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Fusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method / Yuedong Wang in Journal of geodesy, vol 94 n° 5 (May 2020)  

Public [article]  inJournal of geodesy > vol 94 n° 5 (May 2020) Titre : Fusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method Type de document : Article/Communication Auteurs : Yuedong Wang, Auteur ; Zefa Yang, Auteur ; Zhiwei Li, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] analyse des risques [Termes descripteurs IGN] Chine [Termes descripteurs IGN] déformation de la croute terrestre [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] données polarimétriques [Termes descripteurs IGN] échantillonnage de données [Termes descripteurs IGN] image ALOS-PALSAR [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] mine de charbon [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] surveillance géologique Résumé : (auteur) Interferometric synthetic aperture radar (InSAR) technology can be used to observe high spatial resolution one-dimensional (1-D) deformation along the line-of-sight direction from a single-track synthetic aperture radar (SAR) dataset. With the aid of multi-track InSAR data or a prior model, InSAR can be extended to infer 3-D deformation information, but the temporal resolution is generally limited. This paper presents an InSAR-based method to retrieve high spatio-temporal resolution 3-D displacements over mining areas (hereafter referred to as the MTI-based method). The core idea of the proposed method is to enhance the temporal resolution of the time-series 3-D displacement estimates by fusing multi-track InSAR observations and a prior model. Firstly, we retrieve high spatial resolution 3-D mining displacements from single-track InSAR 1-D deformation observations, with the assistance of the prior deformation model. By applying this approach to multi-track InSAR data over the same area, we obtain much denser 3-D mining displacement samples in time than those derived from a single-track InSAR dataset. Secondly, we propose a generalized weighted least-squares method to integrate the denser 3-D displacement samples, to solve the high temporal resolution 3-D mining displacements, in which the rank deficiency needs to be tackled. Finally, time-series 3-D mining displacements at the chronological dates of all the available multi-track SAR images are estimated. The Yungang coal mining area of China was selected to test the proposed method using two adjacent-track ALOS PALSAR-1 datasets. Compared with the single-track InSAR-derived results, the proposed method not only significantly improves the temporal resolution of the monitoring results by 42.6%, obtaining more detailed 3-D displacements, but it also provides important data support for understanding and modeling the distinctive kinematics of mining deformation and assessing mining-related geohazards. What is more, the core idea of the proposed method will be beneficial to high spatio-temporal resolution 3-D deformation estimation in other geophysical processes. Numéro de notice : A2020-239 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01374-8 date de publication en ligne : 23/04/2020 En ligne : https://doi.org/10.1007/s00190-020-01374-8 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94992 [article]

Size-class structure of the forests of Finland during 1921–2013: a recovery from centuries of exploitation, guided by forest policies / Helena M. Henttonen in European Journal of Forest Research, vol 139 n° 2 (April 2020)  

Public [article]  inEuropean Journal of Forest Research > vol 139 n° 2 (April 2020) . - pp 279 – 293 Titre : Size-class structure of the forests of Finland during 1921–2013: a recovery from centuries of exploitation, guided by forest policies Type de document : Article/Communication Auteurs : Helena M. Henttonen, Auteur ; Pekka Nöjd, Auteur ; Susanne Suvanto, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 279 – 293 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] brûlis [Termes descripteurs IGN] densité de la végétation [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] échantillonnage de données [Termes descripteurs IGN] Finlande [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] inventaire forestier étranger (données) [Termes descripteurs IGN] paturage [Termes descripteurs IGN] peuplement forestier [Termes descripteurs IGN] Picea abies [Termes descripteurs IGN] Pinus sylvestris [Termes descripteurs IGN] politique forestière [Termes descripteurs IGN] sylviculture [Termes descripteurs IGN] utilisation du sol [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Frequency distributions of tree diameters are a powerful tool for analyzing changes of tree populations in large areas. We analyzed the densities and mean volume estimates of trees in different size classes for the Finnish forests over the time-span of the National Forest Inventories (1921–2013). The results display a general increase in trees in all size classes, species group and geographical area, mainly after the 1970s. The densities of medium- and large-sized conifers showed large increases in the southern boreal subzone, spruces even more than pines. Small- to medium-sized pines have increased in the middle and northern boreal subzones. The shifts in growing stock are related to changing land use, resulting from the development of the society. The low quantities of both growing stock and large trees during the 1920s reflect a poor initial state of forests. Several land use forms of the former agriculture-based society were detrimental to forests, including slash and burn agriculture, cattle grazing and tar production. The pressure from alternative land use forms was stronger in southern Finland, where the population density (people per km2) is much higher. Between 1971 and 2013, the changes in size-class structure can be attributed mainly to intensified silviculture boosted by actions of the Finnish governments, including both legislation and financial support for management activities. Not only the development of growing stock has exceeded expectations, but the increase has also concentrated in the economically valuable trees in the large size classes. Numéro de notice : A2020-344 Thématique : FORET Nature : Article DOI : 10.1007/s10342-019-01241-y date de publication en ligne : 27/11/2019 En ligne : https://doi.org/10.1007/s10342-019-01241-y Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95224 [article]

