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See the forest and the trees: Effective machine and deep learning algorithms for wood filtering and tree species classification from terrestrial laser scanning / Zhouxin Xi in ISPRS Journal of photogrammetry and remote sensing, vol 168 (October 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 168 (October 2020) . - pp 1 - 16 Titre : See the forest and the trees: Effective machine and deep learning algorithms for wood filtering and tree species classification from terrestrial laser scanning Type de document : Article/Communication Auteurs : Zhouxin Xi, Auteur ; Christopher Hopkinson, Auteur ; Stewart B. Rood, Auteur ; Derek R. Peddle, Auteur Année de publication : 2020 Article en page(s) : pp 1 - 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] classification [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] espèce végétale [Termes descripteurs IGN] gestion forestière [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] télémétrie laser terrestre [Termes descripteurs IGN] variation saisonnière Résumé : (auteur) Determining tree species composition in natural forests is essential for effective forest management. Species classification at the individual tree level requires fine-scale traits which can be derived through terrestrial laser scanning (TLS) point clouds. A generalizable species classification framework also needs to decouple seasonal foliage variation from deciduous species, for which wood filtering is applicable. Different machine learning and deep learning models are feasible for wood filtering and species classification. We investigated 13 machine learning and deep learning classifiers for 9 species, and 15 classifiers for filtering wood points from TLS plot scans. Each classifier was evaluated using the criteria of mean Intersection over Union accuracy (mIoU), training stability and time cost. On average, deep learning classifiers outperformed machine learning classifiers by 10% and 5% in terms of wood and species classification mIoU, respectively. PointNet++ provided the best species classifier, with the highest mIoU (0.906), stability, and moderate time cost. Among wood classifiers, UNet achieved the top mIoU (0.839) while ResNet-50 was recommended for rapid trial and error testing. Across the classifications, the factors of input resolution, attributes and features were also analyzed. Hot zones of species classification with PointNet++ were visualized to indicate how AI interpret species traits. Numéro de notice : A2020-533 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.08.001 date de publication en ligne : 10/08/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.08.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95718 [article]

Automated estimation and tools to extract positions, velocities, breaks, and seasonal terms from daily GNSS measurements: illuminating nonlinear Salton Trough deformation / Michael B. Heflin in Earth and space science, vol 7 n° 7 (July 2020)  

Public [article]  inEarth and space science > vol 7 n° 7 (July 2020) . - 10 p. Titre : Automated estimation and tools to extract positions, velocities, breaks, and seasonal terms from daily GNSS measurements: illuminating nonlinear Salton Trough deformation Type de document : Article/Communication Auteurs : Michael B. Heflin, Auteur ; Andrea Donnellan, Auteur ; Jay Parker, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 10 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] automatisation des processus [Termes descripteurs IGN] Californie (Etats-Unis) [Termes descripteurs IGN] champ de vitesse [Termes descripteurs IGN] déformation horizontale de la croute terrestre [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] dorsale [Termes descripteurs IGN] faille géologique [Termes descripteurs IGN] modèle géologique [Termes descripteurs IGN] positionnement par GNSS [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] sismologie [Termes descripteurs IGN] station GPS [Termes descripteurs IGN] valeur aberrante [Termes descripteurs IGN] variation saisonnière Résumé : (auteur) This paper describes the methods used to estimate positions, velocities, breaks, and seasonalterms from daily Global Navigation Satellite System (GNSS) measurements. Break detection and outlierremoval have been automated so that decades of daily measurements from thousands of stations can beprocessed in a few hours. New measurements are added, and parameters are updated every week. Modelparameters allow separation of interseismic, annual, coseismic, and postseismic signals. Tools availablethrough GeoGateway (http://geo-gateway.org) allow rapid visualization and analysis of these terms forresults that can be subsetted in time or space. Results show highly variable and nonlinear motion for GPSstations in southern California. The variable motion is related to seasonal motions, distributed tectonicmotion, earthquakes, and postseismic motions that can continue for years. In some areas results suggest thatadditional processes are responsible for the observed motions. In general, following earthquakes, stationsreturn to their longterm motions after 2–3 years, though some exceptions occur. The use of the tools showsnonlinear motion in the Salton Trough of southern California related to the 2010 M7.2 El MayorCucapahearthquake, 2012 Brawley earthquake swarm, and a creep event on the Superstition Hills fault in 2017. Numéro de notice : A2020-446 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1029/2019EA000644 date de publication en ligne : 18/05/2020 En ligne : https://doi.org/10.1029/2019EA000644 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95516 [article]

