Descripteur
Documents disponibles dans cette catégorie (6127)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Simulating future LUCC by coupling climate change and human effects based on multi-phase remote sensing data / Zihao Huang in Remote sensing, vol 14 n° 7 (April-1 2022)
[article]
Titre : Simulating future LUCC by coupling climate change and human effects based on multi-phase remote sensing data Type de document : Article/Communication Auteurs : Zihao Huang, Auteur ; Xuejian Li, Auteur ; Qiang Du, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1698 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] automate cellulaire
[Termes IGN] changement climatique
[Termes IGN] changement d'utilisation du sol
[Termes IGN] Chine
[Termes IGN] écosystème forestier
[Termes IGN] forêt tropicale
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] interaction homme-milieu
[Termes IGN] modèle de simulation
[Termes IGN] modèle dynamique
[Termes IGN] modèle numérique de surface
[Termes IGN] puits de carbone
[Termes IGN] simulation spatialeRésumé : (auteur) Future land use and cover change (LUCC) simulations play an important role in providing fundamental data to reveal the carbon cycle response of forest ecosystems to LUCC. Subtropical forests have great potential for carbon sequestration, yet their future dynamics under natural and human influences are unclear. Zhejiang Province in China is an important distribution area for subtropical forests. For forest management, it is of great significance to explore the future dynamic changes of subtropical forests in Zhejiang. As a popular LUCC spatial simulation model, the cellular automata (CA) model coupled with machine learning and LUCC quantitative demand models such as system dynamics (SD) can achieve effective LUCC simulation. Therefore, we first integrated a back propagation neural network (BPNN), a CA, and a SD model as a BPNN_CA_SD (BCS) coupled model for future LUCC simulation and then designed a slow development scenario (SD_Scenario), a harmonious development scenario (HD_Scenario), a baseline development scenario (BD_Scenario), and a fast development scenario (FD_Scenario), combining climate change and human disturbance. Thirdly, we obtained future land-use patterns in Zhejiang Province from 2014 to 2084 under multiple scenarios, and finally, we analyzed the temporal and spatial changes of land use and discussed the subtropical forest dynamics of the future. The results showed the following: (1) The overall accuracy was approximately 0.8, the kappa coefficient was 0.75, and the figure of merit (FOM) value was over 28% when using the BCS model to predict LUCC, indicating that the model could predict the consistent change of LUCC accurately. (2) The future evolution of the LUCC under different scenarios varied, with the growth of bamboo forests and the decline of coniferous forests in the FD_Scenario being prominent among the forest dynamics changes. Compared with 2014, the bamboo forest in 2084 will increase by 37%, while the coniferous forest will decrease by 25%. (3) Comparing the area and spatial change of the subtropical forests, the SD_Scenario was found to be beneficial for the forest ecology. These results can provide an important decision-making reference for land-use planning and sustainable forest development in Zhejiang Province. Numéro de notice : A2022-281 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs14071698 Date de publication en ligne : 31/03/2022 En ligne : https://doi.org/10.3390/rs14071698 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100297
in Remote sensing > vol 14 n° 7 (April-1 2022) . - n° 1698[article]Spatial modeling of migration using GIS-based multi-criteria decision analysis: A case study of Iran / Naeim Mijani in Transactions in GIS, vol 26 n° 2 (April 2022)
[article]
Titre : Spatial modeling of migration using GIS-based multi-criteria decision analysis: A case study of Iran Type de document : Article/Communication Auteurs : Naeim Mijani, Auteur ; Davoud Shahpari Sani, Auteur ; Mohsen Dastaran, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 645 - 668 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse multicritère
[Termes IGN] approche hiérarchique
[Termes IGN] changement climatique
[Termes IGN] coefficient de corrélation
[Termes IGN] combinaison linéaire ponderée
[Termes IGN] données démographiques
[Termes IGN] données socio-économiques
[Termes IGN] Iran
[Termes IGN] migration humaine
[Termes IGN] modélisation spatiale
[Termes IGN] planification urbaine
