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The spatial structure of socioeconomic disadvantage: a Bayesian multivariate spatial factor analysis / Matthew Quick in International journal of geographical information science IJGIS, vol 35 n° 1 (January 2021)
[article]
Titre : The spatial structure of socioeconomic disadvantage: a Bayesian multivariate spatial factor analysis Type de document : Article/Communication Auteurs : Matthew Quick, Auteur ; Hui Luan, Auteur Année de publication : 2021 Article en page(s) : pp 63 - 83 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse multivariée
[Termes IGN] analyse socio-économique
[Termes IGN] classification bayesienne
[Termes IGN] pauvreté
[Termes IGN] quartier
[Termes IGN] revenu
[Termes IGN] structure spatiale
[Termes IGN] TorontoRésumé : (auteur) Neighborhood socioeconomic disadvantage is a measure of socio-spatial inequality that has been shown to be associated with a variety of social, economic, and health outcomes. Existing studies that explore the local patterning of disadvantage often construct composite indices that summarize the interactions between multiple dimensions of social status, but do not consider if, and how, disadvantage exhibits spatial structure. This study applies a Bayesian multivariate factor analytic modeling approach to examine the spatial structure of socioeconomic disadvantage in Toronto, Canada. Socioeconomic disadvantage is modeled as an area-based composite index associated with three variables measuring low income, low-educational attainment, and low occupational status, and a series of models with different assumptions regarding the spatial structure of disadvantage are compared. The best-fitting model shows that the prevalence of low-income households has the strongest positive association with disadvantage and that spatial clustering is three times more important than spatial heterogeneity for explaining the spatial structure of disadvantage. The implications of this study for analyzing multivariate spatial data and for understanding the interactions amongst multiple dimensions of disadvantage are discussed. Numéro de notice : A2021-020 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1759807 Date de publication en ligne : 07/05/2020 En ligne : https://doi.org/10.1080/13658816.2020.1759807 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96519
in International journal of geographical information science IJGIS > vol 35 n° 1 (January 2021) . - pp 63 - 83[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2021011 SL Revue Centre de documentation Revues en salle Disponible Topographic, edaphic and climate influences on aspen (Populus tremuloides) drought stress on an intermountain bunchgrass prairie / Andrew Neary in Forest ecology and management, vol 479 ([01/01/2021])
[article]
Titre : Topographic, edaphic and climate influences on aspen (Populus tremuloides) drought stress on an intermountain bunchgrass prairie Type de document : Article/Communication Auteurs : Andrew Neary, Auteur ; Ricardo Mata-González, Auteur ; Heidi Schmalz, Auteur Année de publication : 2021 Article en page(s) : 12 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de sensibilité
[Termes IGN] climat
[Termes IGN] écophysiologie
[Termes IGN] état du sol
[Termes IGN] facteur édaphique
[Termes IGN] hauteur des arbres
[Termes IGN] humidité du sol
[Termes IGN] manteau neigeux
[Termes IGN] Oregon (Etats-Unis)
[Termes IGN] Poaceae
[Termes IGN] Populus tremuloides
[Termes IGN] prairie
[Termes IGN] série temporelle
[Termes IGN] stress hydrique
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Quaking aspen, Populus tremuloides, has experienced severe declines in recent years in part due to the effects of changing climate and extreme drought. This study set out to investigate these effects by assessing associations of climatic, edaphic and topographic variables with physiological drought stress in aspen. The study took place on the Zumwalt Prairie in northeastern Oregon, a semi-arid bunchgrass prairie where aspen occur in isolated stands associated with riparian areas and late-season persistence of snow drifts. Using a 33-year time series of Landsat imagery to detect associations of aspen stands late-season snow cover and field measurements of soil moisture in aspen stands during 2017, we found while snow dominated stands were associated with greater soil moisture during spring, levels had equilibrated to those of other upland stands by summer. Measurements of predawn and midday stem Ψ in multiple height classes of aspen ramets revealed associations of both shallow soil moisture and vapor pressure deficit with physiological drought stress in aspen. Analysis of soil texture class revealed an important association with midday stem Ψ, with finer textured soils associated with decreased stem Ψ in comparison to coarser textured soils. While neither topographical characteristics nor snow cover were found to be important drivers of drought stress, topographical curvature was found to have a strong influence on summer soil moisture in upland stands. These findings contribute to our understanding of aspen physiology, drought ecology and landscape hydrology toward the xeric margin of aspen’s range. This information can help land managers anticipate and adapt to changing climates and understand their effects on key plant species such as aspen. Numéro de notice : A2021-001 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2020.118530 Date de publication en ligne : 08/09/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118530 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96028
