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Spatial mining of migration patterns from web demographics / T. Edwin Chow in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)
[article]
Titre : Spatial mining of migration patterns from web demographics Type de document : Article/Communication Auteurs : T. Edwin Chow, Auteur ; Ryan T. Schuermann, Auteur ; Anne H. Ngu, Auteur ; Khila R. Dahal, Auteur Année de publication : 2018 Article en page(s) : pp 1977 - 1998 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse multiéchelle
[Termes IGN] arbre de décision
[Termes IGN] coût
[Termes IGN] données démographiques
[Termes IGN] exploration de données géographiques
[Termes IGN] migration humaine
[Termes IGN] qualité des données
[Termes IGN] Texas (Etats-Unis)
[Termes IGN] Viet NamRésumé : (Auteur) Volunteered Geographic Information, social media, and data from Information and Communication Technology are emerging sources of big data that contribute to the development and understanding of the spatiotemporal distribution of human population. However, the inherent anonymity of these crowd-sourced or crowd-harvested data sources lack the socioeconomic and demographic attributes to examine and explain human mobility and spatiotemporal patterns. In this paper, we investigate an Internet-based demographic data source, personal microdata databases publicly accessible on the World Wide Web (hereafter web demographics), as potential sources of aspatial and spatiotemporal information regarding the landscape of human dynamics. The objectives of this paper are twofold: (1) to develop an analytical framework to identify mobile population from web demographics as an individual-level residential history data, and (2) to explore their geographic and demographic patterns of migration. Using web demographics of Vietnamese–Americans in Texas collected in 2010 as a case study, this paper (1) addresses entity resolution and identifies mobile population through the application of a Cost-Sensitive Alternative Decision Tree (CS-ADT) algorithm, (2) investigates migration pathways and clusters to include both short- and long-distance patterns, and (3) analyze the demographic characteristics of mobile population and the functional relationship with travel distance. By linking the physical space at the individual level, this unique methodology attempts to enhance the understanding of human movement at multiple spatial scales. Numéro de notice : A2018-309 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1470633 Date de publication en ligne : 08/05/2018 En ligne : https://doi.org/10.1080/13658816.2018.1470633 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90466
in International journal of geographical information science IJGIS > vol 32 n° 9-10 (September - October 2018) . - pp 1977 - 1998[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018051 RAB Revue Centre de documentation En réserve L003 Disponible Digital aerial photogrammetry for assessing cumulative spruce budworm defoliation and enhancing forest inventories at a landscape-level / Tristan R.H. Goodbody in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)
[article]
Titre : Digital aerial photogrammetry for assessing cumulative spruce budworm defoliation and enhancing forest inventories at a landscape-level Type de document : Article/Communication Auteurs : Tristan R.H. Goodbody, Auteur ; Nicholas C. Coops, Auteur ; Txomin Hermosilla, Auteur ; Piotr Tompalski, Auteur ; Grant MacCartney, Auteur ; David A. MacLean, Auteur Année de publication : 2018 Article en page(s) : pp 1 - 11 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] défoliation
[Termes IGN] dégradation de la flore
[Termes IGN] échantillonnage d'image
[Termes IGN] insecte nuisible
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] méthode des moindres carrés
[Termes IGN] Ontario (Canada)
[Termes IGN] photogrammétrie aérienne
[Termes IGN] photogrammétrie numérique
[Termes IGN] Picea abies
[Termes IGN] régression linéaire
[Termes IGN] semis de points
[Termes IGN] surface terrière
[Termes IGN] surveillance forestière
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Spruce budworm (Choristoneura fumiferana [Clem.], Lepidoptera: Tortricidae) is a native defoliating insect with an important disturbance role in the eastern boreal forests of North America. With an extensive history of outbreaks and associated impacts on forest structural changes and timber supply, the mapping of spruce budworm defoliation has been of major management importance. In this study we assessed the ability of high spatial resolution digital aerial photogrammetric (DAP) data to predict cumulative defoliation as well as basal area and merchantable volume in spruce budworm host stands in the Gordon Cosens Forest south of Kapuskasing, Ontario, Canada. To do so, DAP derived structural and spectral metrics were incorporated to implement a stratified sampling design to improve the efficiency and cost-effectiveness of field surveying. Standard forest inventory measurements