[Termes IGN] système d'information géographiqueRésumé : (auteur) Spatial modeling of migration and the identification of the effective parameters are imperative for planning and managing demographic, economic, social, and environmental changes on various geographical scales. The recent climate change stressors as well as inequality in terms of education and life quality have triggered internal mass migrations in Iran, causing pressure on housing, the job market, and potential slums around large cities. This study proposes a new approach to modeling migration patterns in Iran based on multi-criteria decision analysis. For this purpose, a total of 23 individual criteria embedded within four criteria groups (economic, socio-cultural, welfare, and environmental) affecting national migration were used. The analytic hierarchy process was employed to determine weights for the input factors and the weighted linear combination (WLC) model was used for the integration of criteria, based on which maps of migration potential were produced. The model applied was evaluated based on the correlation coefficient between migration potential values obtained from the WLC model and the actual net migration rate. Among the input individual criteria, unemployment, higher education centers, number of physicians, and dust storms were found to influence national migration. Furthermore, our findings reveal that the potential for migration across Iranian provinces is heterogeneous, with the spatial potential for emigration being the highest and lowest in the border and central provinces, respectively. The correlation coefficient calculated between outputs from the WLC model and the net migration rate from 2011 to 2016, was .81, indicating the relatively high performance of the proposed model in producing a migration spatial potential map. Our proposed approach, along with the results achieved, can be useful to decision-makers and planners in designing data-driven policies against inequality- and climate-induced stressors. Numéro de notice : A2022-363 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.12873 Date de publication en ligne : 23/11/2021 En ligne : https://doi.org/10.1111/tgis.12873 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100582
in Transactions in GIS > vol 26 n° 2 (April 2022) . - pp 645 - 668[article]Validating the impact of various ionosphere correction on mid to long baselines and point positioning using GPS dual-frequency receivers / Alaa A. Elghazouly in Journal of applied geodesy, vol 16 n° 2 (April 2022)
[article]
Titre : Validating the impact of various ionosphere correction on mid to long baselines and point positioning using GPS dual-frequency receivers Type de document : Article/Communication Auteurs : Alaa A. Elghazouly, Auteur ; Mohamed Doma, Auteur ; Ahmed Sedeek, Auteur Année de publication : 2022 Article en page(s) : pp 81 - 90 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] correction ionosphérique
[Termes IGN] ligne de base
[Termes IGN] modèle ionosphérique
[Termes IGN] positionnement ponctuel précis
[Termes IGN] récepteur bifréquence
[Termes IGN] récepteur GPS
[Termes IGN] tempête magnétique
[Termes IGN] teneur verticale totale en électronsRésumé : (auteur) Due to the ionosphere delay, which has become the dominant GPS error source, it is crucial to remove the ionospheric effect before estimating point coordinates. Therefore, different agencies started to generate daily Global Ionosphere Maps (GIMs); the Vertical Total Electron Content (VTEC) values represented in GIMs produced by several providers can be used to remove the ionosphere error from observations. In this research, an analysis will be carried with three sources for VTEC maps produced by the Center for Orbit Determination in Europe (CODE), Regional TEC Mapping (RTM), and the International Reference Ionosphere (IRI). The evaluation is focused on the effects of a specific ionosphere GIM correction on the precise point positioning (PPP) solutions. Two networks were considered. The first network consists of seven Global Navigation Satellite Systems (GNSS) receivers from (IGS) global stations. The selected test days are six days, three of them quiet, and three other days are stormy to check the influence of geomagnetic storms on relative kinematic positioning solutions. The second network is a regional network in Egypt. The results show that the calculated coordinates using the three VTEC map sources are far from each other on stormy days rather than on quiet days. Also, the standard deviation values are large on stormy days compared to those on quiet days. Using CODE and RTM IONEX file produces the most precise coordinates after that the values of IRI. The elimination of ionospheric biases over the estimated lengths of many baselines up to 1000 km has resulted in positive findings, which show the feasibility of the suggested assessment procedure. Numéro de notice : A2022-250 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/jag-2021-0040 Date de publication en ligne : 27/11/2021 En ligne : https://doi.org/10.1515/jag-2021-0040 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100203
in Journal of applied geodesy > vol 16 n° 2 (April 2022) . - pp 81 - 90[article]Mapping forest site quality at national level / Ana Aguirre in Forest ecology and management, vol 508 (March-15 2022)
[article]
Titre : Mapping forest site quality at national level Type de document : Article/Communication Auteurs : Ana Aguirre, Auteur ; Daniel Moreno-Fernández, Auteur ; Iciar A. Alberdi, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120043 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] autocorrélation spatiale
