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Monitoring coastal vulnerability by using DEMs based on UAV spatial data / Antonio Minervino Amodio in ISPRS International journal of geo-information, vol 11 n° 3 (March 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 3 (March 2022) . - n° 155 Titre : Monitoring coastal vulnerability by using DEMs based on UAV spatial data Type de document : Article/Communication Auteurs : Antonio Minervino Amodio, Auteur ; Gianluigi Di Paola, Auteur ; Carmen Maria Rosskopf, Auteur Année de publication : 2022 Article en page(s) : n° 155 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] Adriatique, mer [Termes IGN] détection de changement [Termes IGN] érosion côtière [Termes IGN] géoréférencement [Termes IGN] image captée par drone [Termes IGN] Italie [Termes IGN] littoral méditerranéen [Termes IGN] modèle numérique de surface [Termes IGN] orthophotographie [Termes IGN] point d'appui [Termes IGN] structure-from-motion [Termes IGN] surveillance du littoral [Termes IGN] trait de côte [Termes IGN] vulnérabilité Résumé : (auteur) The use of Unmanned Aerial Vehicles (UAVs) represents a rather innovative, quick, and low-cost methodological approach offering applications in several fields of investigation. The present study illustrates the developed method using Digital Elevation Models (DEMs) based on UAV-derived data for evaluating short-term morphological-topographic changes of the beach system and related implications for coastal vulnerability assessment. UAV surveys were performed during the summers of 2019 and 2020 along a beach stretch affected by erosion, located along the central Adriatic coast. Acquired high-resolution aerial photos were used to generate large-scale DEMs as well as orthophotos of the beach using the Structure from Motion (SfM) image processing tool. Comparison of the generated 2019 and 2020 DEMs highlighted significant morphological changes and a sediment volume loss of about 780 m3 within a surface area of about 4400 m2. Based on 20 m spaced beach profiles derived from the DEMs, a coastal vulnerability assessment was performed using the CVA approach that highlighted some significant variations in the CVA index between 2019 and 2020. Results evidence that UAV surveys provide high-resolution topographic data, suitable for specific beach monitoring activities and the updating of some parameters that enter in the CVA model contributing to its correct application. Numéro de notice : A2022-185 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11030155 Date de publication en ligne : 22/02/2022 En ligne : https://doi.org/10.3390/ijgi11030155 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99895 [article]

Observational constraint on the climate sensitivity to atmospheric CO2 concentrations changes derived from the 1971-2017 global energy budget / Jonathan Chenal in Journal of climate, vol 2022 ([01/03/2022])  

Public [article]  inJournal of climate > vol 2022 [01/03/2022] . - 49 p. Titre : Observational constraint on the climate sensitivity to atmospheric CO2 concentrations changes derived from the 1971-2017 global energy budget Type de document : Article/Communication Auteurs : Jonathan Chenal , Auteur ; Benoit Meyssignac, Auteur ; Aurélien Ribes, Auteur ; Robin Guillaume-Castel, Auteur Année de publication : 2022 Article en page(s) : 49 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Environnement [Termes IGN] analyse diachronique [Termes IGN] atmosphère terrestre [Termes IGN] changement climatique [Termes IGN] dioxyde de carbone [Termes IGN] énergie [Termes IGN] gaz à effet de serre [Termes IGN] incertitude des données [Termes IGN] régression Résumé : (auteur) The estimate of the historical effective climate sensitivity (histeffCS) is revisited with updated historical observations of the global energy budget in order to derive an observational constraint on the effective sensitivity of climate to CO2 (CO2effCS). A regression method based on observations of the energy budget over 1971-2017 is used to estimate the histeffCS (4.34 [2.17;22.83] K, median and 5-95% range). Then, climate model simulations are used to evaluate the distance between the histeffCS and the CO2effCS. The observational estimate of the histeffCS and the distance between the histeffCS and the CO2effCS are combined to derive an observational constraint on CO2effCS of 5.46 [2.40;35.61] K. The main sources of uncertainty in the CO2effCS estimate comes from the uncertainty in aerosol forcing and in the top of the atmosphere energy imbalance. Further uncertainty arises from the pattern effect correction estimated from climate models. There is confidence in the lower end of the 5-95% range derived from our method as it relies only on reliable recent data and it makes full use of the observational record since 1971. This important result suggests that observations of the global energy budget since 1971 are poorly consistent with climate sensitivity to CO2 below 2.4 K. Unfortunately, the upper end of the 5-95% range derived from the regression method is above 30 K. It means that the observational constraint derived from observations of the global energy budget since 1971 is too weak (i.e. the uncertainty is too large) to provide any relevant information on the credibility of high CO2effCS. Numéro de notice : A2022-322 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article DOI : 10.1175/JCLI-D-21-0565.1 Date de publication en ligne : 14/03/2022 En ligne : https://doi.org/10.1175/JCLI-D-21-0565.1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100149 [article]