including diameter and height, as well as ocular and branch level defoliation assessments were undertaken on thirty 400 m2 radius plots. A partial least squares analysis was performed to determine whether structural metrics from a DAP point cloud could be influenced by spruce budworm defoliation, as well as determine the relative effectiveness of spectral (e.g. mean NDVI) vs. structural (e.g. 90th percentile of height) metrics, or their combination, for predicting cumulative defoliation. Results indicated that spectral metrics were the most effective for predicting cumulative defoliation (R2 = 0.79), while structural metrics were the least effective (R2 = 0.49). Metrics characterizing variance of the spectral values were found to be the most important predictors. Structural metrics and linear regression were also used to estimate landscape-level volume and basal area per hectare yielding R2 = 0.80 and R2 = 0.90, respectively. Outcomes of this analysis indicate that DAP-derived spectral metrics were more capable of modeling cumulative defoliation, while structural metrics were effective for landscape-level estimations of standard forest inventory attributes. This analysis indicated that the provision of both spectral and structural metrics from a single aerial imagery survey has potential to enhance defoliation monitoring and forest attribute modeling at a landscape-level. Numéro de notice : A2018-290 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.05.012 Date de publication en ligne : 01/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.05.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90408
in ISPRS Journal of photogrammetry and remote sensing > vol 142 (August 2018) . - pp 1 - 11[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018083 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018082 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Exploring uncertainties in terrain feature extraction across multi-scale, multi-feature, and multi-method approaches for variable terrain / Boleslo E. Romero in Cartography and Geographic Information Science, Vol 45 n° 5 (August 2018)
[article]
Titre : Exploring uncertainties in terrain feature extraction across multi-scale, multi-feature, and multi-method approaches for variable terrain Type de document : Article/Communication Auteurs : Boleslo E. Romero, Auteur ; Keith C. Clarke, Auteur Année de publication : 2018 Article en page(s) : pp 381 - 399 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] crète (ligne)
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] géomorphométrie
[Termes IGN] incertitude géométrique
[Termes IGN] modèle numérique de surface
[Termes IGN] réseau hydrographique
[Termes IGN] talwegRésumé : (Auteur) Terrain analysis uses different workflows to extract features from terrain models for the purpose of understanding topographic patterns and processes. However, the results of different workflows often conflict, leading to uncertainties about feature locations. Instead of relying upon a single workflow, we suggest that a fusion of information from multiple workflows better informs terrain analysis. From terrain data with different degrees of variability, we extracted terrain features related to the set of topographic surface network feature classes {peaks, pits, saddles, ridges, courses} using workflows from free, open-source, and commercial software. A multi-scale analysis produced terrain features with fuzzy membership values for various feature classes and revealed that terrain locations can exhibit characteristics of all classes. Multi-feature maps were created by determining at each location the dominant and second-ranked features, and an uncertainty value. Our multi-method approach incorporated all of the workflows’ multi-scale results and again produced multi-feature maps that increased the confidence of some features and reduced the signal of dissimilar results. We also found that high variability terrain produced crisper features in both spatial extent and membership strength. Our overall conclusion is that multi-scale, multi-feature, and multi-method analyses clarify terrain feature uncertainty. Numéro de notice : A2018-259 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2017.1335235 Date de publication en ligne : 18/07/2017 En ligne : https://doi.org/10.1080/15230406.2017.1335235 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90332
in Cartography and Geographic Information Science > Vol 45 n° 5 (August 2018) . - pp 381 - 399[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2018051 RAB Revue Centre de documentation En réserve L003 Disponible Incorporating crown shape information for identifying ash tree species / Haijian Liu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 8 (août 2018)
[article]
Titre : Incorporating crown shape information for identifying ash tree species Type de document : Article/Communication Auteurs : Haijian Liu, Auteur ; Changshan Wu, Auteur Année de publication : 2018 Article en page(s) : pp 495 - 503 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Fraxinus (genre)