[Termes IGN] carte forestière
[Termes IGN] climat local
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] Espagne
[Termes IGN] gestion forestière durable
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] krigeage
[Termes IGN] modèle numérique
[Termes IGN] sécheresse
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Determining site quality is essential in order to develop sustainable forest management, allowing more appropriate silvicultural decisions to be made. However, most studies carried out in Spain have focused on a few species and at local scale, which makes it difficult to apply the findings or conduct studies at larger scales. The aim of this study is to obtain a site quality map at national scale for the main forest species (Pinus sylvestris, Pinus uncinata, Pinus pinea, Pinus halepensis, Pinus nigra, Pinus pinaster, Pinus canariensis, Pinus radiata, Abies alba, Juniperus thurifera, Quercus robur, Querus petraea, Quercus pyrenaica, Quercus faginea, Quercus ilex, Quercus suber, Populus nigra, Eucalyptus globulus, Eucalyptus camaldulensis, Fagus sylvatica, Castanea sativa, Quercus pubescens, Populus × canadensis, Betula alba). National Forest Inventory (NFI) data has been used to develop site quality models using the site form (SF) concept (dominant height- dominant diameter relationship). Universal Kriging techniques have been used to identify both the geographical trend linked to site factors (climatic, soil and physiographic variables) and their spatial autocorrelation to estimate the SF for every species. Finally, the information was interpolated for each tile of the Spanish National Forest Map in which the species considered was present, thus obtaining a SF national map for each species. The results reveal biologically consistent SF models, indicating that both NFI data and SF are suitable for studying site quality at national level. The variables used differ among the species analyzed, altitude being the most important variable for estimating SF models, while aridity and soil variables are less important. The results obtained could provide an important tool for forest managers working at national level with the main forest species in Spain. This methodology could be used for larger areas, such as at European level, and would allow some species to be analyzed at larger scales. Numéro de notice : A2022-161 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.1016/j.foreco.2022.120043 Date de publication en ligne : 25/01/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120043 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99780
in Forest ecology and management > vol 508 (March-15 2022) . - n° 120043[article]Projections of climate change impacts on flowering-veraison water deficits for Riesling and Müller-Thurgau in Germany / Chenyao Yang in Remote sensing, vol 14 n° 6 (March-2 2022)
[article]
Titre : Projections of climate change impacts on flowering-veraison water deficits for Riesling and Müller-Thurgau in Germany Type de document : Article/Communication Auteurs : Chenyao Yang, Auteur ; Christoph Menz, Auteur ; Maxim Simões De Abreu Jaffe, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1519 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Allemagne
[Termes IGN] changement climatique
[Termes IGN] données météorologiques
[Termes IGN] phénologie
[Termes IGN] sécheresse
[Termes IGN] stress hydrique
[Termes IGN] viticulture
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) With global warming, grapevine is expected to be increasingly exposed to water deficits occurring at various development stages. In this study, we aimed to investigate the potential impacts of projected climate change on water deficits from the flowering to veraison period for two main white wine cultivars (Riesling and Müller-Thurgau) in Germany. A process-based soil-crop model adapted for grapevine was utilized to simulate the flowering-veraison crop water stress indicator (CWSI) of these two varieties between 1976–2005 (baseline) and 2041–2070 (future period) based on a suite of bias-adjusted regional climate model (RCM) simulations under RCP4.5 and RCP8.5. Our evaluation indicates that the model can capture the early-ripening (Müller-Thurgau) and late-ripening (Riesling) traits, with a mean bias of prediction of ≤2 days and a well-reproduced inter-annual variability for more than 60 years. Under climate projections, the flowering stage is advanced by 10–20 days (higher in RCP8.5) between the two varieties, whereas a slightly stronger advancement is found for Müller-Thurgau than for Riesling for the veraison stage. As a result, the flowering-veraison phenophase is mostly shortened for Müller-Thurgau, whereas it is extended by up to two weeks for Riesling in cool and high-elevation areas. The length of phenophase plays an important role in projected changes of flowering-veraison