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Modeling transit-assisted hurricane evacuation through socio-spatial networks / Yan Yang in International journal of geographical information science IJGIS, vol 35 n° 12 (December 2021)
[article]
Titre : Modeling transit-assisted hurricane evacuation through socio-spatial networks Type de document : Article/Communication Auteurs : Yan Yang, Auteur ; Sara Metcalf, Auteur ; Liang Mao, Auteur Année de publication : 2021 Article en page(s) : pp 2424 - 2441 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] comportement
[Termes IGN] Floride (Etats-Unis)
[Termes IGN] gestion de crise
[Termes IGN] modèle de simulation
[Termes IGN] modèle orienté agent
[Termes IGN] réseau social
[Termes IGN] système multi-agents
[Termes IGN] tempête
[Termes IGN] trafic routier
[Termes IGN] transport publicRésumé : (auteur) Increasing intensity and frequency of hurricane events underscores the need for efficient and inclusive evacuation plans, particularly for carless and disabled populations. Hurricane evacuation intrinsically involves both social and spatial processes. People’s decision to evacuate spreads over social networks; once their decisions are made, they flee through spatial transportation networks. This article describes a novel effort to integrate socio-spatial networks into an agent-based evacuation simulation model, taking the Florida Keys in the USA as a study area. In the model, households, as agents, were synthesized from Census data, then connected by a ‘home-workplace-neighborhood’ social network, and registered to a spatial road network. A threshold decision model was used to simulate social contagion of households’ decision to evacuate. The resulting travel demands were input into the TRANSIMS platform to generate on-road traffic. The model analyzed scenarios of automobile-only and public transit-assisted evacuation. The results show that the simulated traffic under the automobile-only scenario aligns with the observed traffic dynamics, which validates our socio-spatially integrated model. Adding public transportation capacity significantly reduces the traffic load and evacuation time, and provides a practical, accessible, and equitable route to safety for low mobility populations. Numéro de notice : A2021-874 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1828590 Date de publication en ligne : 02/10/2020 En ligne : https://doi.org/10.1080/13658816.2020.1828590 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99137
in International journal of geographical information science IJGIS > vol 35 n° 12 (December 2021) . - pp 2424 - 2441[article]Modelling bark volume for six commercially important tree species in France: assessment of models and application at regional scale / Rodolphe Bauer in Annals of Forest Science, vol 78 n° 4 (December 2021)
[article]
Titre : Modelling bark volume for six commercially important tree species in France: assessment of models and application at regional scale Type de document : Article/Communication Auteurs : Rodolphe Bauer, Auteur ; Antoine Billard, Auteur ; Frédéric Mothe, Auteur ; Fleur Longuetaud, Auteur ; Mojtaba Houballah, Auteur ; Alain Bouvet, Auteur ; Henri E. Cuny , Auteur ; Antoine Colin , Auteur ; Francis Colin, Auteur Année de publication : 2021 Projets : ARBRE / AgroParisTech (2007 -), EMERGE / Deleuze, Christine Article en page(s) : n° 104 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba
[Termes IGN] biomasse forestière
[Termes IGN] Bourgogne Franche-Comté (région 2016)
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] écorce
[Termes IGN] Fagus sylvatica
[Termes IGN] Grand Est (région 2016)
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] modèle statistique
[Termes IGN] Picea abies
[Termes IGN] Pseudotsuga menziesii
[Termes IGN] Quercus pedunculata
[Termes IGN] Quercus sessiliflora
[Termes IGN] volume (grandeur)
[Vedettes matières IGN] Economie forestièreRésumé : (auteur) Key message : A set of models of bark thickness at breast height and bark volume are now available for six species in France. A common model suitable for predicting bark volume was proposed for all species. A small but significant altitude effect on bark thickness at breast height was detected for three species.
Context : The growing demand for wood energy and bio-molecules requires a thorough evaluation of forest biomass, particularly bark.
Aims : The objective of this study is to have statistical models of bark volumes for the six main forest species present in North-Eastern France and to be able to estimate regional bark biomasses and quantities of chemical extractives at regional scale.
Methods : A large databank gathering bark thickness measured at different heights in France was used for selecting literature or new alternative models of tree bark volume. These models were applied to the available forest inventory data from North-Eastern France to estimate the regional bark volume. Secondly, by multiplying these volumes by basic density data and extractive content recently obtained, bark biomasses and extractives quantities were deduced.
Results : The first results consist in a set of species-specific models of bark thickness at breast height with R2 around 0.70 and a relative RMSE around 30% which is an improvement of 0.1 for R2 and of 1–2% for relative RMSE depending on the species compared to the best models from the literature. The second results consist in a set of species-specific models of tree bark volumes with R2 of 0.90 and a relative RMSE which varies between 22% when bark thickness at breast height is included and 40% when it is predicted. A significant relationship between bark thickness at breast height and altitude was also observed. The bark resources of Grand Est and Bourgogne-Franche-Comté regions were estimated at 558 000 m3/year and 611 000 m3/year respectively representing between 5.5% and 15% of the stem volume depending on the species. The propagation of the measurement error of bark gauge was estimated at 5% for model of bark thickness at breast height and 24% for bark volume model.
