Centre de documentation
scientifique

Application of a graph convolutional network with visual and semantic features to classify urban scenes / Yongyang Xu in International journal of geographical information science IJGIS, vol 36 n° 10 (October 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 10 (October 2022) . - pp 2009-2034 Titre : Application of a graph convolutional network with visual and semantic features to classify urban scenes Type de document : Article/Communication Auteurs : Yongyang Xu, Auteur ; Shuai Jin, Auteur ; Zhanlong Chen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2009-2034 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] extraction de traits caractéristiques [Termes IGN] matrice de co-occurrence [Termes IGN] OpenStreetMap [Termes IGN] Pékin (Chine) [Termes IGN] point d'intérêt [Termes IGN] relation spatiale [Termes IGN] réseau neuronal de graphes [Termes IGN] réseau routier [Termes IGN] scène urbaine Résumé : (auteur) Urban scenes consist of visual and semantic features and exhibit spatial relationships among land-use types (e.g. industrial areas are far away from the residential zones). This study applied a graph convolutional network with neighborhood information (henceforth, named the neighbour supporting graph convolutional neural network), to learn spatial relationships for urban scene classification. Furthermore, a co-occurrence analysis with visual and semantic features proceeded to improve the accuracy of urban scene classification. We tested the proposed method with the fifth ring road of Beijing with an overall classification accuracy of 0.827 and a Kappa coefficient of 0.769. In comparison with other methods, such as support vector machine, random forest, and general graph convolutional network, the case study showed that the proposed method improved about 10% in urban scene classification. Numéro de notice : A2022-740 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2048834 Date de publication en ligne : 10/03/2022 En ligne : https://doi.org/10.1080/13658816.2022.2048834 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101717 [article]

Assessing logging residues availability for energy production by using forest management plans data and geographic information system (GIS) / Luca Nonini in European Journal of Forest Research, vol 141 n° 5 (October 2022)  

Public [article]  inEuropean Journal of Forest Research > vol 141 n° 5 (October 2022) . - pp 959 - 977 Titre : Assessing logging residues availability for energy production by using forest management plans data and geographic information system (GIS) Type de document : Article/Communication Auteurs : Luca Nonini, Auteur ; Calogero Schillaci, Auteur ; Marco Fiala, Auteur Année de publication : 2022 Article en page(s) : pp 959 - 977 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] données localisées [Termes IGN] estimation statistique [Termes IGN] exploitation forestière [Termes IGN] gestion forestière [Termes IGN] Italie [Termes IGN] planification [Termes IGN] système d'information géographique Résumé : (auteur) The aim of the work was to quantify the mass of logging residues (branches and tops; t yr−1 dry matter, DM) for energy generation starting from Forest Management Plans (FMP) data. The methodology was applied to public stands of an Italian district (area: 3.60 × 104 ha; period: 2009–2018). Compared to the previous preliminary analysis, the potentially available residues were computed considering forest accessibility and road traversability, by combining FMPs data with a geographic information system (GIS). New issues that were assessed here were: (i) representation of stands consisting of multiple disconnected parts; (ii) calculation of producible residues by using different values of biomass expansion factors (Scenario 1, S1; Scenario 2, S2). The potentially available residues computed for the analyzed period were used to quantify the current sustainable supply. Then, the potentially generated heat (thermal energy, TE; GJ yr−1) and electricity (EE; GJ yr−1), and the potentially avoided CO2 emissions into the atmosphere (EM; t yr−1 CO2) related to the final combustion process were computed by assuming that the current supply of residues was used as woodchips in a local centralized heating plant currently operating. For both S1 and S2, the large difference between the potentially producible and the potentially available residues demonstrated that geodata are essential for reliable estimations. Moreover, as the required information for the GIS analysis can be easily found in databases made available by forestry authorities, the proposed approach can be applied also to other areas; this could be helpful to support local decision-makers in defining sustainable practices for residues recovery. Numéro de notice : A2022-760 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.1007/s10342-022-01484-2 Date de publication en ligne : 22/08/2022 En ligne : https://doi.org/10.1007/s10342-022-01484-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101772 [article]

Augmented reality for scene text recognition, visualization and reading to assist visually impaired people / Imene Ouali in Procedia Computer Science, vol 207 (2022)  