mean temperature and precipitation. The late-ripening trait of Riesling makes it more exposed to increased summer temperature (mainly in August), resulting in a higher mean temperature increase for Riesling (1.5–2.5 °C) than for Müller-Thurgau (1–2 °C). As a result, an overall increased CWSI by up to 15% (ensemble median) is obtained for both varieties, whereas the upper (95th) percentile of simulations shows a strong signal of increased water deficit by up to 30%, mostly in the current winegrowing regions. Intensified water deficit stress can represent a major threat for high-quality white wine production, as only mild water deficits are acceptable. Nevertheless, considerable variabilities of CWSI were discovered among RCMs, highlighting the importance of efforts towards reducing uncertainties in climate change impact assessment. Numéro de notice : A2022-252 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/rs14061519 Date de publication en ligne : 21/03/2022 En ligne : https://doi.org/10.3390/rs14061519 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100208
in Remote sensing > vol 14 n° 6 (March-2 2022) . - n° 1519[article]Aboveground biomass of salt-marsh vegetation in coastal wetlands: Sample expansion of in situ hyperspectral and Sentinel-2 data using a generative adversarial network / Chen Chen in Remote sensing of environment, vol 270 (March 2022)PermalinkAre northern German Scots pine plantations climate smart? The impact of large-scale conifer planting on climate, soil and the water cycle / Christoph Leuschner in Forest ecology and management, vol 507 (March-1 2022)PermalinkAssessing ZWD models in delay and height domains using data from stations in different climate regions / Thainara Munhoz Alexandre de Lima in Applied geomatics, vol 14 n° 1 (March 2022)PermalinkChallenges related to the determination of altitudes of mountain peaks presented on cartographic sources / Katarzyna Chwedczuk in Geodetski vestnik, vol 66 n° 1 (March 2022)PermalinkClassification of Eucalyptus plantation Site Index (SI) and Mean Annual Increment (MAI) prediction using DEM-based geomorphometric and climatic variables in Brazil / Aliny Aparecida Dos Reis in Geocarto international, vol 37 n° 5 ([01/03/2022])PermalinkEvolution de la ressource et de la production des chênes pubescent, pédonculé et sessile / Ingrid Bonhême in Forêt entreprise, n° 261 (novembre-décembre 2021)PermalinkExploring the relationship between the 2D/3D architectural morphology and urban land surface temperature based on a boosted regression tree: A case study of Beijing, China / Zhen Li in Sustainable Cities and Society, vol 78 (March 2022)PermalinkFlood monitoring by integration of remote sensing technique and multi-criteria decision making method / Hadi Farhadi in Computers & geosciences, vol 160 (March 2022)PermalinkMonitoring 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)PermalinkObservational 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])PermalinkSimulation 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)PermalinkSimultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3 / Nima Pahlevan in Remote sensing of environment, vol 270 (March 2022)PermalinkUnderstanding the geodetic signature of large aquifer systems: Example of the Ozark plateaus in central United States / Stacy Larochelle in Journal of geophysical research : Solid Earth, vol 127 n° 3 (March 2022)PermalinkUnexpected 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)PermalinkValidating a new GNSS-based sea level instrument (CalNaGeo) at Senetosa Cape / Pascal Bonnefond in Marine geodesy, vol 45 n° 2 (March 2022)PermalinkCompetition and climate influence in the basal area increment models for Mediterranean mixed forests / Diego Rodríguez de Prado in Forest ecology and management, vol 506 (February-15 2022)PermalinkComprehensive study on the tropospheric wet delay and horizontal gradients during a severe weather event / Victoria Graffigna in Remote sensing, vol 14 n° 4 (February-2 2022)PermalinkMulti-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques / Saman Javadi in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkPourquoi la forêt française a besoin d’un traitement de fond / Guillaume Decocq in The Conversation France, vol 2022 ([10/02/2022])PermalinkAn 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)PermalinkApplication of catastrophe theory to spatial analysis of groundwater potential in a sub-humid tropical region: a hybrid approach / Laishram Kanta Singh in Geocarto international, vol 37 n° 3 ([01/02/2022])PermalinkApplications and challenges of GRACE and GRACE follow-on satellite gravimetry / Jianli Chen in Surveys in Geophysics, vol 43 n° 1 (February 2022)PermalinkAssessment 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)PermalinkComparison of atmospheric mass density models using a new data source: COSMIC satellite ephemerides / Yang Yang in IEEE Aerospace and Electronic Systems Magazine, vol 37 n° 2 (February 2022)PermalinkDevelopment of earth observational diagnostic