple the incidence of demographic events in the genetic structure.
Results: Genetic diversity at SSRs agreed with the putative location of cryptic Pleistocene refugia in Nothofagus. In addition, each species showed different trends for nucleotide diversity at candidate genes. Unbiased heterozygosity significantly correlated with precipitation at EST-SSRs in Nothofagus nervosa. We found evidences of balancing selection and several SNPs departed from neutral expectations.
Conclusions: Nothofagus genetic variability shows a strong imprint of demographic changes that reveals refugia location for the species during Pleistocene. This variability is modelled by environmental conditions across natural gradients, which impose selection pressure at genome regions related to stress response, providing clues about inter-specific differences in adaptive potential to water deficit.Numéro de notice : A2020-032 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0908-x Date de publication en ligne : 10/01/2020 En ligne : https://doi.org/10.1007/s13595-019-0908-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94489
in Annals of Forest Science > Vol 77 n° 1 (March 2020) . - 17 p.[article]A discriminative tensor representation model for feature extraction and classification of multispectral LiDAR data / Qingwang Wang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
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Titre : A discriminative tensor representation model for feature extraction and classification of multispectral LiDAR data Type de document : Article/Communication Auteurs : Qingwang Wang, Auteur ; Yanfeng Gu, Auteur Année de publication : 2020 Article en page(s) : pp 1568 -1586 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Amérique du nord
[Termes IGN] analyse discriminante
[Termes IGN] calcul tensoriel
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification multibande
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] état de l'art
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image multibande
[Termes IGN] modèle géométrique
[Termes IGN] semis de points
[Termes IGN] tenseur
[Termes IGN] vectorisation
[Termes IGN] voisinage (relation topologique)Résumé : (Auteur) Multispectral light detection and ranging (MS-LiDAR) systems open the door to the possibility in the 3-D land cover classification at a finer scale using only point cloud data. This article proposes a model based on the tensor representation for multispectral point cloud classification. The proposed method combines the 3-D local spatial structure of each multispectral point by characterizing the point with a second-order tensor. The first mode of the tensor indicates the spatial location and spectral information of each point (i.e., the row of the second-order tensor) and the second mode denotes the neighborhood geometric and spectral structures (i.e., the column of the second-order tensor). Then we develop a novel tensor manifold discriminant embedding (TMDE) algorithm to extract the geometric–spectral features for multispectral point clouds classification. TMDE solves the mapping matrices of each mode by preserving the intraclass samples’ distribution further making it more compact and maximizing the distance of different classes. Finally, the support vector machine classifier with the extracted features as input is used to implement the classification of multispectral point clouds. Experiments are conducted on two real multispectral point cloud data sets. The experimental results demonstrate that the proposed method can achieve significant improvements in classification accuracies in comparison with several state-of-the-art algorithms. Numéro de notice : A2020-086 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2947081 Date de publication en ligne : 30/10/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2947081 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94660
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 3 (March 2020) . - pp 1568 -1586[article]Estimation of variance and spatial correlation width for fine-scale measurement error in digital elevation model / Mikhail L. Uss in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
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Titre : Estimation of variance and spatial correlation width for fine-scale measurement error in digital elevation model Type de document : Article/Communication Auteurs : Mikhail L. Uss, Auteur ; Benoit Vozel, Auteur ; Vladimir V. Lukin, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1941 - 1956 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] Advanced Spaceborne Thermal Emission and Reflection Radiometer
[Termes IGN] analyse multivariée
[Termes IGN] corrélation automatique de points homologues
[Termes IGN] courbe épipolaire
[Termes IGN] erreur de mesure
[Termes IGN] image ALOS