Public [article]  inProcedia Computer Science > vol 207 (2022) . - pp 158 - 167 Titre : Augmented reality for scene text recognition, visualization and reading to assist visually impaired people Type de document : Article/Communication Auteurs : Imene Ouali, Auteur ; Mohamed Ben Halima, Auteur ; Ali Wali, Auteur Année de publication : 2022 Article en page(s) : pp 158 - 167 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] enquête [Termes IGN] personne malvoyante [Termes IGN] réalité augmentée [Termes IGN] reconnaissance de caractères [Termes IGN] signalisation routière [Termes IGN] visualisation Résumé : (auteur) Reading traffic signs while driving a car for visually impaired people and people with visual problems is a very difficult task for them. This task is encountered every day, sometimes incorrect reading of traffic signs can lead to very serious results. In particular, the Arabic language is very difficult, making recognizing and viewing Arabic text a difficult task. In this context, we are looking for an effective solution to remove errors and results that can sometimes end someone's life. This article aims to correctly read traffic signs with Arabic text using augmented reality technology. Our system is composed of three modules. The first is text detection and recognition. The second is Text visualization. The third is Text to speech methods conversion. With this system, the user can have two different results. The first result is visual with much-improved text and enhancement. The second result is sound, he can hear the text aloud. This system is very applicable and effective for daily life. To assess the effectiveness of our work, we offer a survey to a group of visually impaired people to give their opinion on the use of our application. The results have been good for most people. Numéro de notice : A2023-010 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Article DOI : 10.1016/j.procs.2022.09.048 Date de publication en ligne : 19/10/2022 En ligne : https://doi.org/10.1016/j.procs.2022.09.048 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102119 [article]

Canopy self-replacement in Pinus sylvestris rear-edge populations following drought-induced die-off and mortality / Jordi Margalef- Marrase in Forest ecology and management, vol 521 (October-1 2022)  

Public [article]  inForest ecology and management > vol 521 (October-1 2022) . - n° 120427 Titre : Canopy self-replacement in Pinus sylvestris rear-edge populations following drought-induced die-off and mortality Type de document : Article/Communication Auteurs : Jordi Margalef- Marrase, Auteur ; Guillem Bagaria, Auteur ; Francisco Lloret, Auteur Année de publication : 2022 Article en page(s) : n° 120427 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] adaptation (biologie) [Termes IGN] analyse de données [Termes IGN] canopée [Termes IGN] Catalogne (Espagne) [Termes IGN] changement climatique [Termes IGN] classification et arbre de régression [Termes IGN] croissance des arbres [Termes IGN] dépérissement [Termes IGN] mortalité [Termes IGN] Pinus sylvestris [Termes IGN] Quercus pubescens [Termes IGN] sécheresse [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) In recent years, Pinus sylvestris die-off and mortality events have occurred across all its range of distribution, usually associated with recurrent droughts induced by climate change. A shift in canopy dominance towards other better adapted co-existing species can be expected, especially in populations located close to their climatic tolerance limits. Herein, we tested, along a local elevational gradient, whether canopy opening resulting from die-off and mortality favours the growth of a non-dominant co-existing tree species (Quercus pubescens) established in the sub-canopy, in comparison to P. sylvestris sub-canopy trees. We also tested whether the growth of both species is associated with local climatic suitability for these species (extracted from SDMs) or, alternatively, with direct measures of micro-climatic variables. Finally, the effect on tree growth of other micro-local factors such as competition, canopy closure and micro-topography was also tested. Sub-canopy tree growth was enhanced overall by canopy opening resulting from P. sylvestris canopy die-off, but this response was stronger in P. sylvestris trees, reinforcing the self-replacement of this species after die-off. This higher growth rate is related to modifications in the micro-local climate (higher temperatures in the wettest quarter). Conversely, Q. pubescens is less sensitive to micro-local climate conditions but it can grow faster than P. sylvestris on stands with no canopy die-off or mortality. In contrast, climatic suitability extracted from SDMs was negatively related to sub-canopy P. sylvestris growth and had no effect on Q. pubescens. These contrasting results support observations at plot scale that P. sylvestris self-replacement is better explained by local environmental conditions than by values of climatic suitability obtained from regional-scale data-sets. Nevertheless, these climatic suitability measures remain consistent with the overall pattern of low seedling recruitment observed in previous works at the rear edge of species' distribution. This study reveals that short-term shifts in species dominance at a local scale will not necessarily occur in the studied P. sylvestris forests following die-off. This finding endorses the notion that micro-local environment and species traits (i.e., light and temperature tolerance, life-history strategies) modulate the capacity for resilience in rear-edge populations that would probably be prone to collapse otherwise. Numéro de notice : A2022-709 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : https://doi.org/10.1016/j.foreco.2022.120427 Date de publication en ligne : 21/07/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120427 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101585 [article]

Challenges and limitations of earthquake-induced building damage mapping techniques using remote sensing images : A systematic review / Sahar S. Matin in Geocarto international, Vol 37 n° 21 ([01/10/2022])  