drought prediction model for regional error calibration: A case study on agricultural drought in Kyrgyzstan / Eunbeen Park in GIScience and remote sensing, vol 59 n° 1 (2022)PermalinkFast local adaptive multiscale image matching algorithm for remote sensing image correlation / Niccolò Dematteis in Computers & geosciences, vol 159 (February 2022)PermalinkGNSS reflectometry global ocean wind speed using deep learning: Development and assessment of CyGNSSnet / Milad Asgarimehr in Remote sensing of environment, vol 269 (February 2022)PermalinkGrowing stock monitoring by European National Forest Inventories: Historical origins, current methods and harmonisation / Thomas Gschwantner in Forest ecology and management, vol 505 (February-1 2022)PermalinkMapping global flying aircraft activities using Landsat 8 and cloud computing / Fen Zhao in ISPRS Journal of photogrammetry and remote sensing, vol 184 (February 2022)PermalinkPossibilities 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)PermalinkSpatiotemporal temperature fusion based on a deep convolutional network / Xuehan Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 2 (February 2022)PermalinkTree mortality caused by Diplodia shoot blight on Pinus sylvestris and other mediterranean pines / Maria Caballol in Forest ecology and management, vol 505 (February-1 2022)PermalinkUsing vertices of a triangular irregular network to calculate slope and aspect / Guanghui Hu in International journal of geographical information science IJGIS, vol 36 n° 2 (February 2022)PermalinkCo-seismic ionospheric disturbances following the 2016 West Sumatra and 2018 Palu earthquakes from GPS and GLONASS measurements / Mokhamad Nur Cahyadi in Remote sensing, vol 14 n° 2 (January-2 2022)PermalinkForest floor alteration by canopy trees and soil wetness drive regeneration of a spruce-beech forest / Pavel Daněk in Forest ecology and management, vol 504 (January-15 2022)PermalinkMulti-temporal remote sensing data to monitor terrestrial ecosystem responses to climate variations in Ghana / Ram Avtar in Geocarto international, vol 37 n° 2 ([15/01/2022])PermalinkSoil erosion estimation of Bhandara region of Maharashtra, India, by integrated use of RUSLE, remote sensing, and GIS / Sumedh R. Kashiwar in Natural Hazards, vol 110 n° 2 (January 2022)Permalink3D geovisualization for visual analysis of urban climate / Sidonie Christophe in Cybergeo, European journal of geography, vol 2022 ([01/01/2022])PermalinkAdaptation of the standardized vegetation optical depth index for satellite-based soil moisture / Juliette Raabe (2022)PermalinkAnalyse haute résolution de la morphologie des paysages et des processus à partir de LiDAR aéroporté répété et simulation hydraulique / Thomas Bernard (2022)PermalinkApplication of deep learning with stratified K-fold for vegetation species discrimation in a protected mountainous region using Sentinel-2 image / Efosa Gbenga Adagbasa in Geocarto international, vol 37 n° 1 ([01/01/2022])PermalinkApport des nouveaux systèmes GNSS de cartographie du niveau marin à l’exploitation des données altimétriques en zone côtière / Clémence Chupin (2022)PermalinkApport de la télédétection et des variables auxiliaires dans l'étude de l'évolution des périodes de sécheresse / Nesrine Farhani (2022)PermalinkAssessment of the performance of GIS-based analytical hierarchical process (AHP) approach for flood modelling in Uttar Dinajpur district of West Bengal, India / Rajib Mitra in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkPermalinkBeech and hornbeam dominate oak 20 years after the creation of storm-induced gaps / Lucie Dietz in Forest ecology and management, vol 503 (January-1 2022)PermalinkCartographie dynamique de la topographie de l'océan de surface par assimilation de données altimétriques / Florian Le Guillou (2022)PermalinkLa cartographie au service de la diffusion des connaissances de l’Inventaire du Patrimoine culturel de la Région Bretagne / Elise Frank (2022)PermalinkCharacteristics of taiga and tundra snowpack in development and validation of remote sensing of snow / Henna-Reetta Hannula (2022)PermalinkCIME: Context-aware geolocation of emergency-related posts / Gabriele Scalia in Geoinformatica, vol 26 n° 1 (January 2022)PermalinkContraintes observationnelles historiques sur la sensibilité climatique : implications pour les projections de la hausse du niveau de la mer / Jonathan Chenal (2022)PermalinkConventional and neural network-based water vapor density model for GNSS troposphere tomography / Chen Liu in GPS solutions, vol 26 n° 1 (January 2022)PermalinkCultural Heritage and Climate Change: New challenges and perspectives for research / Christopher Ballard (2022)PermalinkPermalinkDetection and biomass estimation of phaeocystis globosa blooms off Southern China from UAV-based hyperspectral measurements / Xue Li in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)PermalinkDetection of windthrown tree stems on UAV-orthomosaics using U-Net convolutional networks / Stefan Reder in Remote