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A 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)
[article]
Titre : A framework for unsupervised wildfire damage assessment using VHR satellite images with PlanetScope data Type de document : Article/Communication Auteurs : Minkyung Chung, Auteur ; Youkyung Han, Auteur ; Yongil Kim, Auteur Année de publication : 2020 Article en page(s) : n° 3835 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aide à la décision
[Termes IGN] classification non dirigée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] Corée du sud
[Termes IGN] détection de changement
[Termes IGN] dommage
[Termes IGN] estimation par noyau
[Termes IGN] flou
[Termes IGN] gestion des risques
[Termes IGN] image à très haute résolution
[Termes IGN] image Geoeye
[Termes IGN] image multibande
[Termes IGN] image PlanetScope
[Termes IGN] incendie de forêt
[Termes IGN] Normalized Difference Vegetation IndexRésumé : (auteur) The application of remote sensing techniques for disaster management often requires rapid damage assessment to support decision-making for post-treatment activities. As the on-demand acquisition of pre-event very high-resolution (VHR) images is typically limited, PlanetScope (PS) offers daily images of global coverage, thereby providing favorable opportunities to obtain high-resolution pre-event images. In this study, we propose an unsupervised change detection framework that uses post-fire VHR images with pre-fire PS data to facilitate the assessment of wildfire damage. To minimize the time and cost of human intervention, the entire process was executed in an unsupervised manner from image selection to change detection. First, to select clear pre-fire PS images, a blur kernel was adopted for the blind and automatic evaluation of local image quality. Subsequently, pseudo-training data were automatically generated from contextual features regardless of the statistical distribution of the data, whereas spectral and textural features were employed in the change detection procedure to fully exploit the properties of different features. The proposed method was validated in a case study of the 2019 Gangwon wildfire in South Korea, using post-fire GeoEye-1 (GE-1) and pre-fire PS images. The experimental results verified the effectiveness of the proposed change detection method, achieving an overall accuracy of over 99% with low false alarm rate (FAR), which is comparable to the accuracy level of the supervised approach. The proposed unsupervised framework accomplished efficient wildfire damage assessment without any prior information by utilizing the multiple features from multi-sensor bi-temporal images. Numéro de notice : A2020-793 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs12223835 Date de publication en ligne : 22/11/2020 En ligne : https://doi.org/10.3390/rs12223835 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96570
in Remote sensing > vol 12 n° 22 (December-1 2020) . - n° 3835[article]Large-scale stochastic flood hazard analysis applied to the Po River / A. Curran in Natural Hazards, vol 104 n° 3 (December 2020)
[article]
Titre : Large-scale stochastic flood hazard analysis applied to the Po River Type de document : Article/Communication Auteurs : A. Curran, Auteur ; Karin De Bruijn, Auteur ; Alessio Domeneghetti, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2027 – 2049 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse des risques
[Termes IGN] digue
[Termes IGN] inondation
[Termes IGN] modèle hydrographique
[Termes IGN] modèle stochastique
[Termes IGN] Pô (plaine)
[Termes IGN] prévention des risques
[Termes IGN] probabilité
[Termes IGN] surveillance hydrologiqueRésumé : (auteur) Reliable hazard analysis is crucial in the flood risk management of river basins. For the floodplains of large, developed rivers, flood hazard analysis often needs to account for the complex hydrology of multiple tributaries and the potential failure of dikes. Estimating this hazard using deterministic methods ignores two major aspects of large-scale risk analysis: the spatial–temporal variability of extreme events caused by tributaries, and the uncertainty of dike breach development. Innovative stochastic methods are here developed to account for these uncertainties and are applied to the Po River in Italy. The effects of using these stochastic methods are compared against deterministic equivalents, and the methods are combined to demonstrate applications for an overall stochastic hazard analysis. The results show these uncertainties can impact extreme event water levels by more than 2 m at certain channel locations, and also affect inundation and breaching patterns. The combined hazard analysis allows for probability distributions of flood hazard and dike failure to be developed, which can be used to assess future flood risk management measures. Numéro de notice : A2020-735 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s11069-020-04260-w Date de publication en ligne : 08/09/2020 En ligne : https://doi.org/10.1007/s11069-020-04260-w Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96350
in Natural Hazards > vol 104 n° 3 (December 2020) . - pp 2027 – 2049[article]Analyzing the joint effect of forest management and wildfires on living biomass and carbon stocks in Spanish forests / Patricia Adame in Forests, vol 11 n°11 (November 2020)
[article]
Titre : Analyzing the joint effect of forest management and wildfires on living biomass and carbon stocks in Spanish forests Type de document : Article/Communication Auteurs : Patricia Adame, Auteur ; Isabel Canellas, Auteur ; Daniel Moreno-Fernández, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 1219 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse
[Termes IGN] Espagne
[Termes IGN] forêt méditerranéenne
[Termes IGN] gestion forestière durable
[Termes IGN] incendie de forêt
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle dynamique
[Termes IGN] politique forestière
[Termes IGN] puits de carbone
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Research Highlights: This is the first study that has considered forest management and wildfires in the balance of living biomass and carbon stored in Mediterranean forests. Background and Objectives: The Kyoto Protocol and Paris Agreement request countries to estimate and report carbon emissions and removals from the forest in a transparent and reliable way. The aim of this study is to forecast the carbon stored in the living biomass of Spanish forests for the period 2000–2050 under two forest management alternatives and three forest wildfires scenarios. Materials and Methods: To produce these estimates, we rely on data from the Spanish National Forest Inventory (SNFI) and we use the European Forestry Dynamics Model (EFDM). SNFI plots were classified according to five static (forest type, known land-use restrictions, ownership, stand structure and bioclimatic region) and two dynamic factors (quadratic mean diameter and total volume). The results were validated using data from the latest SNFI cycle (20-year simulation). Results: The increase in wildfire occurrence will lead to a decrease in biomass/carbon between 2000 and 2050 of up to 22.7% in the medium–low greenhouse gas emissions scenario (B2 scenario) and of up to 32.8% in the medium–high greenhouse gas emissions scenario (A2 scenario). Schoolbook allocation management could buffer up to 3% of wildfire carbon loss. The most stable forest type under both wildfire scenarios are Dehesas. As regards bioregions, the Macaronesian area is the most affected and the Alpine region, the least affected. Our validation test revealed a total volume underestimation of 2.2% in 20 years. Conclusions: Forest wildfire scenarios provide more realistic simulations in Mediterranean forests. The results show the potential benefit of forest management, with slightly better results in schoolbook forest management compared to business-as-usual forest management. The EFDM harmonized approach simulates the capacity of forests to store carbon under different scenarios at national scale in Spain, providing important information for optimal decision-making on forest-related policies. Numéro de notice : A2020-758 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f11111219 Date de publication en ligne : 19/11/2020 En ligne : https://doi.org/10.3390/f11111219 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96471
in Forests > vol 11 n°11 (November 2020) . - n° 1219[article]Bayesian-deep-learning estimation of earthquake location from single-station observations / S. Mostafa Mousavi in IEEE Transactions on geoscience and remote sensing, vol 58 n° 11 (November 2020)
[article]
Titre : Bayesian-deep-learning estimation of earthquake location from single-station observations Type de document : Article/Communication Auteurs : S. Mostafa Mousavi, Auteur ; Gregory C. Beroza, Auteur Année de publication : 2020 Article en page(s) : pp 8211 - 8224 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] apprentissage profond
[Termes IGN] classification bayesienne
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection du signal
[Termes IGN] épicentre
[Termes IGN] estimation bayesienne
[Termes IGN] onde sismique
[Termes IGN] régression
[Termes IGN] séisme
[Termes IGN] station d'observation
[Termes IGN] surveillance géologique
[Termes IGN] temps de propagationRésumé : (auteur) We present a deep-learning method for a single-station earthquake location, which we approach as a regression problem using two separate Bayesian neural networks. We use a multitask temporal convolutional neural network to learn epicentral distance and P travel time from 1-min seismograms. The network estimates epicentral distance and P travel time with mean errors of 0.23 km and 0.03 s and standard deviations of 5.42 km and 0.66 s, respectively, along with their epistemic and aleatory uncertainties. We design a separate multi-input network using standard convolutional layers to estimate the back-azimuth angle and its epistemic uncertainty. This network estimates the direction from which seismic waves arrive at the station with a mean error of 1°. Using this information, we estimate the epicenter, origin time, and depth along with their confidence intervals. We use a global data set of earthquake signals recorded within 1° (~112 km) from the event to build the model and demonstrate its performance. Our model can predict epicenter, origin time, and depth with mean errors of 7.3 km, 0.4 s, and 6.7 km, respectively, at different locations around the world. Our approach can be used for fast earthquake source characterization with a limited number of observations and also for estimating the location of earthquakes that are sparsely recorded—either because they are small or because stations are widely separated. Numéro de notice : A2020-684 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2988770 Date de publication en ligne : 06/05/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2988770 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96209
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 11 (November 2020) . - pp 8211 - 8224[article]Macrozonation of seismic transient and permanent ground deformation of Iran / Saeideh Farahani in Natural Hazards and Earth System Sciences, vol 20 n° 11 (November 2020)
[article]