[Termes IGN] image TanDEM-X
[Termes IGN] modèle d'erreur
[Termes IGN] modèle numérique de surface
[Termes IGN] mouvement brownien
[Termes IGN] varianceRésumé : (Auteur) In this article, we borrow from the blind noise parameter estimation (BNPE) methodology early developed in the image processing field an original and innovative no-reference approach to estimate digital elevation model (DEM) vertical error parameters without resorting to a reference DEM. The challenges associated with the proposed approach related to the physical nature of the error and its multifactor structure in DEM are discussed in detail. A suitable multivariate method is then developed for estimating the error in gridded DEM. It is built on a recently proposed vectorial BNPE method for estimating spatially correlated noise using noise informative areas and fractal Brownian motion. The new multivariate method is derived to estimate the effect of the stacking procedure and that of the epipolar line error on local (fine-scale) standard deviation and autocorrelation function width of photogrammetric DEM measurement error. Applying the new estimator to Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) GDEM2 and Advanced Land Observing Satellite (ALOS) World 3D DEMs, good agreement of derived estimates with results available in the literature is evidenced. Adopted for TanDEM-X-DEM, estimates obtained agree well with the values provided in the height error map. In future works, the proposed no-reference method for analyzing DEM error can be extended to a larger number of predictors for accounting for other factors influencing remote sensing (RS) DEM accuracy. Numéro de notice : A2020-092 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2951178 Date de publication en ligne : 28/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2951178 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94666
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 3 (March 2020) . - pp 1941 - 1956[article]Evaluation of the high-rate GNSS-PPP method for vertical structural motion / Mosbeh R. Kaloop in Survey review, vol 52 n° 371 (March 2020)
PermalinkHeuristic sample learning for complex urban scenes: Application to urban functional-zone mapping with VHR images and POI data / Xiuyuan Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 161 (March 2020)
PermalinkHierarchical classification of pole‐like objects in mobile laser scanning point clouds / Rufei Liu in Photogrammetric record, vol 35 n° 169 (March 2020)
PermalinkIntegrated edge detection and terrain analysis for agricultural terrace delineation from remote sensing images / Wen Dai in International journal of geographical information science IJGIS, vol 34 n° 3 (March 2020)
PermalinkLes missions photogrammétriques réalisées par drone au centimètre sans points de calage au sol / Olivier Degueldre in XYZ, n° 162 (mars 2020)
PermalinkMorphological tessellation as a way of partitioning space: Improving consistency in urban morphology at the plot scale / Martin Fleischmann in Computers, Environment and Urban Systems, vol 80 (March 2020)
PermalinkMulti-century reconstruction suggests complex interactions of climate and human controls of forest fire activity in a Karelian boreal landscape, North-West Russia / N. Ryzhkova in Forest ecology and management, vol 459 (1 March 2020)
PermalinkQuels plans de comparaison à Paris avant le nivellement général de la France ? / Alain Coulomb in XYZ, n° 162 (mars 2020)
PermalinkRecent sea level change in the black sea from satellite altimetry and tide gauge observations / Nevin Betül Avsar in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
PermalinkSimultaneous intensity bias estimation and stripe noise removal in infrared images using the global and local sparsity constraints / Li Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
PermalinkSmoothing and predicting celestial pole offsets using a Kalman filter and smoother / Jolanta Nastula in Journal of geodesy, Vol 94 n°3 (March 2020)
PermalinkPermalinkValidation of marine geoid models by utilizing hydrodynamic model and shipborne GNSS profiles / Sander Varbla in Marine geodesy, Vol 43 n° 2 (March 2020)
PermalinkAutomated extraction of lane markings from mobile LiDAR point clouds based on fuzzy inference / Heidar Rastiveis in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)
PermalinkA breakpoint detection in the mean model with heterogeneous variance on fixed time-intervals / Olivier Bock in Statistics and Computing, vol 29 n° 1 (February 2020)
PermalinkCloud detection by luminance and inter-band parallax analysis for pushbroom satellite imagers / Tristan Dagobert in IPOL Journal, Image Processing On Line, vol 10 (2020)
PermalinkComplex deformation at shallow depth during the 30 October 2016 Mw6.5 Norcia earthquake: interferencebetween tectonic and gravity processes? / Arthur Delorme in Tectonics, vol 39 n° 2 (February 2020)
