Descripteur
Termes IGN > sciences humaines et sociales > vie des organisations > gestion des risques
gestion des risquesVoir aussi |
Documents disponibles dans cette catégorie (828)


Etendre la recherche sur niveau(x) vers le bas
Flood vulnerability assessment of urban buildings based on integrating high-resolution remote sensing and street view images / Ziyao Xing in Sustainable Cities and Society, vol 92 (May 2023)
![]()
[article]
Titre : Flood vulnerability assessment of urban buildings based on integrating high-resolution remote sensing and street view images Type de document : Article/Communication Auteurs : Ziyao Xing, Auteur ; Shuai Yang, Auteur ; Xuli Zan, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 104467 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] attention (apprentissage automatique)
[Termes IGN] bâtiment
[Termes IGN] Chine
[Termes IGN] gestion des risques
[Termes IGN] image Streetview
[Termes IGN] inondation
[Termes IGN] milieu urbain
[Termes IGN] planification urbaine
[Termes IGN] Quickbird
[Termes IGN] segmentation sémantique
[Termes IGN] vulnérabilitéRésumé : (auteur) Urban flood risk management requires an extensive investigation of the vulnerability characteristics of buildings. Large-scale field surveys usually cost a lot of time and money, while satellite remote sensing and street view images can provide information on the tops and facades of buildings respectively. Thereupon, this paper develops a building vulnerability assessment framework using remote sensing and street view features. Specifically, a UNet-based semantic segmentation model, FSA-UNet (Fusion-Self-Attention-UNet) is proposed to integrate remote sensing and street view features and the vulnerability information contained in the images is fully exploited. And the building vulnerability index is generated to provide the spatial distribution characteristics of urban building vulnerability. The experiment shows that the mIoU of the proposed model can reach 82% for building vulnerability classification in Hefei, China, which is more accurate than the traditional semantic segmentation models. The results indicate that the integration of street view and remote sensing image features can improve the ability of building vulnerability assessment, and the model proposed in this study can better capture the correlation features of multi-angle images through the self-attention mechanism and combines hierarchy features and edge information to improve the classification effect. This study can support for disaster management and urban planning. Numéro de notice : A2023-152 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.scs.2023.104467 Date de publication en ligne : 23/02/2023 En ligne : https://doi.org/10.1016/j.scs.2023.104467 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102826
in Sustainable Cities and Society > vol 92 (May 2023) . - n° 104467[article]Seismic deformation in the Adriatic Sea region / B. Orecchio in Journal of geodynamics, vol 155 (March 2023)
![]()
[article]
Titre : Seismic deformation in the Adriatic Sea region Type de document : Article/Communication Auteurs : B. Orecchio, Auteur ; D. Presti, Auteur ; S. Scolaro, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n°101956 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] Adriatique, mer
[Termes IGN] déformation de la croute terrestre
[Termes IGN] faille géologique
[Termes IGN] forme d'onde
[Termes IGN] histogramme
[Termes IGN] inversion
[Termes IGN] sismologie
[Termes IGN] surveillance géologique
[Termes IGN] tectonique des plaquesRésumé : (auteur) We present an overall analysis of the recent seismic activity occurred in the Adriatic Sea region, a strongly debated sector of the Mediterranean area, where several authors have proposed different models of plate configuration and kinematics. In the past, seismic investigations of this marine area have been strongly hampered by non-optimal network geometries, but data quality increase and recent methodological improvements lay the groundwork to attempt more accurate analyses including proper evaluations of result reliability. On these grounds, we investigated the seismic activity of the last decades by means of new hypocenter locations, waveform inversion focal mechanisms and seismogenic stress fields. We used the Bayloc non-linear probabilistic algorithm