Simulation d'ouragans et de collectes de déchets sur QGIS pour l'amélioration de la collecte des déchets post-ouragan / Quy Thy Truong in Cartes & Géomatique, n° 247-248 (mars-juin 2022)

Public [article]  inCartes & Géomatique > n° 247-248 (mars-juin 2022) . - pp 61 - 63 Titre : Simulation d'ouragans et de collectes de déchets sur QGIS pour l'amélioration de la collecte des déchets post-ouragan Type de document : Article/Communication Auteurs : Quy Thy Truong , Auteur ; Anne Ruas , Auteur Année de publication : 2022 Conférence : ICC 2021, 30th ICA international cartographic conference 14/12/2021 18/12/2021 Florence Italie Article en page(s) : pp 61 - 63 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes IGN] catastrophe naturelle [Termes IGN] collecte des déchets [Termes IGN] dommage matériel [Termes IGN] gestion de crise [Termes IGN] implémentation (informatique) [Termes IGN] module d'extension [Termes IGN] prototype [Termes IGN] QGIS [Termes IGN] Saint-Martin, île de [Termes IGN] simulation spatiale [Termes IGN] stockage [Termes IGN] tempête Résumé : (Auteur) [Contexte] Au cours des dernières décennies, des évènements naturels catastrophiques tels que des tempêtes et des ouragans ont touché des millions de personnes dans le Monde : environ 33 millions de personnes sont touchées chaque année entre 2007 et 2016 (Bellow et Wallemacq, 2018). Par exemple, l'ouragan Katrina (Etas-Unis, 2015) a causé des dégâts catastrophiques du centre de la Floride à l'est du Texas, au moins 1836 personnes sont mortes et le total des dommages matériels a été estimé à 125 milliards de dollars. Par ailleurs, le changement climatique est susceptible d'augmenter la fréquence des catégories d'ouragans les plus intenses ainsi que le niveau de la mer, entraînant des ondes de tempête plus destructrices lorsque des ouragans se produisent (GIEC, 2013). Les ouragans génèrent de grandes quantités de déchets directement liés aux impacts induits (Brown et al., 2011). La rapidité de collecte et de tri des déchets est essentielle car non seulement les déchets bloquent et ralentissent l'activité humaine mais ils génèrent aussi des pollutions. La gestion de ces déchets est donc un enjeu majeur dans la gestion de crise post-ouragan. L'ouragan Irma, qui a frappé les Caraïbes au début de septembre 2017, en particulier les îles de Saint-Martin et Saint-Barthélémy, est un exemple frappant de ce problème. Dans cet article nous présentons un système d'information pour améliorer la collecte des déchets post-ouragan aux Antilles françaises. Ces travaux sont faits dans le cadre du projet de recherche DéPOs financé par l'ANR. Numéro de notice : A2022-676 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101891 [article]

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Unexpected negative effect of available water capacity detected on recent conifer forest growth trends across wide environmental gradients / Clémentine Ols in Ecosystems, vol 25 n° 2 (March 2022)  