Public [article]  inGeocarto international > Vol 37 n° 21 [01/10/2022] . - pp 6186 - 6212 Titre : Challenges and limitations of earthquake-induced building damage mapping techniques using remote sensing images : A systematic review Type de document : Article/Communication Auteurs : Sahar S. Matin, Auteur ; Biswajeet Pradhan, Auteur Année de publication : 2022 Article en page(s) : pp 6186 - 6212 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage profond [Termes IGN] cartographie thématique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] déformation d'édifice [Termes IGN] détection de changement [Termes IGN] dommage matériel [Termes IGN] données lidar [Termes IGN] image optique [Termes IGN] image radar moirée [Termes IGN] secours d'urgence [Termes IGN] séisme Résumé : (auteur) Assessing the extent and level of building damages is crucial to support post-earthquake rescue and relief activities. There is a large body of literature proposing novel frameworks for automating earthquake-induced building damage mapping using high-resolution remote sensing images. Yet, its deployment in real-world scenarios is largely limited to the manual interpretation of images. Although manual interpretation is costly and labor-intensive, it is preferred over automatic and semi-automatic building damage mapping frameworks such as machine learning and deep learning because of its reliability. Therefore, this review paper explores various automatic and semi-automatic building damage mapping techniques with a quest to understand the pros and cons of different methodologies to narrow the gap between research and practice. Further, the research gaps and opportunities are identified for the future development of real-world scenarios earthquake-induced building damage mapping. This review can serve as a guideline for researchers, decision-makers, and practitioners in the emergency management service domain. Numéro de notice : A2022-719 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1933213 Date de publication en ligne : 07/06/2021 En ligne : https://doi.org/10.1080/10106049.2021.1933213 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101651 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2022211	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Challenging the link between functional and spectral diversity with radiative transfer modeling and data / Javier Pacheco-Labradora in Remote sensing of environment, vol 280 (October 2022)  

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Comparison of layer-stacking and Dempster-Shafer theory-based methods using Sentinel-1 and Sentinel-2 data fusion in urban land cover mapping / Dang Hung Bui in Geo-spatial Information Science, vol 25 n° 3 (October 2022)  

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Deep learning high resolution burned area mapping by transfer learning from Landsat-8 to PlanetScope / V.S. Martins in Remote sensing of environment, vol 280 (October 2022)  

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Detecting overmature forests with airborne laser scanning (ALS) / Marc Fuhr in Remote sensing in ecology and conservation, vol 8 n° 5 (October 2022)  

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A determination of the motion based on GNSS observations between 2000 and 2021 using the IGS points in the polar regions / Atinç Pirti in Geodesy and cartography, vol 48 n° 3 (October 2022)  

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Developing a GIS-based rough fuzzy set granulation model to handle spatial uncertainty for hydrocarbon structure classification, case study: Fars domain, Iran / Sahand Seraj in Geo-spatial Information Science, vol 25 n° 3 (October 2022)  

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Estimating urban functional distributions with semantics preserved POI embedding / Weiming Huang in International journal of geographical information science IJGIS, vol 36 n° 10 (October 2022)  

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Estimation of ionospheric total electron content using GNSS observations derived from a smartphone / Li Xu in GPS solutions, vol 26 n° 4 (October 2022)  

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Evaluation of Landsat 8 image pansharpening in estimating soil organic matter using multiple linear regression and artificial neural networks / Abdelkrim Bouasria in Geo-spatial Information Science, vol 25 n° 3 (October 2022)  

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GNSS best integer equivariant estimation combining with integer least squares estimation: an integrated ambiguity resolution method with optimal integer aperture test / Liye Ma in GPS solutions, vol 26 n° 4 (October 2022)  

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Identify urban building functions with multisource data: a case study in Guangzhou, China / Yingbin Deng in International journal of geographical information science IJGIS, vol 36 n° 10 (October 2022)  

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Incremental road network update method with trajectory data and UAV remote sensing imagery / Jianxin Qin in ISPRS International journal of geo-information, vol 11 n° 10 (October 2022)  

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Investigating the efficiency of deep learning methods in estimating GPS geodetic velocity / Omid Memarian Sorkhabi in Earth and space science, vol 9 n° 10 (October 2022)  

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Investigation of recognition and classification of forest fires based on fusion color and textural features of images / Cong Li in Forests, vol 13 n° 10 (October 2022)  

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Machine learning and natural language processing of social media data for event detection in smart cities / Andrei Hodorog in Sustainable Cities and Society, vol 85 (October 2022)  

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Modelling and prediction of GNSS time series using GBDT, LSTM and SVM machine learning approaches / Wenzong Gao in Journal of geodesy, vol 96 n° 10 (October 2022)  

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Monitoring spatiotemporal soil moisture changes in the subsurface of forest sites using electrical resistivity tomography (ERT) / Julian Fäth in Journal of Forestry Research, vol 33 n° 5 (October 2022)  

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Multi‑constellation GNSS interferometric reflectometry for the correction of long-term snow height retrieval on sloping topography / Wei Zhou in GPS solutions, vol 26 n° 4 (October 2022)  

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Multisource forest inventories: A model-based approach using k-NN to reconcile forest attributes statistics and map products / Ankit Sagar in ISPRS Journal of photogrammetry and remote sensing, vol 192 (October 2022)  

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Novel algorithm based on geometric characteristics for tree branch skeleton extraction from LiDAR point cloud / Jie Yang in Forests, vol 13 n° 10 (October 2022)  

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