Assessment of the Baspa basin glaciers mass budget using different remote sensing methods and modeling techniques / Vinay Kumar Gaddam in Geocarto international, vol 35 n° 3 ([01/03/2020])  

Public [article]  inGeocarto international > vol 35 n° 3 [01/03/2020] . - pp 296 - 316 Titre : Assessment of the Baspa basin glaciers mass budget using different remote sensing methods and modeling techniques Type de document : Article/Communication Auteurs : Vinay Kumar Gaddam, Auteur ; Anil V. Kulkarni, Auteur ; Anil Kumar Gupta, Auteur Année de publication : 2020 Article en page(s) : pp 296 - 316 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] bande C [Termes descripteurs IGN] bilan de masse [Termes descripteurs IGN] cheminement géodésique [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] échantillonnage de données [Termes descripteurs IGN] fonte des glaces [Termes descripteurs IGN] glacier [Termes descripteurs IGN] Himalaya [Termes descripteurs IGN] MNS ASTER [Termes descripteurs IGN] MNS SRTM [Termes descripteurs IGN] précipitation [Termes descripteurs IGN] température Résumé : (auteur) Glacial melt water is the key source for various socio-industrial and domestic activities in the Himalayas. Several recent studies suggest that glaciers are experiencing rapid melt. The glaciers health can be best assessed by mass balance. However, the mass balance investigations using in-situ methods for a large sample of glaciers are highly difficult in the Himalaya. Hence, remote sensing methods and modelling techniques are preferred. However, there is a lack of information on uncertainties associated with these methods in assessing the regional scale mass balance. Hence, these methods are applied to evaluate the regional scale mass budget of Baspa basin, Western Himalaya between 2000 and 2011. The total mass loss estimated using geodetic method amounts to −0.49 ± 0.1 gigatons, temperature index method to −0.43 ± 0.012 gigatons and AAR method to −0.36 ± 0.1 gigatons. Furthermore, this study highlights the limitations of these methods in mass loss evaluation in data scarce Himalayan regions. Numéro de notice : A2020-055 Nature : Article DOI : 10.1080/10106049.2018.1516247 date de publication en ligne : 06/01/2020 En ligne : https://doi.org/10.1080/10106049.2018.1516247 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94568 [article]

Can mixed pine forests conserve understory richness by improving the establishment of understory species typical of native oak forests? / Daphne Lopez-Marcos in Annals of Forest Science [en ligne], Vol 77 n° 1 (March 2020)  