in Forest ecology and management > vol 479 [01/01/2021] . - 12 p.[article]Understanding the geodetic signature of large aquifer systems: Example of the Ozark Plateaus in Central United States / Stacy Larochelle (2021)
Titre : Understanding the geodetic signature of large aquifer systems: Example of the Ozark Plateaus in Central United States Type de document : Article/Communication Auteurs : Stacy Larochelle, Auteur ; Kristel Chanard , Auteur ; Luce Fleitout, Auteur ; Jérôme Nicolas Fortin, Auteur ; Adriano Gualandi, Auteur ; Laurent Longuevergne, Auteur ; Paul Rebischung , Auteur ; Sophie Violette, Auteur ; Jean-Philippe Avouac, Auteur Editeur : Washington DC [Etats-Unis] : Earth and Space Science Open Archive ESSOAr Année de publication : 2021 Projets : 1-Pas de projet / Importance : 29 p. Note générale : bibliographie
soumis au Journal of Geophysical Research - Solid EarthLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] aquifère
[Termes IGN] Arkansas (Etats-Unis)
[Termes IGN] déformation de la croute terrestre
[Termes IGN] élasticité
[Termes IGN] Kansas (Etats-Unis ; état)
[Termes IGN] masse d'eau
[Termes IGN] Missouri (Etats-Unis)
[Termes IGN] Oklahoma (Etats-Unis)
[Termes IGN] série temporelle
[Termes IGN] surcharge hydrologiqueRésumé : (auteur) The continuous redistribution of water mass involved in the hydrologic cycle leads to deformation of the solid Earth. On a global scale, this deformation is well explained by redistribution in surface loading and can be quantified to first order with space-based gravimetric and geodetic measurements. At the regional scale, however, aquifer systems also undergo poroelastic deformation in response to groundwater fluctuations. Disentangling these related but distinct 3D deformation fields from geodetic time series is essential to accurately invert for changes in continental water mass, to understand the mechanical response of aquifers to internal pressure changes as well as to correct time series for these known effects. Here, we demonstrate a methodology to accomplish this task by considering the example of the well-instrumented Ozark Plateaus Aquifer System (OPAS) in central United States. We begin by characterizing the most important sources of signal in the spatially heterogeneous groundwater level dataset using an Independent Component Analysis. Then, to estimate the associated poroelastic displacements, we project geodetic time series corrected for surface loading effects onto orthogonalized versions of the groundwater temporal functions. We interpret the extracted displacements in light of analytical solutions and a 2D model relating groundwater level variations to surface displacements. In particular, the relatively low estimates of elastic moduli inferred from the poroelastic displacements and groundwater fluctuations may be indicative of surficial layers with a high fracture density. Our findings suggest that OPAS undergoes significant poroelastic deformation, including highly heterogeneous horizontal poroelastic displacements. Numéro de notice : P2021-006 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Preprint nature-HAL : Préprint DOI : 10.1002/essoar.10507870.1 Date de publication en ligne : 02/09/2021 En ligne : https://doi.org/10.1002/essoar.10507870.1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98994 Bioclimatic modeling of potential vegetation types as an alternative to species distribution models for projecting plant species shifts under changing climates / Robert E. Keane in Forest ecology and management, vol 477 ([01/12/2020])
[article]
Titre : Bioclimatic modeling of potential vegetation types as an alternative to species distribution models for projecting plant species shifts under changing climates Type de document : Article/Communication Auteurs : Robert E. Keane, Auteur ; Lisa M. Holsinger, Auteur ; Rachel Loehman, Auteur Année de publication : 2020 Article en page(s) : 12 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] carte de la végétation
[Termes IGN] changement climatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] distribution spatiale
[Termes IGN] écosystème
[Termes IGN] espèce végétale
[Termes IGN] habitat forestier
[Termes IGN] modèle de simulation
[Termes IGN] modèle dynamique
[Termes IGN] modélisation de la forêt
[Termes IGN] Montana (Etats-Unis)
[Termes IGN] substitution
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Land managers need new tools for planning novel futures due to climate change. Species distribution modeling (SDM) has been used extensively to predict future distributions of species under different climates, but their map products are often too coarse for fine-scale operational use. In this study we developed a flexible, efficient, and robust method for mapping current and future distributions and abundances of vegetation species and communities at the fine spatial resolutions that are germane to land management. First, we mapped Potential Vegetation Types (PVTs) using conventional statistical modeling techniques (Random Forests) that used bioclimatic ecosystem process and climate variables as predictors. We obtained over 50% accuracy across 13 mapped PVTs for our study area. We then applied future climate projections as climate input to the Random Forest model to generate future PVT maps, and used field data