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PermalinkA convolutional neural network approach for counting and geolocating citrus-trees in UAV multispectral imagery / Lucas Prado Osco in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)
PermalinkData scale as cartography: a semi-automatic approach for thematic web map creation / Auriol Degbelo in Cartography and Geographic Information Science, vol 47 n° 2 (February 2020)
PermalinkEstimating wheat yields in Australia using climate records, satellite image time series and machine learning methods / Elisa Kamir in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)
PermalinkGeneralized tensor regression for hyperspectral image classification / Jianjun Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)
PermalinkLand use and land cover change modeling and future potential landscape risk assessment using Markov-CA model and analytical hierarchy process / Biswajit Nath in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)
PermalinkLandslide displacement mapping based on ALOS-2/PALSAR-2 data using image correlation techniques and SAR interferometry: application to the Hell-Bourg landslide (Salazie Circle, La Réunion Island) / Daniel Raucoules in Geocarto international, vol 35 n° 2 ([01/02/2020])
PermalinkLandslide susceptibility mapping using maximum entropy and support vector machine models along the highway corridor, Garhwal Himalaya / Vijendra Kumar Pandey in Geocarto international, vol 35 n° 2 ([01/02/2020])
PermalinkOptimising drone flight planning for measuring horticultural tree crop structure / Yu-Hsuan Tu in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)
PermalinkPromoting environmental justice through Integrated mapping approaches: the map of water conflicts in Andalusia (Spain) / Belen Pedregal in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)
PermalinkRadial interpolation of GPS and leveling data of ground deformation in a resurgent caldera: application to Campi Flegrei (Italy) / Andrea Bevilacqua in Journal of geodesy, vol 94 n°2 (February 2020)
PermalinkThe "Incense Road" from Petra to Gaza: an analysis using GIS and Cost functions / Motti Zohar in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)
PermalinkA two-step approach for the correction of rolling shutter distortion in UAV photogrammetry / Yilin Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)
PermalinkTypology of meteorological weather forecast maps printed in world newspapers / Jaromir Kolejka in Cartographic journal (the), Vol 57 n° 1 (February 2020)
PermalinkModelling the orthoimage accuracy using DEM accuracy and off-nadir angle / Altan Yilmaz in Geocarto international, Vol 35 n° 1 ([02/01/2020])
PermalinkSpatial visualization of quantitative landscape changes in an industrial region between 1827 and 1883. Case study Katowice, southern Poland / Paweł Cybulski in Journal of maps, vol 16 n° 1 ([02/01/2020])
PermalinkPermalinkAbsolute field calibration for multi-GNSS receiver antennas at ETH Zurich / Daniel Willi in GPS solutions, vol 24 n° 1 (January 2020)
PermalinkPermalinkPermalinkAnalyse automatique du couvert végétal pour la gestion du risque végétation en milieu ferroviaire à partir d'imagerie aérienne / Hélène Rouillon (2020)
PermalinkApplication of geographic Information system and remote sensing in multiple criteria analysis to identify priority areas for biodiversity conservation in Vietnam / Xuan Dinh Vu (2020)
PermalinkApplication of machine learning techniques for evidential 3D perception, in the context of autonomous driving / Edouard Capellier (2020)
PermalinkArctic sea ice thickness retrievals from CryoSat-2: seasonal and interannual comparisons of three different products / Mengmeng Li in International Journal of Remote Sensing IJRS, vol 41 n° 1 (01 - 08 janvier 2020)
PermalinkCamera orientation, calibration and inverse perspective with uncertainties: a Bayesian method applied to area estimation from diverse photographs / Grégoire Guillet in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)
PermalinkCaractérisation de la contribution des charges hydrologiques, atmosphériques et océaniques aux séries temporelles de position GNSS : analyse comparée des modèles de charge et de mouvement du géocentre / Elie-Alban Lescout (2020)
PermalinkCaractérisation du manteau neigeux arctique, suivi climatique et télédétection micro-onde / Céline Vargel (2020)
PermalinkCartographie des essences forestières à partir de séries temporelles d’images satellitaires à hautes résolutions : stabilité des prédictions, autocorrélation spatiale et cohérence avec la phénologie observée in situ / Nicolas Karasiak (2020)
PermalinkCartographie sémantique hybride de scènes urbaines à partir de données image et Lidar / Mohamed Boussaha (2020)
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