to compute hypocenter locations for the most relevant seismic sequences by carefully evaluating location quality and seismolineaments reliability. We also provided an updated database of waveform inversion focal mechanisms including original solutions estimated by applying the waveform inversion method Cut And Paste and data available from official catalogs. Then, focal mechanism solutions have been used to estimate seismogenic stress fields through different inversion algorithms. Seismic results indicate a relevant degree of fragmentation and different patterns of deformation in the Central Adriatic region. In particular, our analyses depicted two NW-SE oriented, adjacent volumes: (i) a pure compressive domain with NNE-trending axis of maximum compression characterizes the northeastern volume where the seismic activity occurs on W-to-NW oriented seismic sources; (ii) a transpressive domain with NW-trending axis of maximum compression characterizes the southwestern sector where thrust faulting preferentially occurs on ENE-to-NE oriented planes and strike-slip faulting on E-W ones. Joint evaluation of seismic findings of the present study and kinematic models proposed in the literature indicates just in the Central Adriatic region the presence of a broad deformation zone, accommodating a still evolving fragmentation of the Adriatic domain in two blocks rotating in opposite directions. On these grounds, the obtained results not only furnish new seismological evidence supporting the "two-blocks model" proposed by previous authors, but they also provide additional constraints, useful for better understanding and modeling the seismotectonic processes occurring in the Adriatic region. Numéro de notice : A2023-051 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1016/j.jog.2022.101956 Date de publication en ligne : 30/11/2022 En ligne : https://doi.org/10.1016/j.jog.2022.101956 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102379
in Journal of geodynamics > vol 155 (March 2023) . - n°101956[article]Large-scale burn severity mapping in multispectral imagery using deep semantic segmentation models / Xikun Hu in ISPRS Journal of photogrammetry and remote sensing, vol 196 (February 2023)
![]()
[article]
Titre : Large-scale burn severity mapping in multispectral imagery using deep semantic segmentation models Type de document : Article/Communication Auteurs : Xikun Hu, Auteur ; Puzhao Zhang, Auteur ; Yifang Ban, Auteur Année de publication : 2023 Article en page(s) : pp 228 - 240 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte thématique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] dommage
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] incendie de forêt
[Termes IGN] jeu de données localisées
[Termes IGN] segmentation sémantique
[Termes IGN] surveillance forestière
[Termes IGN] zone sinistréeRésumé : (auteur) Nowadays Earth observation satellites provide forest fire authorities and resource managers with spatial and comprehensive information for fire stabilization and recovery. Burn severity mapping is typically performed by classifying bi-temporal indices (e.g., dNBR, and RdNBR) using thresholds derived from parametric models incorporating field-based measurements. Analysts are currently expending considerable manual effort using prior knowledge and visual inspection to determine burn severity thresholds. In this study, we aim to employ highly automated approaches to provide spatially explicit damage level estimates. We first reorganize a large-scale Landsat-based bi-temporal burn severity assessment dataset (Landsat-BSA) by visual data cleaning based on annotated MTBS data (approximately 1000 major fire events in the United States). Then we apply state-of-the-art deep learning (DL) based methods to map burn severity based on the Landsat-BSA dataset. Experimental results emphasize that multi-class semantic segmentation algorithms can approximate the threshold-based techniques used extensively for burn severity classification. UNet-like models outperform other region-based CNN and Transformer-based models and achieve accurate pixel-wise classification results. Combined with the online hard example mining algorithm to reduce class imbalance issue, Attention UNet achieves the highest mIoU (0.78) and the highest Kappa coefficient close to 0.90. The bi-temporal inputs with ancillary spectral indices work much better than the uni-temporal multispectral inputs. The restructured dataset will be publicly available and create opportunities for further advances in remote sensing and wildfire communities. Numéro de notice : A2023-122 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.12.026 Date de publication en ligne : 11/01/2023 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.12.026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102498