describing the occurrence of tree and non-tree species in each PVT category to model and map species distribution for current and future climate. These maps were then compared to two previous SDM mapping efforts with over 80% agreement and equivalent accuracy. Because PVTs represent the biophysical potential of the landscape to support vegetation communities as opposed to the vegetation that currently exists, they can be readily linked to climate forecasts and correlated with other, climate-sensitive ecological processes significant in land management, such as fire regimes and site productivity. Numéro de notice : A2020-624 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2020.118498 Date de publication en ligne : 18/08/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118498 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96022
in Forest ecology and management > vol 477 [01/12/2020] . - 12 p.[article]Empirical assessment of road network resilience in natural hazards using crowdsourced traffic data / Yi Qiang in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)
[article]
Titre : Empirical assessment of road network resilience in natural hazards using crowdsourced traffic data Type de document : Article/Communication Auteurs : Yi Qiang, Auteur ; Jinwen Xu, Auteur Année de publication : 2020 Article en page(s) : pp 2434 - 2450 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse de groupement
[Termes IGN] données localisées des bénévoles
[Termes IGN] étude empirique
[Termes IGN] Google Maps
[Termes IGN] Ohio (Etats-Unis)
[Termes IGN] participation du public
[Termes IGN] réseau routier
[Termes IGN] résilience écologique
[Termes IGN] risque naturel
[Termes IGN] trafic routierRésumé : (auteur) Climate change and natural hazards pose great threats to road transport systems which are ‘lifelines’ of human society. However, there is generally a lack of empirical data and approaches for assessing resilience of road networks in real hazard events. This study introduces an empirical approach to evaluate road network resilience using crowdsourced traffic data in Google Maps. Based on the conceptualization of resilience and the Hansen accessibility index, resilience of road network is measured from accumulated accessibility reduction over time during a hazard. The utility of this approach is demonstrated in a case study of the Cleveland metropolitan area (Ohio) in Winter Storm Harper. The results reveal strong spatial variations of the disturbance and recovery rate of road network performance during the hazard. The major findings of the case study are: (1) longer distance travels have higher increasing ratios of travel time during the hazard; (2) communities with low accessibility at the normal condition have lower road network resilience; (3) spatial clusters of low resilience are identified, including communities with low socio-economic capacities. The introduced approach provides ground-truth validation for existing quantitative models and supports disaster management and transportation planning to reduce hazard impacts on road network. Numéro de notice : A2020-691 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1694681 Date de publication en ligne : 25/11/2020 En ligne : https://doi.org/10.1080/13658816.2019.1694681 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96229
in International journal of geographical information science IJGIS > vol 34 n° 12 (December 2020) . - pp 2434 - 2450[article]Quantification of cotton water consumption by remote sensing / Jefferson Vieira José in Geocarto international, vol 35 n° 16 ([01/12/2020])PermalinkSTME: An effective method for discovering spatiotemporal multi‐type clusters containing events with different densities / Chao Wang in Transactions in GIS, Vol 24 n° 6 (December 2020)PermalinkUse of remote sensing data to improve the efficiency of National Forest Inventories: A case study from the United States National Forest Inventory / Andrew J. Lister in Forests, vol 11 n° 12 (December 2020)PermalinkAnalysis of the effect of climate warming on paludification processes: Will soil conditions limit the adaptation of Northern boreal forests to climate change? A synthesis / Ahmed Laamrani in Forests, vol 11 n°11 (November 2020)PermalinkEffects of radiometric correction on cover type and spatial resolution for modeling plot level forest attributes using multispectral airborne LiDAR data / Wai Yeung Yan in ISPRS Journal of photogrammetry and remote sensing, vol 169 (November 2020)PermalinkMapping tree species deciduousness of tropical dry forests combining reflectance, spectral unmixing, and texture data from high-resolution imagery / Astrid Helena Huechacona-Ruiz in Forests, vol 11 n°11 (November 2020)PermalinkRiver ice segmentation with deep learning / Abhineet Singh in IEEE Transactions on geoscience and remote sensing, vol 58 n° 11 (November 2020)PermalinkTopographic connection method for automated mapping of landslide inventories, study case: semi urban sub-basin from Monterrey, Northeast of México / Nelly L. Ramirez Serrato in Geocarto international, vol 35 n° 15 ([01/11/2020])PermalinkUsing climate-sensitive 3D city modeling to analyze outdoor thermal comfort in urban areas / Rabeeh Hosseinihaghighi in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)PermalinkVNIR-SWIR superspectral mineral mapping: An example from Cuprite, Nevada / Kathleen E. Johnson in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 11 (November 2020)Permalink