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Modelling evacuation preparation time prior to floods: A machine learning approach / R. Sreejith in Sustainable Cities and Society, vol 87 (December 2022)
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Titre : Modelling evacuation preparation time prior to floods: A machine learning approach Type de document : Article/Communication Auteurs : R. Sreejith, Auteur ; K.R. Sinimole, Auteur Année de publication : 2022 Article en page(s) : n° 104257 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage automatique
[Termes IGN] chronométrie
[Termes IGN] données spatiotemporelles
[Termes IGN] gestion de crise
[Termes IGN] inondation
[Termes IGN] Kerala (Inde ; état)
[Termes IGN] modèle de simulation
[Termes IGN] plan de prévention des risques
[Termes IGN] questionnaire
[Termes IGN] risque naturel
[Termes IGN] secours d'urgenceRésumé : (auteur) Flooding is a significant hazard responsible for substantial damage and risks to human life worldwide. Effective emergency evacuation to a safer location remains a concern even though the crisis can be predicted and warnings were given. During a calamity, most residents cannot quickly and securely flee. As it is crucial to start evacuation at the right time to have a safe evacuation, this study focuses on a machine learning-based model for predicting a household's evacuation preparation time in the incident of a flood. The study is based on the data collected from flood-affected people from Kerala, India, through a questionnaire. The study indicates that people's demographic, geographical and behavioural aspects, awareness of natural hazards and management are the critical components for improved emergency actions. Further, the article also analysed the characteristics of the respondents and successfully created clusters in which the respondents broadly belong, which will help the rescue team operationalize the evacuation process. Numéro de notice : A2022-819 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scs.2022.104257 Date de publication en ligne : 14/10/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104257 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101986
in Sustainable Cities and Society > vol 87 (December 2022) . - n° 104257[article]Flood 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)
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Titre : Flood mapping using multi-temporal Sentinel-1 SAR images: A case study—Inaouene watershed from Northeast of Morocco Type de document : Article/Communication Auteurs : Brahim Benzougagh, Auteur ; Pierre-Louis Frison , Auteur ; Sarita Gajbhiye Meshram, Auteur ; Larbi Boudad, Auteur ; Abdallah Dridri, Auteur ; Driss Sadkaoui, Auteur ; Khalid Mimich, Auteur ; Khaled Mohamed Khedher, Auteur
Année de publication : 2022 Projets : 3-projet - voir note / Article en page(s) : pp 1481 - 1490 Note générale : bibliographie
This research work was supported by the Deanship of Scientific Research at King Khalid University under Grant number RGP. 2/173/42.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bassin hydrographique
[Termes IGN] cartographie des risques
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] inondation
[Termes IGN] Maroc
[Termes IGN] plan de prévention des risques
[Termes IGN] prévention des risques
[Termes IGN] risque naturelRésumé : (auteur) Natural disasters like floods are happening worldwide. Due to their negative impact on different social, economic and environmental aspects need to monitor and map these phenomena have increased. In fact, to access the zones affected by the flood, we use open source remote sensing (RS) images acquired by optical and radar sensors. Furthermore, we present a method using Sentinel-1 images; we suggest applying Ground Range Detected (GRD) images. For this purpose, pre-processed built and provided by the European Space Agency (ESA), preserved by free software Sentinel Application Platform (SNAP) for data extraction around appropriate demand. Moreover, the principal objective of this article is to assess the capability of Sentinel-1 Synthetic Aperture Radar (SAR) images in order to visualize flood areas in the Inaouene watershed located in north-eastern of Morocco. The origin of this natural hazard is the combination of natural and anthropogenic factors that makes the watershed vulnerable with a sub-annual frequency. The results of this work help decision-makers and managers in the field of natural risk management and land-use planning to implement a strategy and action plan for the protection of the populations and the environment against the negative impact of floods. Numéro de notice : A2022-580 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.1007/s40996-021-00683-y Date de publication en ligne : 18/06/2021 En ligne : https://doi.org/10.1007/s40996-021-00683-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99581
in Iranian Journal of Science and Technology - Transactions of Civil Engineering > vol 46 n° 2 (April 2022) . - pp 1481 - 1490[article]Development 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)