in ISPRS Journal of photogrammetry and remote sensing > vol 196 (February 2023) . - pp 228 - 240[article]Perspectives: Critical zone perspectives for managing changing forests / Marissa Kopp in Forest ecology and management, vol 528 (January-15 2023)
![]()
[article]
Titre : Perspectives: Critical zone perspectives for managing changing forests Type de document : Article/Communication Auteurs : Marissa Kopp, Auteur ; Denise Alving, Auteur ; Taylor Blackman, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120627 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] changement climatique
[Termes IGN] écosystème forestier
[Termes IGN] Etats-Unis
[Termes IGN] géologie locale
[Termes IGN] gestion de l'eau
[Termes IGN] gestion forestière
[Termes IGN] incendie de forêt
[Termes IGN] Insecta
[Termes IGN] parasite (biologie)
[Termes IGN] planification
[Termes IGN] productivité
[Termes IGN] stress hydrique
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Forest management is under intensifying ecological and societal pressures amid the current geological epoch, which some see becoming the Anthropocene. These pressures extend to temporal and physical scales typical of geology; however, integrating geological processes into forest management has lagged behind the inclusion of shorter-term and surficial ecosystem processes. As such, we examine the field of critical zone science for connections that translate geologic knowledge to forest management and planning. Earth’s critical zone is the thin near-surface zone spanning from the bottom of circulating groundwater to the top of the atmospheric boundary layer of forest canopies. We explore four case studies from regions of the U.S.A. to highlight how recent critical zone discoveries inform contemporary forest management challenges. Some examples of management-relevant research include mediation of the impacts of climate change on forest productivity across gradients in geology, aspect, and topography; the role of bedrock water storage on drought resistance; hydrology-vegetation interactions following pest outbreaks; and quantification of water partitioning and erosion following fire. The accelerated pace of critical zone discovery has been synchronous with increased availability of open-source data resources for forest managers to expand this framework in management and planning. Numéro de notice : A2023-034 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120627 Date de publication en ligne : 16/11/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120627 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102297
in Forest ecology and management > vol 528 (January-15 2023) . - n° 120627[article]La forêt progresse mais la mortalité des arbres s’accroît / Anonyme in Géomètre, n° 2209 (janvier 2023)
[article]
Titre : La forêt progresse mais la mortalité des arbres s’accroît Type de document : Article/Communication Auteurs : Anonyme, Auteur Année de publication : 2023 Article en page(s) : pp 13 - 13 Langues : Français (fre) Descripteur : [Termes IGN] bois mort
[Termes IGN] incendie de forêt
[Termes IGN] sécheresse
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Premier enseignement de l’inventaire forestier national 2021, publié par l’Institut national de l’information géographique et forestière (IGN) en décembre dernier : la mortalité des arbres s’est accrue de 54 % sur la dernière décennie. En cause : les sécheresses récurrentes et les conditions climatiques, difficiles pour les arbres mais aussi propices aux insectes xylophages. Les forêts du Grand Est et de Bourgogne-Franche-Comté sont les plus touchées, les moins impactées étant les régions du sud. Châtaignier, épicéa commun et frêne sont les essences les plus affectées. Aujourd’hui, le bilan entre la croissance des arbres, leur mortalité naturelle et les prélèvements de bois par l’homme se traduit par une augmentation du volume de la forêt de 1,6m3/ha/an. En effet, malgré tout, la surface de la forêt augmente, atteignant 17,1 millions d’hectares en 2021 – soit une extension de 21 % depuis 1985. Qu’en sera-t-il de l’inventaire forestier de l’année 2022 (à paraître fin 2023), marquée par de terribles incendies pendant l’été ? Près de 67000 ha sont partis en fumée l’année dernière. Numéro de notice : A2023-060 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 01/01/2023 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102332