Public [article]  inEcosystems > vol 25 n° 2 (March 2022) . - pp 404 - 421 Titre : Unexpected negative effect of available water capacity detected on recent conifer forest growth trends across wide environmental gradients Type de document : Article/Communication Auteurs : Clémentine Ols , Auteur ; Thomas Gschwantner, Auteur ; Klemens Schadauer, Auteur ; Jean-Daniel Bontemps , Auteur Année de publication : 2022 Projets : ARBRE / AgroParisTech (2007 -), LUE / Université de Lorraine Article en page(s) : pp 404 - 421 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba [Termes IGN] analyse diachronique [Termes IGN] Autriche [Termes IGN] cerne [Termes IGN] changement climatique [Termes IGN] croissance des arbres [Termes IGN] gradient d'altitude [Termes IGN] hétérogénéité environnementale [Termes IGN] inventaire forestier étranger (données) [Termes IGN] inventaire forestier national (données France) [Termes IGN] Larix decidua [Termes IGN] modèle de croissance végétale [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] ressources en eau [Termes IGN] structure d'un peuplement forestier [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) National Forest Inventories (NFIs) perform systematic forest surveys across space and time. They are hence powerful tools to understand climate controls on forest growth at wide geographical scales and account for the effects of local abiotic and biotic interactions. To investigate the effects of climate change upon growth dynamics of four major European conifer species along elevation and continentality gradients, we herein provide an original harmonization of the French and Austrian NFI datasets. The growth of Norway spruce, Scots pine, silver fir and European larch over the 1996–2016 period was studied in pure and even-aged plots across different ecological regions. We derived climate-driven growth trends from > 65, 000 radial increment series filtered out from major biotic and abiotic influences using statistical modeling. We further identified primary environmental drivers of conifer growth by regressing growth trends against regionally aggregated biotic and abiotic forest attributes. Negative growth trends were observed in continental regions undergoing the most rapid warming and thermal amplitude contraction over the study period. Negative trends were also associated with lower forest structural heterogeneity and, surprisingly, with greater available water capacity. Remarkably, we observed these associations both at the inter- and intra-species levels, suggesting the universality of these primary growth determinants. Our study shows that harmonized NFI data at the transnational level provide reliable information on climate–growth interactions. Here, greater forest structural complexity and greater water resource limitation were highlighted as drivers of greater forest resilience to climate change at large-scale. This result forms crucial bases to implementing climate-smart forest management. Numéro de notice : A2022-023 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10021-021-00663-3 En ligne : https://doi.org/10.1007/s10021-021-00663-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98116 [article]

Using street view images to identify road noise barriers with ensemble classification model and geospatial analysis / Kai Zhang in Sustainable Cities and Society, vol 78 (March 2022)  

Public [article]  inSustainable Cities and Society > vol 78 (March 2022) . - n° 103598 Titre : Using street view images to identify road noise barriers with ensemble classification model and geospatial analysis Type de document : Article/Communication Auteurs : Kai Zhang, Auteur ; Zhen Qian, Auteur ; Yue Yang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 103598 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] apprentissage profond [Termes IGN] cartographie du bruit [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] distribution spatiale [Termes IGN] image Streetview [Termes IGN] lutte contre le bruit [Termes IGN] milieu urbain [Termes IGN] OpenStreetMap [Termes IGN] planification urbaine [Termes IGN] pollution acoustique [Termes IGN] trafic routier [Termes IGN] ville durable Résumé : (auteur) Road noise barriers (RNBs) are important urban infrastructures to relieve the harm of traffic noise pollution for citizens. Therefore, obtaining the spatial distribution characteristics of RNBs, such as precise positions and mileage, can be of great help for obtaining more accurate urban noise maps and assessing the quality of the urban living environment for sustainable urban development. However, an effective and efficient method for identifying RNBs and acquiring their attributes in large areas is scarce. This study constructs an ensemble classification model (ECM) to automatically identify RNBs at the city level based on Baidu Street View (BSV). Firstly, the bootstrap sampling method is proposed to build a street view image-based train set, where the effect of imbalanced categories of samples was reduced by adding confusing negative samples. Secondly, two state-of-the-art deep learning models, ResNet and DenseNet, are ensembled to construct an ECM based on the bagging framework. Finally, a post-processing method has been proposed based on geospatial analysis to eliminate street view images (SVIs) that are misclassified as RNBs. This study takes Suzhou, China as the study area to validate the proposed method. The model achieved an accuracy and F1-score of 0.98 and 0.90, respectively. The total mileage of the RNBs in Suzhou was 178,919 m. The results demonstrated the performance of the proposed RNBs identification framework. The significance of obtaining RNBs attributes for accelerating sustainable urban development has been demonstrated through the case of photovoltaic noise barriers (PVNBs). Numéro de notice : A2022-241 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1016/j.scs.2021.103598 Date de publication en ligne : 20/12/2021 En ligne : https://doi.org/10.1016/j.scs.2021.103598 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100167 [article]