Determining the road traffic accident hotspots using GIS-based temporal-spatial statistical analytic techniques in Hanoi, Vietnam / Khanh Giang Le in Geo-spatial Information Science, vol 23 n° 2 (June 2020)  

Public [article]  inGeo-spatial Information Science > vol 23 n° 2 (June 2020) . - pp 153 - 164 Titre : Determining the road traffic accident hotspots using GIS-based temporal-spatial statistical analytic techniques in Hanoi, Vietnam Type de document : Article/Communication Auteurs : Khanh Giang Le, Auteur ; Pei Liu, Auteur ; Liang-Tay Lin, Auteur Année de publication : 2020 Article en page(s) : pp 153 - 164 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes descripteurs IGN] accident de la route [Termes descripteurs IGN] base de données spatiotemporelles [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] estimation par noyau [Termes descripteurs IGN] Hanoï [Termes descripteurs IGN] indice de risque [Termes descripteurs IGN] nuit [Termes descripteurs IGN] système d'information géographique [Termes descripteurs IGN] variation diurne [Termes descripteurs IGN] variation saisonnière Résumé : (auteur) This study applied GIS-based statistical analytic techniques to investigate the influence of accident Severity Index (SI) on temporal-spatial patterns of accident hotspots related to the specific time intervals of day and seasons. Road Traffic Accident (RTA) data in 3 years (2015 − 2017) in Hanoi, Vietnam were used to analyze and test this approach. Firstly, the RTA data were divided into four seasons in accordance with Hanoi’s weather conditions and the time intervals such as the daytime, nighttime, or peak hours. Then, the Kernel Density Estimation (KDE) method was applied to analyze hotspots according to the time intervals and seasons. Finally, the results were presented by using the comap technique. This study considered both analyses with and without SI. The accident SI measures the seriousness of an accident. The approach method is to give higher weights to the more serious accidents, but not with the extremely high values calculated on a direct rate to the accident expenditures. The results showed that both analyses determined the relatively similar hotspots, but the rankings of some hotspots were quite different due to the integration of SI. It is better to take into account SI in determining RTA hotspots because the gained results are more precise and the rankings of hotspots are more accurate. From there, the traffic authorities can easily understand the causes behind each accident and provide reasonable solutions to solve the most dangerous hotspots in case of limited budget and resources appropriately. This is also the first study about this issue in Vietnam, so the contribution of the article will help the traffic authorities easily solve this problem not only in Hanoi but also in other cities. Numéro de notice : A2020-317 Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10095020.2019.1683437 date de publication en ligne : 02/12/2019 En ligne : https://doi.org/10.1080/10095020.2019.1683437 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95176 [article]

Improved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation / Eslam Ali in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 106 - 124 Titre : Improved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation Type de document : Article/Communication Auteurs : Eslam Ali, Auteur ; Wenbin Xu, Auteur ; Xiao-Li Ding, Auteur Année de publication : 2020 Article en page(s) : pp 106 - 124 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] correction des ombres [Termes descripteurs IGN] COSI-Corr [Termes descripteurs IGN] déplacement d'objet géographique [Termes descripteurs IGN] désert [Termes descripteurs IGN] désertification [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] dune [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image optique [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] incertitude des données [Termes descripteurs IGN] modèle d'inversion [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] prévention des risques [Termes descripteurs IGN] sable [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] SINAI [Termes descripteurs IGN] variation saisonnière [Termes descripteurs IGN] vent de sable Résumé : (auteur) Sand dune migration poses a potential threat to desert infrastructure, vegetation, and atmospheric conditions. Capturing the patterns of long-term dune migration is useful for predicting probable desertification issues and wind conditions across vast desert areas. In this study, we employed optical image matching and a singular value decomposition approach to estimate the rates of dune migration in the North Sinai Sand Sea using the free Landsat 8 and Sentinel-2 archives. Our optical image matching time-series selection and inversion (OPTSI) algorithm limited the difference in the solar illumination of correlated pairs to decrease shadows and seasonal variability. We found that the maximum annual dune migration rates were 9.4 m/a and 15.9 m/a for Landsat 8 and Sentinel-2 data, respectively, and the results of time-series analysis revealed the existence of seasonal variations in dune migration controlled by wind regimes. The directions of sand movement extracted from the mean velocity solution agreed strongly with each other and with the drift directions estimated using wind data from meteorological stations. We assessed the uncertainty of each solution based on the variance of stable areas. Our results showed that the proposed inversion decreased uncertainty by up to 25% and increased the spatial coverage by up to 20%. This algorithm is also promising for the retrieval of historical time series on the ground displacements of glaciers and slow-moving landslides employing free archives that provide high-frequency images. Numéro de notice : A2020-253 Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.04.004 date de publication en ligne : 27/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.04.004 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94997 [article]