in Géomètre > n° 2209 (janvier 2023) . - pp 13 - 13[article]Réservation
Réserver ce documentExemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 063-2023011 SL Revue Centre de documentation Revues en salle Disponible Mitigating the risk of wind damage at the forest landscape level by using stand neighbourhood and terrain elevation information in forest planning / Roope Ruotsalainen in Forestry, an international journal of forest research, vol 96 n° 1 (January 2023)
PermalinkPrescribed fire after thinning increased resistance of sub-Mediterranean pine forests to drought events and wildfires / Lena Vilà-Vilardell in Forest ecology and management, vol 527 (January-1 2023)
PermalinkWavelet-like denoising of GNSS data through machine learning. Application to the time series of the Campi Flegrei volcanic area (Southern Italy) / Rolando Carbonari in Geomatics, Natural Hazards and Risk, vol 14 n° 1 (2023)
PermalinkEstablishing a GIS-based evaluation method considering spatial heterogeneity for debris flow susceptibility mapping at the regional scale / Shengwu Qin in Natural Hazards, vol 114 n° 3 (December 2022)
PermalinkForêt amazonienne : de nouveau sous contrôle ? / Laurent Polidori in Géomètre, n° 2208 (décembre 2022)
PermalinkModelling evacuation preparation time prior to floods: A machine learning approach / R. Sreejith in Sustainable Cities and Society, vol 87 (December 2022)
PermalinkSpatio-temporal patterns of wildfires in Siberia during 2001–2020 / Oleg Tomshin in Geocarto international, vol 37 n° 25 ([01/12/2022])
PermalinkAccompagner le rétablissement spontané de la forêt après un incendie / Jacques Hazera in Géomètre, n° 2207 (novembre 2022)
PermalinkDeep 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)
PermalinkInvestigation 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)
PermalinkSpatio-temporal graph convolutional networks for road network inundation status prediction during urban flooding / Faxi Yuan in Computers, Environment and Urban Systems, vol 97 (October 2022)
PermalinkExploring multi-modal evacuation strategies for a landlocked population using large-scale agent-based simulations / Kevin Chapuis in International journal of geographical information science IJGIS, vol 36 n° 9 (September 2022)
PermalinkFeux de forêt : un drone traque les risques de reprise / Nathalie Da Cruz in Géomètre, n° 2205 (septembre 2022)
PermalinkFlood vulnerability and buildings’ flood exposure assessment in a densely urbanised city: comparative analysis of three scenarios using a neural network approach / Quoc Bao Pham in Natural Hazards, vol 113 n° 2 (September 2022)
PermalinkLarge-area high spatial resolution albedo retrievals from remote sensing for use in assessing the impact of wildfire soot deposition on high mountain snow and ice melt / André Bertoncini in Remote sensing of environment, vol 278 (September 2022)
PermalinkRapid source models of the 2021 Mw 7.4 Maduo, China, earthquake inferred from high-rate BDS3/2, GPS, Galileo and GLONASS observations / Jianfei Zang in Journal of geodesy, vol 96 n° 9 (September 2022)
PermalinkTowards a global seasonal and permanent reference water product from Sentinel-1/2 data for improved flood mapping / Sandro Martinis in Remote sensing of environment, vol 278 (September 2022)
PermalinkDetection and characterization of slow-moving landslides in the 2017 Jiuzhaigou earthquake area by combining satellite SAR observations and airborne Lidar DSM / Jiehua Cai in Engineering Geology, vol 305 (August 2022)
PermalinkInfluence of the declaration of protected natural areas on the evolution of forest fires in collective lands in Galicia (Spain) / Gervasio Lopez Rodriguez in Forests, Vol 13 n° 8 (August 2022)