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Titre : Development of earth observational diagnostic drought prediction model for regional error calibration: A case study on agricultural drought in Kyrgyzstan Type de document : Article/Communication Auteurs : Eunbeen Park, Auteur ; Hyun-Woo Jo, Auteur ; Sujong Lee, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 36 - 53 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] changement temporel
[Termes IGN] image Terra-MODIS
[Termes IGN] Indice de précipitations antérieures
[Termes IGN] indice de végétation
[Termes IGN] Kirghizistan
[Termes IGN] message d'alerte
[Termes IGN] modèle de simulation
[Termes IGN] plan de prévention des risques
[Termes IGN] prévision météorologique
[Termes IGN] sécheresseRésumé : (auteur) Drought is a natural disaster that occurs globally and is a main trigger of secondary environmental and socio-economic damages, such as food insecurity, land degradation, and sand-dust storms. As climate change is being accelerated by human activities and environmental changes, both the severity and uncertainties of drought are increasing. In this study, a diagnostic drought prediction model (DDPM) was developed to reduce the uncertainties caused by environmental diversity at the regional level in Kyrgyzstan, by predicting drought with meteorological forecasts and satellite image diagnosis. The DDPM starts with applying a prognostic drought prediction model (PDPM) to 1) estimate future agricultural drought by explaining its relationship with the standardized precipitation index (SPI), an accumulated precipitation anomaly, and 2) compensate for regional variances, which were not reflected sufficiently in the PDPM, by taking advantage of preciseness in the time-series vegetation condition index (VCI), a satellite-based index representing land surface conditions. Comparing the prediction results with the monitored VCI from June to August, it was found that the DDPM outperformed the PDPM, which exploits only meteorological data, in both spatiotemporal and spatial accuracy. In particular, for June to August, respectively, the results of the DDPM (coefficient of determination [R2] = 0.27, 0.36, and 0.4; root mean squared error [RMSE] = 0.16, 0.13, and 0.13) were more effective in explaining the spatial details of drought severity on a regional scale than those of the PDPM (R2 = 0.09, 0.10, and 0.11; RMSE = 0.17, 0.15, and 0.16). The DDPM revealed the possibility of advanced drought assessment by integrating the earth observation big data comprising meteorological and satellite data. In particular, the advantage of data fusion is expected to be maximized in areas with high land surface heterogeneity or sparse weather stations by providing observational feedback to the PDPM. This research is anticipated to support policymakers and technical officials in establishing effective policies, action plans, and disaster early warning systems to reduce disaster risk and prevent environmental and socio-economic damage. Numéro de notice : A2022-132 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/15481603.2021.2012370 Date de publication en ligne : 20/12/2021 En ligne : https://doi.org/10.1080/15481603.2021.2012370 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99720
in GIScience and remote sensing > vol 59 n° 1 (2022) . - pp 36 - 53[article]Size 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)
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Titre : Size dependency of variables influencing fire occurrence in Mediterranean forests of Eastern Spain Type de document : Article/Communication Auteurs : Marina Peris-Llopis, Auteur ; José Ramon Gonzalez-Olabarria, Auteur ; Blas Mola-Yudego, Auteur Année de publication : 2020 Article en page(s) : pp 525 - 537 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] altitude
[Termes IGN] cartographie numérique
[Termes IGN] combinaison linéaire ponderée
[Termes IGN] forêt méditerranéenne
[Termes IGN] fréquence
[Termes IGN] incendie de forêt
[Termes IGN] pente
[Termes IGN] Pinus (genre)
[Termes IGN] plan de prévention des risques
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Fires are among the most damaging disturbances to forests in the Mediterranean area. The study analyses the occurrence and characteristics of forest fires in Eastern Spain (1993–2015) to identify key variables related to burnt forest land, differentiating fires according to their burnt area. Data are retrieved from digital cartography, the Spanish Forest Map and data concerning fires. Based on previous research, the variables included are altitude, slope, aspect, fuel, species, population and road density. The fires are classified in small (5–50 ha), medium (50–500 ha) and large (> 500 ha). Four models are considered to explain the proportion of burnt area based on weighted generalized linear models: a general model and one per size class. The results highlight the different relations of similar variables with fires according to the size. When a single