Conclusion : These results constitute an important contribution for a better knowledge of the bark resource at a regional scale and may help to optimise bark valuation by the forest-wood sector.Numéro de notice : A2021-909 Affiliation des auteurs : IGN+Ext (2020- ) Thématique : FORET/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-021-01096-7 Date de publication en ligne : 02/01/2022 En ligne : https://doi.org/10.1007/s13595-021-01096-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99458
in Annals of Forest Science > vol 78 n° 4 (December 2021) . - n° 104[article]Modelling the impact of climate change on the occurrence of frost damage in Sitka spruce (Picea sitchensis) in Great Britain / A.A. Atucha-Zamkova in Forestry, an international journal of forest research, vol 94 n° 5 (December 2021)
[article]
Titre : Modelling the impact of climate change on the occurrence of frost damage in Sitka spruce (Picea sitchensis) in Great Britain Type de document : Article/Communication Auteurs : A.A. Atucha-Zamkova, Auteur ; K.A. Steele, Auteur ; A.R. Smith, Auteur Année de publication : 2021 Article en page(s) : p 664 - 676 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] changement climatique
[Termes IGN] cycle climatique
[Termes IGN] gelée
[Termes IGN] Grande-Bretagne
[Termes IGN] historique des données
[Termes IGN] modèle de simulation
[Termes IGN] phénologie
[Termes IGN] Picea sitchensis
[Termes IGN] température
[Termes IGN] variation saisonnière
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Climate change is predicted to increase temperature and seasonal temperature variance in Great Britain (GB). Sitka spruce (Picea sitchensis (Bong.) Carr) is the most important tree species used in commercial plantations throughout Europe and GB. Frosts that occur outside the winter dormancy period can negatively affect trees, since they happen after dehardening. Damage can be especially severe at bud burst, before emerging needles mature and form protective barriers. Here, we modelled the impact of climate change on frost sensitivity in Sitka spruce with temperature data from five climate projections. The UKCP09 climate model HadRm3 uses emission scenario SRESA1B for the years 2020–2099. The global and downscaled versions of the UKCP18 HadGem3 model use the emissions scenario RCP 8.5. The global model CMCC-CM uses the RCP 4.5 and RCP 8.5 emissions scenarios. The predictions based on these models were compared with results from gridded historical data for the period 1960–2015. Three indicators that assessed the frost sensitivity of Sitka spruce were explored: the total number of frosts between the onset of dehardening and the end of summer, which use three different temperature thresholds (Index 10°C, 1–3°C, 1–5°C); the total number of frosts after bud burst (Index 2); the number of days with minimum temperatures below the resistance level (backlashes) during the hardening–dehardening period (September–August) (Index 3). The indices were validated with historical data for frost damage across GB, and Index 1–3°C, Index 1–5°C and Index 3 were shown to be significantly correlated. The frequency of all frosts and backlashes is expected to decrease with climate change, especially under higher emissions scenarios. Post-bud burst frosts have been historically very rare in GB and remain so with climate change. Downscaled regional climate models detect geographic variability within GB and improve prediction of overall trends in frost damage in comparison to global climate change models for GB. Numéro de notice : A2021-825 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1093/forestry/cpab020 Date de publication en ligne : 17/05/2021 En ligne : https://doi.org/10.1093/forestry/cpab020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98944
in Forestry, an international journal of forest research > vol 94 n° 5 (December 2021) . - p 664 - 676[article]Multi-model estimation of forest canopy closure by using red edge bands based on Sentinel-2 images / Yiying Hua in Forests, vol 12 n° 12 (December 2021)
[article]
Titre : Multi-model estimation of forest canopy closure by using red edge bands based on Sentinel-2 images Type de document : Article/Communication Auteurs : Yiying Hua, Auteur ; Xuesheng Zhao, Auteur Année de publication : 2021 Article en page(s) : n° 1768 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] bande infrarouge
[Termes IGN] coefficient de corrélation
[Termes IGN] couvert forestier
[Termes IGN] détection de contours
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] indice de végétation
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] modèle statistique
[Termes IGN] Mongolie intérieure (Chine)
[Termes IGN] régression