PermalinkSpatial–spectral attention network guided with change magnitude image for land cover change detection using remote sensing images / Zhiyong Lv in IEEE Transactions on geoscience and remote sensing, vol 60 n° 8 (August 2022)
PermalinkUse of GIS and dasymetric mapping for estimating tsunami-affected population to facilitate humanitarian relief logistics: a case study from Phuket, Thailand / Kiatkulchai Jitt-Aer in Natural Hazards, vol 113 n° 1 (August 2022)
PermalinkA comparison of three multi-criteria decision-making models in mapping flood hazard areas of Northeast Penang, Malaysia / Rofiat Bunmi Mudashiru in Natural Hazards, vol 112 n° 3 (July 2022)
PermalinkRisk assessment and prediction of forest health for effective geo-environmental planning and monitoring of mining affected forest area in hilltop region / Narayan Kayet in Geocarto international, vol 37 n° 11 ([15/06/2022])
PermalinkGIS and machine learning for analysing influencing factors of bushfires using 40-year spatio-temporal bushfire data / Wanqin He in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)
PermalinkThe effects of fire on Pinus sylvestris L. as determined by dendroecological analysis (Sierra de Gredos, Spain) / Mar Génova in iForest, biogeosciences and forestry, vol 15 n° 3 (June 2022)
PermalinkAnalyzing spatio-temporal pattern of the forest fire burnt area in Uttarakhand using Sentinel-2 data / Shailja Mamgain in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-3-2022 (2022 edition)
PermalinkCliff change detection using siamese KPCONV deep network on 3D point clouds / Iris de Gelis in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-3-2022 (2022 edition)
PermalinkA voxel-based method for the three-dimensional modelling of heathland from lidar point clouds: first results / N. Homainejad in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-3-2022 (2022 edition)
PermalinkDeep mass redistribution prior to the 2010 Mw 8.8 Maule (Chile) Earthquake revealed by GRACE satellite gravity / Marie Bouih in Earth and planetary science letters, vol 584 (15 April 2022)
PermalinkDetermination of building flood risk maps from LiDAR mobile mapping data / Yu Feng in Computers, Environment and Urban Systems, vol 93 (April 2022)
PermalinkFlood mapping using multi-temporal Sentinel-1 SAR images: A case study—Inaouene watershed from Northeast of Morocco / Brahim Benzougagh in Iranian Journal of Science and Technology - Transactions of Civil Engineering, vol 46 n° 2 (April 2022)
PermalinkNatural disturbances risks in European boreal and temperate forests and their links to climate change : A review of modelling approaches / Joyce Machado Nunes Romeiro in Forest ecology and management, vol 509 (April-1 2022)
PermalinkEarly warning of COVID-19 hotspots using human mobility and web search query data / Takahiro Yabe in Computers, Environment and Urban Systems, vol 92 (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)
PermalinkA national fuel type mapping method improvement using sentinel-2 satellite data / Alexandra Stefanidou in Geocarto international, vol 37 n° 4 ([15/02/2022])
PermalinkScorch height and volume modeling in prescribed fires: Effects of canopy gaps in Pinus pinaster stands in Southern Europe / J.R. Molina in Forest ecology and management, vol 506 (February-15 2022)
PermalinkSimulating fire-safe cities using a machine learning-based algorithm for the complex urban forms of developing nations: a case of Mumbai India / Vaibhav Kumar in Geocarto international, vol 37 n° 4 ([15/02/2022])
PermalinkPermalinkDevelopment 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)
PermalinkMapping 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)
PermalinkMulti-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)
PermalinkClassification of mediterranean shrub species from UAV point clouds / Juan Pedro Carbonell-Rivera in Remote sensing, vol 14 n° 1 (January-1 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)
PermalinkHarmonisation de la production cartographique dans le cadre des Programmes d’Actions de Prévention des Inondations / Nils Deslandes (2022)
PermalinkMapping burned areas and land-uses in Kangaroo Island using an object-based image classification framework and Landsat 8 Imagery from Google Earth Engine / Jiyu Liu in Geomatics, Natural Hazards and Risk, vol 13 (2022)
PermalinkModélisation du lien entre éruptions et glissements de flancs au Piton de la Fournaise / Quentin Dumont (2022)