model is considered to explain all area burnt, the relationships are mainly driven by large fires. The larger area is burnt on forests with pine, bushes and small trees, whereas smaller fires tend to occur on lower altitude, low slope, high population and road densities. There are large differences in the variables according to the fire sizes, especially for the presence of pine (negative in the medium fires model but positive for the large fires model) and Pasture (which only explains the small fires). The models can be applied to analyse occurrence by fire size in Mediterranean areas, and the results can help elaborate fire prevention strategies and land-planning schemes. Numéro de notice : A2020-423 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10342-020-01265-9 Date de publication en ligne : 10/02/2020 En ligne : https://doi.org/10.1007/s10342-020-01265-9 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95486
in European Journal of Forest Research > vol 139 n°4 (August 2020) . - pp 525 - 537[article]
Titre : Rainfall erosivity in soil erosion processes Type de document : Monographie Auteurs : Gianni Bellocchi, Éditeur scientifique ; Nazzareno Diodato, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2020 Importance : 148 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-03928-805-2 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Vedettes matières IGN] Végétation et changement climatique
[Termes IGN] aide à la décision
[Termes IGN] bilan hydrique
[Termes IGN] changement climatique
[Termes IGN] érosion hydrique
[Termes IGN] gestion de l'eau
[Termes IGN] modélisation spatiale
[Termes IGN] plan de prévention des risques
[Termes IGN] précipitation
[Termes IGN] risque naturel
[Termes IGN] utilisation du solRésumé : (éditeur) This book gathers recent international research on the association between aggressive rainfall and soil loss and landscape degradation. Different contributions explore these complex relationships and highlight the importance of the spatial patterns of precipitation intensity on land flow under erosive storms, with the support of observational and modelling data. This is a large and multifaceted area of research of growing importance that outlines the challenge of protecting land from natural hazards. The increase in the number of high temporal resolution rainfall records together with the development of new modelling capabilities has opened up new opportunities for the use of large-scale planning and risk prevention methods. These new perspectives should no longer be considered as an independent research topic, but should, above all, support comprehensive land use planning, which is at the core of environmental decision-making and operations. Textbooks such as this one demonstrate the significance of how hydrological science can enable tangible progress in understanding the complexity of water management and its current and future challenges. Note de contenu : 1- Rainfall erosivity in soil erosion processes
2- Estimating current and future rainfall erosivity in Greece using regional climate models and spatial quantile regression forests
3- Evaluation of hydromulches as an erosion control measure using
laboratory-scale experiments
4- Spatial and temporal patterns of rainfall erosivity in the Tibetan plateau
5- Effect of rain peak morphology on runoff and sediment yield in Miyun water source reserve in China
6- Design of a pressurized rainfall simulator for evaluating performance of erosion
control practices
7- Reconstruction of seasonal net erosion in a Mediterranean landscape (Alento River basin, Southern Italy) over the past five decades
8- Raindrop energy impact on the distribution characteristics of splash aggregates of cultivated dark Loessial cores
9- Projected rainfall erosivity over central Asia based on CMIP5 climate modelsNuméro de notice : 25994 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie DOI : 10.3390/books978-3-03928-805-2 En ligne : https://doi.org/10.3390/books978-3-03928-805-2 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96775 Changement climatique et risque inondation / William Halbecq in Géomatique expert, n° 119 (novembre - décembre 2017)
PermalinkGIS-based MCDA–AHP modelling for avalanche susceptibility mapping of Nubra valley region, Indian Himalaya / Satish Kumar in Geocarto international, vol 32 n° 11 (November 2017)
PermalinkPrise en compte des forêts à fonction de protection dans les cartographies réglementaires de prévention des risques naturels : Tour d’horizon européen et recommandations pour la France / Jérôme Liévois in Rendez-vous techniques, n° 51-52 (printemps - été 2016)
PermalinkPermalinkPermalinkPermalinkLa cartographie cognitive appliquée dans le domaine du risque géologique / H. Mansour in Bulletin des sciences géographiques, n° 27 (juin 2012)
PermalinkPermalinkSIG et LiDAR pour la réalisation de plans de prévention du risque de chute de blocs : Application dans les alpes françaises / Nicolas Clouet in Géomatique expert, n° 82 (01/09/2011)
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