sensing, vol 14 n° 1 (January-1 2022)PermalinkEffets des bryophytes sur les microsites de régénération forestière en climat tempéré / Laura Chevaux (2022)PermalinkPermalinkEvaluation de méthodes automatisées de cartographie des zones inondables adaptées à la prévision des crues soudaines / Nabil Hocini (2022)PermalinkÉvolution rétrospective et prospective d’un massif dunaire par imagerie multispectrale et LiDAR / Iris Jeuffrard (2022)PermalinkFlood susceptibility mapping using meta-heuristic algorithms / Alireza Arabameri in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkForest fire susceptibility assessment using Google Earth engine in Gangwon-do, Republic of Korea / Yong Piao in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkPermalinkGlobal and climate challenges, graph-based data analysis for multisource information extraction / Morgane Batelier (2022)PermalinkGlobal glacier mass change by spatiotemporal analysis of digital elevation models / Romain Hugonnet (2022)PermalinkHarmonisation de la production cartographique dans le cadre des Programmes d’Actions de Prévention des Inondations / Nils Deslandes (2022)PermalinkHistorical shoreline analysis and field monitoring at Ennore coastal stretch along the Southeast coast of India / M. Dhananjayan in Marine geodesy, vol 45 n° 1 (January 2022)PermalinkHistorical Vltava River valley–various historical sources within web mapping environment / Jiří Krejčí in ISPRS International journal of geo-information, vol 11 n° 1 (January 2022)PermalinkHourly rainfall forecast model using supervised learning algorithm / Qingzhi Zhao in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)PermalinkPermalinkImplementation of the log-transformed band ratio algorithm on images of WorldView-3 and Sentinel-2 for bathymetry mapping of a pocket beach of Malta / Antoine Cornu (2022)PermalinkImportance des facteurs locaux climatiques et édaphiques dans la dynamique de régénération des communautés à hêtre en marge d’aire de répartition / Ludovic Lacombe (2022)PermalinkInvestigating the role of wind disturbance in tropical forests through a forest dynamics model and satellite observations / E-Ping Rau (2022)PermalinkItalian National Forest Inventory: Methods and results of the third survey / Patrizia Gasparini (2022)PermalinkLatent heat flux variability and response to drought stress of black poplar: A multi-platform multi-sensor remote and proximal sensing approach to relieve the data scarcity bottleneck / Flavia Tauro in Remote sensing of environment, vol 268 (January 2022)PermalinkA method to produce metadata describing and assessing the quality of spatial landmark datasets in mountain area / Marie-Dominique Van Damme (2022)PermalinkModalités et rythmes d'évolution des falaises des Vaches Noires (Normandie, France) : caractérisation et quantification des dynamiques hydrogravitaires par approches multi-scalaires / Thomas Roulland (2022)PermalinkModeling of precipitable water vapor from GPS observations using machine learning and tomography methods / Mir Reza Ghaffari Razin in Advances in space research, vol 69 n° 7 (April 2022)PermalinkModélisation du lien entre éruptions et glissements de flancs au Piton de la Fournaise / Quentin Dumont (2022)PermalinkPermalinkModélisations des écoulements fluviaux adaptées aux observations spatiales et assimilations de données altimétriques / Thibault Malou (2022)PermalinkMonitoring and analysis of crop irrigation dynamics in Central Italy through the use of MODIS NDVI data / Marta Chiesi in European journal of remote sensing, vol 55 n° 1 (2022)PermalinkMonitoring and modeling of the Sacramento Valley aquifer (California) using geodetic and piezometric measurements / Stacy Larochelle (2022)PermalinkNew insights in the modeling and simulation of tree and stand level variables in Mediterranean mixed forests in the present context of climate change / Diego Rodríguez de Prado (2022)PermalinkA new method for the attribution of breakpoints in segmentation of IWV difference time series / Khanh Ninh Nguyen (2022)PermalinkNon-linear GNSS signal processing applied to land observation with high-rate airborne reflectometry / Hamza Issa (2022)PermalinkPotentialité de la télédétection thermique pour la modélisation climatique en milieu viticole / Gwenaël Morin (2022)PermalinkPrecipitation frequency in MED and EURO-CORDEX ensembles from 0.44° to convective permitting resolution: Impact of model resolution and convection representation / Minh Ha-Truong (2022)PermalinkPredicting AIS reception using tropospheric propagation forecast and machine learning / Zackary Vanche (2022)PermalinkPreparation of the VENµS satellite data over Israel for the input into the GRASP data treatment algorithm / Maeve Blarel (2022)PermalinkPython software to transform GPS SNR wave phases to volumetric water content / Angel Martín in GPS solutions, vol 26 n° 1 (January 2022)PermalinkPermalinkPermalinkRegeneration of spruce - fir - beech mixed forests under climate and ungulate pressure / Mithila Unkule (2022)PermalinkPermalink