PermalinkMonitoring forest-savanna dynamics in the Guineo-Congolian transition area of the centre region of Cameroon / Le Bienfaiteur Sagang Takougoum (2022)
PermalinkSimulation of the meltwater under different climate change scenarios in a poorly gauged snow and glacier-fed Chitral River catchment (Hindukush region) / Huma Hayat in Geocarto international, vol 37 n° 1 ([01/01/2022])
PermalinkThree-dimensional simulations of rockfalls in Ischia, Southern Italy, and preliminary susceptibility zonation / Massimiliano Alvioli in Geomatics, Natural Hazards and Risk, vol 13 (2022)
PermalinkA GIS-remote sensing approach for forest fire risk assessment: case of Bizerte region, Tunisia / Salwa Saidi in Applied geomatics, vol 13 n° 4 (December 2021)
PermalinkIncorporating multi-criteria decision-making and fuzzy-value functions for flood susceptibility assessment / Ali Azareh in Geocarto international, vol 36 n° 20 ([01/12/2021])
PermalinkPrescribed burning as a cost-effective way to address climate change and forest management in Mediterranean countries / Renata Martins Pacheco in Annals of Forest Science, vol 78 n° 4 (December 2021)
PermalinkValidation of the accuracy of geodetic automated measurement system based on GNSS platform for continuous monitoring of surface movements in post-mining areas / Violetta Sokoła-Szewioła in Reports on geodesy and geoinformatics, vol 112 n° 1 (December 2021)
PermalinkPersistent scatterer interferometry for Pettimudi (India) landslide monitoring using Sentinel-1A images / Hari Shankar in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 11 (November 2021)
PermalinkDeep-learning-based burned area mapping using the synergy of Sentinel-1&2 data / Qi Zhang in Remote sensing of environment, vol 264 (October 2021)
PermalinkInvestigation of the landslides in Beylikdüzü-Esenyurt districts of Istanbul from InSAR and GNSS observations / Caglar Bayik in Natural Hazards, vol 109 n° 1 (October 2021)
PermalinkLandslide susceptibility prediction based on image semantic segmentation / Bowen Du in Computers & geosciences, vol 155 (October 2021)
PermalinkOn the suitability of a unified GIS-BIM-HBIM framework for cataloguing and assessing vulnerability in Historic Urban Landscapes: a critical review / Rafael Ramirez Eudave in International journal of geographical information science IJGIS, vol 35 n° 10 (October 2021)
PermalinkPrioritization of forest fire hazard risk simulation using Hybrid Grey Relativity Analysis (HGRA) and Fuzzy Analytical Hierarchy Process (FAHP) coupled with multicriteria decision analysis (MCDA) techniques – a comparative study analysis / Michael Stanley Peprah in Geodesy and cartography, vol 47 n° 3 (October 2021)
PermalinkDevelopment of a GIS-based alert system to mitigate flash flood impacts in Asyut governorate, Egypt / Soha A. Mohamed in Natural Hazards, vol 108 n° 3 (September 2021)
PermalinkInvestigating the application of artificial intelligence for earthquake prediction in Terengganu / Suzlyana Marhain in Natural Hazards, vol 108 n° 1 (August 2021)
PermalinkRapid and large-scale mapping of flood inundation via integrating spaceborne synthetic aperture radar imagery with unsupervised deep learning / Xin Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)
PermalinkApplying planetary mapping methods to submarine environments: onshore-offshore geomorphology of Christiana-Santorini-Kolumbo Volcanic Group, Greece / Alexandra E. Huff in Journal of maps, vol 17 n° 3 (July 2021)
PermalinkDetecting high-temperature anomalies from Sentinel-2 MSI images / Yongxue Liu in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 2021)
PermalinkDynamique contrastée de la compaction d’un ferralsol après une défriche mécanisée alternative en Guyane française / Xavier Guerrini in Bois et forêts des tropiques, n° 348 ([01/07/2021])
PermalinkFeux de forêts et technologies spatiales / Laurent Polidori in Géomètre, n° 2193 (juillet-août 2021)
PermalinkMulti-scale coal fire detection based on an improved active contour model from Landsat-8 satellite and UAV images / Yanyan Gao in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)
PermalinkA compilation of snow cover datasets for Svalbard: A multi-sensor, multi-model study / Hannah Vickers in Remote sensing, vol 13 n°10 (May-2 2021)