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Year-to-year crown condition poorly contributes to ring width variations of beech trees in French ICP level I network / Clara Tallieu in Forest ecology and management, Vol 465 (1 June 2020)  

Public [article]  inForest ecology and management > Vol 465 (1 June 2020) . - 15 p. Titre : Year-to-year crown condition poorly contributes to ring width variations of beech trees in French ICP level I network Type de document : Article/Communication Auteurs : Clara Tallieu, Auteur ; Vincent Badeau, Auteur ; Denis Allard, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 15 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] dendrochronologie [Termes descripteurs IGN] Fagus (genre) [Termes descripteurs IGN] Fagus sylvatica [Termes descripteurs IGN] feuille (végétation) [Termes descripteurs IGN] houppier [Termes descripteurs IGN] indice foliaire [Termes descripteurs IGN] pollution atmosphérique [Termes descripteurs IGN] sécheresse [Termes descripteurs IGN] stress hydrique [Termes descripteurs IGN] surveillance forestière [Termes descripteurs IGN] variation saisonnière [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Since the 1980-90′s episodes of decline in Central European Forests, forest condition has been surveyed thanks to the trans-national network the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests). It has been traditionally accepted that leaf loss is directly related to impairment of physiological condition of the tree. A few studies tried to correlate crown condition and growth trends while others concentrated on linking annual growth with crown observation at one date clustered into fertility classes. However, none focussed on the high frequency synchronism between leaf loss from annual network observations and annual radial growth issued from dendrochronology. Therefore, we jointly studied annual leaf loss observations and tree-ring width measurements on 715 common beech (Fagus sylvatica L.) trees distributed in the French part of the ICP monitoring network. Detrended inter-annual variations of leaf loss and tree-ring width index were used as response variables in the machine-learning algorithm Random Forest to investigate a common response to abiotic (current and lagged) and biotic hazards, to test the extent to which leaf loss helped to predict inter-annual variations in radial growth. Using Random Forest was effective to identify a common sensitivity to soil water deficit at different time lags. Previous-year climatic variables tended to control leaf loss while radial growth was more sensitive to current-year soil water deficit. Late frost damages were observed on crown condition in mountainous regions but no impact was detected on radial growth. Few significant biotic damages were observed on growth or leaf loss. Leaf loss series did not show a clear common signal among trees from a plot as did radial growth and captured fewer pointer years. Radial growth index did not fall below normal until a 20% leaf loss was reached. However, this threshold is driven by a few extreme leaf loss events. As shown by our joint analysis of leaf loss and radial growth pointer years, no relationship occurred in cases of slight or moderate defoliation. Crown condition is a poorer descriptor of tree vitality than radial growth. Numéro de notice : A2020-287 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2020.118071 date de publication en ligne : 01/04/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118071 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95111 [article]

Visualizing when, where, and how fires happen in U.S. parks and protected areas / Nicole C. Inglis in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

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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 (2020)  

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Recent 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)  

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Xylem anatomy of Robinia pseudoacacia L. and Quercus robur L. is differently affected by climate in a temperate alluvial forest / Paola Nola in Annals of Forest Science [en ligne], Vol 77 n° 1 (March 2020)  

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Estimating 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)  

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Arctic 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)  

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A new segmentation method for the homogenisation of GNSS-derived IWV time-series / Annarosa Quarello (2020)  

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Accurate modelling of canopy traits from seasonal Sentinel-2 imagery based on the vertical distribution of leaf traits / Tawanda W. Gara in ISPRS Journal of photogrammetry and remote sensing, vol 157 (November 2019)  

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Vulnerability of forest ecosystems to fire in the French Alps / Sylvain Dupire in European Journal of Forest Research, Vol 138 n° 5 (octobre 2019)  

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Decomposition of geodetic time series: A combined simulated annealing algorithm and Kalman filter approach / Feng Ming in Advances in space research, vol 64 n°5 (1 September 2019)  

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