Titre : Macrozonation of seismic transient and permanent ground deformation of Iran Type de document : Article/Communication Auteurs : Saeideh Farahani, Auteur ; Behrouz Behnam, Auteur ; Ahmad Tahershamsi, Auteur Année de publication : 2020 Article en page(s) : pp 2889 – 2903 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] carte sismologique
[Termes IGN] déformation de la croute terrestre
[Termes IGN] effondrement de terrain
[Termes IGN] faille géologique
[Termes IGN] modèle numérique de surface
[Termes IGN] réflexion (rayonnement)
[Termes IGN] surveillance géologique
[Termes IGN] système d'information géographique
[Termes IGN] zone à risqueRésumé : (auteur) Iran is located on the Alpide earthquake belt, in the active collision zone between the Eurasian and Arabian plates. This issue makes Iran a country that suffers from geotechnical seismic hazards associated with frequent destructive earthquakes. Also, according to the rapid growth of population and demands for construction lifelines, risk assessment studies which should be carried out in order to reduce the probable damages are necessary. The most important destructive effects of earthquakes on lifelines are transient and permanent ground displacements. The availability of the map of the displacements caused by liquefaction, landslide, and surface fault rupture can be a useful reference for researchers and engineers who want to carry out a risk assessment project for each specific region of the country. In this study, these precise maps are produced and presented by using a considerable number of GIS-based analyses and by employing the HAZUS methodology. It is important to note that a required accuracy for risk assessment is approximately around the macro scale. So, in order to produce a suitable map for risk assessment goals, in terms of accuracy, the GIS-based analyses are employed to map all of Iran. Numéro de notice : A2020-712 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/POSITIONNEMENT Nature : Article DOI : 10.5194/nhess-20-2889-2020 Date de publication en ligne : 03/11/2020 En ligne : https://doi.org/10.5194/nhess-20-2889-2020 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96277
in Natural Hazards and Earth System Sciences > vol 20 n° 11 (November 2020) . - pp 2889 – 2903[article]Soil erosion assessment using RUSLE model and its validation by FR probability model / Amiya Gayen in Geocarto international, vol 35 n° 15 ([01/11/2020])PermalinkComparison of tree-based classification algorithms in mapping burned forest areas / Dilek Kucuk Matci in Geodetski vestnik, vol 64 n° 3 (September - November 2020)PermalinkGeo-environment risk assessment in Zhengzhou City, China / Chuanming Ma in Geomatics, Natural Hazards and Risk, vol 11 n° 1 (2020)PermalinkA spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery / Bo Yang in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)PermalinkUse of Bayesian modeling to determine the effects of meteorological conditions, prescribed burn season, and tree characteristics on litterfall of pinus nigra and pinus pinaster stands / Juncal Espinosa in Forests, vol 11 n° 9 (September 2020)PermalinkWater level prediction from social media images with a multi-task ranking approach / P. Chaudhary in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)PermalinkEvaluation of single-frequency receivers for studying crustal deformation at the longitudinal Valley fault, eastern Taiwan / Horng-Yue Chen in Survey review, vol 52 n° 374 (August 2020)PermalinkNear-real time forecasting and change detection for an open ecosystem with complex natural dynamics / Jasper A. Slingsby in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)PermalinkSize dependency of variables influencing fire occurrence in Mediterranean forests of Eastern Spain / Marina Peris-Llopis in European Journal of Forest Research, vol 139 n°4 (August 2020)PermalinkPredicting displacement of bridge based on CEEMDAN-KELM model using GNSS monitoring data / Qian Fan in Journal of applied geodesy, vol 14 n° 3 (July 2020)PermalinkRegionalization of flood magnitudes using the ecological attributes of watersheds / Bahman Jabbarian Amiri in Geocarto international, vol 35 n° 9 ([01/07/2020])PermalinkA web-based spatial decision support system for monitoring the risk of water contamination in private wells / Yu Lan in Annals of GIS, vol 26 n° 3 (July 2020)PermalinkAnalysis of dam deformation with robust weight functions / Berkant Konakoglu in Geodetski vestnik, vol 64 n° 2 (June - August 2020)PermalinkData-driven evidential belief function (EBF) model in exploring landslide susceptibility zones for the Darjeeling Himalaya, India / Subrata Mondal in Geocarto international, Vol 35 n° 8 ([01/06/2020])PermalinkImproved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation / Eslam Ali in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkFusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method / Yuedong Wang in Journal of geodesy, vol 94 n° 5 (May 2020)PermalinkIncorporating Sentinel-1 SAR imagery with the MODIS MCD64A1 burned area product to improve burn date estimates and reduce burn date uncertainty in wildland fire mapping / Kristofer Lasko in Geocarto international, vol 35 n° 6 ([01/05/2020])PermalinkShrub biomass estimates in former burnt areas using Sentinel 2 images processing and classification / Jose Aranha in Forests, vol 11 n° 5 (May 2020)PermalinkTephra mass eruption rate from ground-based X-band and L-band microwave radars during the November 23, 2013, Etna Paroxysm / Frank S. Marzano in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)PermalinkVisualizing when, where, and how fires happen in U.S. parks and protected areas / Nicole C. Inglis in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)Permalink