Public [article]  inAnnals of Forest Science [en ligne] > Vol 77 n° 1 (March 2020) . - 13 p. Titre : Can mixed pine forests conserve understory richness by improving the establishment of understory species typical of native oak forests? Type de document : Article/Communication Auteurs : Daphne Lopez-Marcos, Auteur ; Maria-Belen Turrion, Auteur ; Felipe Bravo, Auteur ; Carolina Martinez-Ruiz, Auteur Année de publication : 2020 Article en page(s) : 13 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] échantillonnage de données [Termes descripteurs IGN] Espagne [Termes descripteurs IGN] étage de végétation [Termes descripteurs IGN] forêt de zone humide [Termes descripteurs IGN] forêt tempérée [Termes descripteurs IGN] parcelle forestière [Termes descripteurs IGN] peuplement mélangé [Termes descripteurs IGN] Pinus pinaster [Termes descripteurs IGN] Pinus sylvestris [Termes descripteurs IGN] quercus pyrenaica [Termes descripteurs IGN] régénération (sylviculture) [Termes descripteurs IGN] sous-étage [Vedettes matières IGN] Sylviculture Résumé : (auteur) Key message: A positive effect of mixed pine forests ( Pinus sylvestris L. and Pinus pinaster Ait.) on the understory richness and tree regeneration was observed with respect to monospecific stands. Understory species typical of the native Pyrenean oak forests in the Iberian Peninsula contribute to maintaining high understory richness in such mixed pine forests. Context: The influence of stands characteristics on the understory in mixtures that combine coniferous tree species of the same genus deserves more study since they are frequent in Spain. Aims: To assess the effect of mixed versus monospecific stands of Pinus sylvestris L. and Pinus pinaster Ait. on the main tree species regeneration and understory species composition. Methods: Tree regeneration and understory species composition were inventoried in eighteen forest plots (6 triplets) in North-Central Spain. Each triplet consisted of two plots dominated either by Scots pine or Maritime pine and one mixed plot that contained both species. Results: The basal area (%) of both Pinus species was the only characteristic of the stands that significantly influenced the understory composition and tree regeneration. Characteristic species of humid and temperate zones, including P. sylvestris regeneration, dominated in Scots pine stands, and typical species of well-drained Mediterranean areas, including P. pinaster regeneration, dominated in Maritime pine stands. In mixed stands, the highest regeneration of the native Pyrenean oak with respect to monospecific stands was accompanied by understory species typical of native oak forests that share the same regeneration niche. Conclusion: Mixed pine forests allow the development of understory species better than monospecific forests. Numéro de notice : A2020-067 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-0919-7 date de publication en ligne : 04/02/2020 En ligne : https://doi.org/10.1007/s13595-020-0919-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94579 [article]

Transferring deep learning models for cloud detection between Landsat-8 and Proba-V / Gonzalo Mateo-García in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 160 (February 2020) . - pp 1 - 17 Titre : Transferring deep learning models for cloud detection between Landsat-8 and Proba-V Type de document : Article/Communication Auteurs : Gonzalo Mateo-García, Auteur ; Valero Laparra, Auteur ; Dan López-Puigdollers, Auteur ; Luis Gómez-Chova, Auteur Année de publication : 2020 Article en page(s) : pp 1 - 17 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] apprentissage par transformation [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] conversion de données [Termes descripteurs IGN] détection des nuages [Termes descripteurs IGN] échantillonnage de données [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image PROBA [Termes descripteurs IGN] jeu de données [Termes descripteurs IGN] masque [Termes descripteurs IGN] réseau neuronal convolutif [Termes descripteurs IGN] seuillage de points Résumé : (Auteur) Accurate cloud detection algorithms are mandatory to analyze the large streams of data coming from the different optical Earth observation satellites. Deep learning (DL) based cloud detection schemes provide very accurate cloud detection models. However, training these models for a given sensor requires large datasets of manually labeled samples, which are very costly or even impossible to create when the satellite has not been launched yet. In this work, we present an approach that exploits manually labeled datasets from one satellite to train deep learning models for cloud detection that can be applied (or transferred) to other satellites. We take into account the physical properties of the acquired signals and propose a simple transfer learning approach using Landsat-8 and Proba-V sensors, whose images have different but similar spatial and spectral characteristics. Three types of experiments are conducted to demonstrate that transfer learning can work in both directions: (a) from Landsat-8 to Proba-V, where we show that models trained only with Landsat-8 data produce cloud masks 5 points more accurate than the current operational Proba-V cloud masking method, (b) from Proba-V to Landsat-8, where models that use only Proba-V data for training have an accuracy similar to the operational FMask in the publicly available Biome dataset (87.79–89.77% vs 88.48%), and (c) jointly from Proba-V and Landsat-8 to Proba-V, where we demonstrate that using jointly both data sources the accuracy increases 1–10 points when few Proba-V labeled images are available. These results highlight that, taking advantage of existing publicly available cloud masking labeled datasets, we can create accurate deep learning based cloud detection models for new satellites, but without the burden of collecting and labeling a large dataset of images. Numéro de notice : A2020-043 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.11.024 date de publication en ligne : 10/12/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.11.024 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94522 [article]

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