PermalinkSNR-based water height retrieval in rivers: Application to high amplitude asymmetric tides in the Garonne river / Pierre Zeiger in Remote sensing, vol 13 n° 9 (May-1 2021)
PermalinkPotentialité des données satellitaires Sentinel-2 pour la cartographie de l’impact des feux de végétation en Afrique tropicale : application au Togo / Yawo Konko in Bois et forêts des tropiques, n° 347 ([02/04/2021])
PermalinkRépartitions spatiale et temporelle des feux à Madagascar / Solofo Rakotondraompiana in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)
PermalinkAttribution of the Australian bushfire risk to anthropogenic climate change / Geert Jan Van Oldenborgh in Natural Hazards and Earth System Sciences, vol 21 n° 3 (March 2021)
PermalinkIntegration of an InSAR and ANN for sinkhole susceptibility mapping: A case study from Kirikkale-Delice (Turkey) / Hakan Nefeslioglu in ISPRS International journal of geo-information, vol 10 n° 3 (March 2021)
PermalinkAn improved rainfall-threshold approach for robust prediction and warning of flood and flash flood hazards / Geraldo Moura Ramos Filho in Natural Hazards, Vol 105 n° 3 (February 2021)
PermalinkA dynamic bidirectional coupled surface flow model for flood inundation simulation / Chunbo Jiang in Natural Hazards and Earth System Sciences, Vol 21 n° 2 (February 2021)
PermalinkA GIS- and AHP-based approach to map fire risk: a case study of Kuan Kreng peat swamp forest, Thailand / Narissara Nuthammachot in Geocarto international, vol 36 n° 2 ([01/02/2021])
PermalinkOptimizing flood mapping using multi-synthetic aperture radar images for regions of the lower mekong basin in Vietnam / Vu Anh Tuan in European journal of remote sensing, vol 54 n° 1 (2021)
PermalinkReclaimed-airport surface-deformation monitoring by improved permanent-scatterer interferometric synthetic-aperture radar: a case study of Shenzhen Bao'an international airport, China / Lu Miao in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 2 (February 2021)
PermalinkGIS-based multicriteria evaluation for earthquake response: a case study of expert opinion in Vancouver, Canada / Blake Byron Walker in Natural Hazards, Vol 105 n° 2 (January 2021)
PermalinkAssessing the accuracy of remotely sensed fire datasets across the southwestern Mediterranean Basin / Luis Felipe Galizia in Natural Hazards and Earth System Sciences, vol 21 n° 1 (January 2021)
PermalinkPermalinkPermalinkDeep learning for wildfire progression monitoring using SAR and optical satellite image time series / Puzhao Zhang (2021)
PermalinkDéveloppement d’outils d’exploitation des archives photographiques aériennes de l’IGN pour caractériser l’évolution pluridécennale du littoral sur l’île de la Réunion / Adinane Oladjidé Ayichemi (2021)
PermalinkDrought propagation and its impact on groundwater hydrology of wetlands: a case study on the Doode Bemde nature reserve (Belgium) / Buruk Kitachew Wossenyeleh in Natural Hazards and Earth System Sciences, vol 21 n° 1 (January 2021)
PermalinkDynamic mechanism of blown sand hazard formation at the Jieqiong section of the Lhasa–Shigatse railway / Shengbo Xie in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)
PermalinkDynamics of inundation events in the rivers-estuaries-ocean continuum in Bengal delta : synergy between hydrodynamic modelling and spaceborne remote sensing / Md Jamal Uddin Kahn (2021)
PermalinkFlood mapping from radar remote sensing using automated image classification techniques / Lisa Landuyt (2021)
PermalinkImpact of forest disturbance on InSAR surface displacement time series / Paula M. Bürgi in IEEE Transactions on geoscience and remote sensing, vol 59 n° 1 (January 2021)
PermalinkModeling the risk of robbery in the city of Tshwane, South Africa / Nicolas Kemp in Cartography and Geographic Information Science, vol 48 n° 1 (January 2021)
PermalinkPermalinkPermalinkDoes recent fire activity impact fire-related traits of Pinus halepensis Mill. and Pinus sylvestris L. in the French Mediterranean area? / Bastien Romero in Annals of Forest Science, vol 77 n° 4 (December 2020)
PermalinkA framework for unsupervised wildfire damage assessment using VHR satellite images with PlanetScope data / Minkyung Chung in Remote sensing, vol 12 n° 22 (December-1 2020)
PermalinkLarge-scale stochastic flood hazard analysis applied to the Po River / A. Curran in Natural Hazards, vol 104 n° 3 (December 2020)
Permalink