Aboveground biomass estimation of an agro-pastoral ecology in semi-arid Bundelkhand region of India from Landsat data: a comparison of support vector machine and traditional regression models / Dibyendu Deb in Geocarto international, vol 37 n° 4 ([15/02/2022])  

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Multi-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques / Saman Javadi in Geocarto international, vol 37 n° 4 ([15/02/2022])  

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A national fuel type mapping method improvement using sentinel-2 satellite data / Alexandra Stefanidou in Geocarto international, vol 37 n° 4 ([15/02/2022])  

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Pourquoi la forêt française a besoin d’un traitement de fond / Guillaume Decocq in The Conversation France, vol 2022 ([10/02/2022])  

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An open science and open data approach for the statistically robust estimation of forest disturbance areas / Saverio Francini in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)  

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Analysis of spatio-temporal changes in forest biomass in China / Weiyi Xu in Journal of Forestry Research, vol 33 n° 1 (February 2022)  

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Assessment and mapping soil water erosion using RUSLE approach and GIS tools: Case of Oued el-Hai watershed, Aurès West, Northeastern of Algeria / Aida Bensekhria in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)  

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Débris spatiaux, l’inquiétante prolifération / Laurent Polidori in Géomètre, n° 2199 (février 2022)

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Decision fusion of deep learning and shallow learning for marine oil spill detection / Junfang Yang in Remote sensing, vol 14 n° 3 (February-1 2022)  

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Detection of damaged buildings after an earthquake with convolutional neural networks in conjunction with image segmentation / Ramazan Unlu in The Visual Computer, vol 38 n° 2 (February 2022)  

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European-wide forest monitoring substantiate the neccessity for a joint conservation strategy to rescue European ash species (Fraxinus spp.) / Jan-Peter George in Scientific reports, vol 12 (2022)  

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Mapping burn severity in the western Italian Alps through phenologically coherent reflectance composites derived from Sentinel-2 imagery / Donato Morresi in Remote sensing of environment, vol 269 (February 2022)  

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Maps, volunteered geographic information (VGI) and the spatio-discursive construction of nature / Juan Astaburuaga in Digital Geography and Society, vol 3 (2022)  

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Multi-method monitoring of rockfall activity along the classic route up Mont Blanc (4809 m a.s.l.) to encourage adaptation by mountaineers / Jacques Mourey in Natural Hazards and Earth System Sciences, vol 22 n° 2 (February 2022)  

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Possibilities for assessment and geovisualization of spatial and temporal water quality data using a webGIS application / Daniel Balla in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)  

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Relationships between species richness and ecosystem services in Amazonian forests strongly influenced by biogeographical strata and forest types / Gijs Steur in Scientific reports, vol 12 (2022)  

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Les risques-réseaux : une matrice des défaillances des réseaux urbains interdépendants / Nabil Touili in Belgeo, vol 2022 n° 1 (2022)  

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Three-Dimensional point cloud analysis for building seismic damage information / Fan Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 2 (February 2022)  

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Automatic extraction of damaged houses by earthquake based on improved YOLOv5: A case study in Yangbi / Yafei Jing in Remote sensing, vol 14 n° 2 (January-2 2022)  

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Conservation zones increase habitat heterogeneity of certified Mediterranean oak woodlands / Teresa Mexia in Forest ecology and management, vol 504 (January-15 2022)  

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