[Termes IGN] surveillance de la végétationRésumé : (auteur) In remote sensing, red edge bands are important indicators for monitoring vegetation growth. To examine the application potential of red edge bands in forest canopy closure estimation, three types of commonly used models—empirical statistical models (multiple stepwise regression (MSR)), machine learning models (back propagation neural network (BPNN)) and physical models (Li–Strahler geometric-optical (Li–Strahler GO) models)—were constructed and verified based on Sentinel-2 data, DEM data and measured data. In addition, we set up a comparative experiment without red edge bands. The relative error (ER) values of the BPNN model, MSR model, and Li–Strahler GO model with red edge bands were 16.97%, 20.76% and 24.83%, respectively. The validation accuracy measures of these models were higher than those of comparison models. For comparative experiments, the ER values of the MSR, Li–Strahler GO and BPNN models were increased by 13.07%, 4% and 1.22%, respectively. The experimental results demonstrate that red edge bands can effectively improve the accuracy of forest canopy closure estimation models to varying degrees. These findings provide a reference for modeling and estimating forest canopy closure using red edge bands based on Sentinel-2 images. Numéro de notice : A2021-125 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f12121768 Date de publication en ligne : 14/12/2021 En ligne : https://doi.org/10.3390/f12121768 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99318
in Forests > vol 12 n° 12 (December 2021) . - n° 1768[article]Understanding and predicting the spatio-temporal spread of COVID-19 via integrating diffusive graph embedding and compartmental models / Tong Zhang in Transactions in GIS, vol 25 n° 6 (December 2021)
[article]
Titre : Understanding and predicting the spatio-temporal spread of COVID-19 via integrating diffusive graph embedding and compartmental models Type de document : Article/Communication Auteurs : Tong Zhang, Auteur ; Jing Li, Auteur Année de publication : 2021 Article en page(s) : pp 3025 - 3047 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage profond
[Termes IGN] Colorado (Etats-Unis)
[Termes IGN] données spatiotemporelles
[Termes IGN] épidémie
[Termes IGN] maladie virale
[Termes IGN] mobilité territoriale
[Termes IGN] modèle de simulation
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] outil d'aide à la décision
[Termes IGN] quartier
[Termes IGN] réseau de transport
[Termes IGN] risque sanitaire
[Termes IGN] surveillance sanitaireRésumé : (Auteur) In order to find useful intervention strategies for the novel coronavirus (COVID-19), it is vital to understand how the disease spreads. In this study, we address the modeling of COVID-19 spread across space and time, which facilitates understanding of the pandemic. We propose a hybrid data-driven learning approach to capture the mobility-related spreading mechanism of infectious diseases, utilizing multi-sourced mobility and attributed data. This study develops a visual analytic approach that identifies and depicts the strength of the transmission pathways of COVID-19 between areal units by integrating data-driven deep learning and compartmental epidemic models, thereby engaging stakeholders (e.g., public health officials, managers from transportation agencies) to make informed intervention decisions and enable public messaging. A case study in the state of Colorado, USA was performed to demonstrate the applicability of the proposed transmission modeling approach in understanding the spatio-temporal spread of COVID-19 at the neighborhood level. Transmission path maps are presented and analyzed, demonstrating their utility in evaluating the effects of mitigation measures. In addition, integrated embeddings also support daily prediction of infected cases and role analysis of each area unit during the transmission of the virus. Numéro de notice : A2021-932 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12803 Date de publication en ligne : 16/07/2021 En ligne : https://doi.org/10.1111/tgis.12803 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99447
in Transactions in GIS > vol 25 n° 6 (December 2021) . - pp 3025 - 3047[article]What is the impact of tectonic plate movement on country size? A long-term forecast / Kamil Maciuk in Remote sensing, vol 13 n° 23 (December-1 2021)PermalinkThe spatiotemporal implications of urbanization for urban heat islands in Beijing: A predictive approach based on CA–Markov modeling (2004–2050) / Muhammad Amir Siddique in Remote sensing, vol 13 n° 22 (November-2 2021)PermalinkA comparison of a gradient boosting decision tree, random forests, and artificial neural networks to model urban land use changes: the case of the Seoul metropolitan area / Myung-Jin Jun in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)PermalinkSemi-automatic extraction of rural roads under the constraint of combined geometric and texture features / Hai Tan in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)PermalinkLandslide susceptibility prediction based on image semantic segmentation / Bowen Du in Computers & geosciences, vol 155 (October 2021)PermalinkLeast squares adjustment with a rank-deficient weight matrix and Its applicability to image/Lidar data processing / Radhika Ravi in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)PermalinkOn determination of the geoid from measured gradients of the Earth's gravity field potential / Pavel Novák in Earth-Science Reviews, vol 221 (October 2021)PermalinkPredicting total electron content in ionosphere using vector autoregression model during geomagnetic storm / Sumitra Iyer in Journal of applied geodesy, vol 15 n° 4 (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)PermalinkAssessment and prediction of urban growth for a mega-city using CA-Markov model / Veerendra Yadav in Geocarto international, vol 36 n° 17 ([15/09/2021])Permalink