[Termes IGN] fusion de données
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Milwaukee
[Termes IGN] photo-interprétation assistée par ordinateur
[Termes IGN] zone urbaineRésumé : (Auteur) Identifying ash trees from other common deciduous trees is challenging due to subtle spectral differences of foliage among species. Although many researchers have integrated lidar-derived tree height and crown size metrics to improve tree species classification accuracy, these simple biophysical attributes provide inadequate explanatory power in distinguishing ash trees (Fraxinus, spp.) in urban ecosystems. To address this issue, shape-related features, including crown shape index (SI) and coefficient of variation (CV) of crown height, were extracted from lidar data, and fused with treetopbased spectra for ash tree species identification in Milwaukee City, Wisconsin, United States. Analysis results indicate shape features including SI and CV play a big role in improving the accuracy for ash tree identification. Specifically, Fusion of CV and treetop-based spectra improved the overall accuracy from 81.9 percent to 89 percent, and McNemar tests indicated the differences in accuracy between CV fusion and tree height fusion was statistically significant (p = 0.016). Numéro de notice : A2018-360 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.8.495 Date de publication en ligne : 01/08/2018 En ligne : https://doi.org/10.14358/PERS.84.8.495 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90600
in Photogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 8 (août 2018) . - pp 495 - 503[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2018081 RAB Revue Centre de documentation En réserve L003 Disponible Intra-annual phenology for detecting understory plant invasion in urban forests / Kunwar K. Singh in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)
[article]
Titre : Intra-annual phenology for detecting understory plant invasion in urban forests Type de document : Article/Communication Auteurs : Kunwar K. Singh, Auteur ; Yin-Hsuen Chen, Auteur ; Lindsey Smart, Auteur ; Josh Gray, Auteur ; Ross K. Meentemeyer, Auteur Année de publication : 2018 Article en page(s) : pp 151 - 161 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Caroline du Nord (Etats-Unis)
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] densité de la végétation
[Termes IGN] détection d'anomalie
[Termes IGN] espèce exotique envahissante
[Termes IGN] flore urbaine
[Termes IGN] forêt tempérée
[Termes IGN] image Landsat-TM
[Termes IGN] indice de végétation
[Termes IGN] Ligustrum sinense
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] phénologie
[Termes IGN] protection de la biodiversité
[Termes IGN] surveillance forestièreRésumé : (Auteur) Accurate and repeatable mapping of biological plant invasions is essential to develop successful management strategies for conserving native biodiversity. While overstory invasive plants have been successfully detected and mapped using multiple methods, understory invasive detection remains a challenge, particularly in dense forested environments. Very few studies have utilized an approach that identifies and aligns the acquisition timing of remote sensing imagery with peak phenological differences between understory and overstory vegetation types. We investigated this opportunity by analyzing a monthly time-series of 2011 Landsat TM data to identify acquisition periods with the highest phenological differences between understory and overstory vegetation for detecting the spatial distribution of the exotic understory plant Ligustrum sinense Lour., a rapidly spreading invader in urbanizing regions of the southeastern United States. We used vegetation indices (VI) to establish intra-annual phenological trends for L. sinense, evergreen forest, and deciduous forest located in Mecklenburg County, North Carolina, USA. We developed Random Forest (RF) models to detect L. sinense from those time steps exhibiting the highest phenological differences. We assessed the relative contribution of VI and topographic indices (TI) to the detection of L. sinense. We compared the top performing models and used the best overall model to produce a map of L. sinense for the study area. RF models that included VI, TI, and Landsat TM bands for March 13 and 29, 2011 (the periods with highest detected phenological differences), produced the highest overall accuracy and Kappa estimates, outperforming the combination of VI and TI by 8.5% in accuracy and 20.5% in Kappa. The top performing model from the RF produced a Kappa of 0.75. Our findings suggest that selecting remote sensing data for a period when phenological differences between L. sinense and forest types are at their peak can improve the detection and mapping of L. sinense. Numéro de notice : A2018-293 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.05.023 Date de publication en ligne : 15/06/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.05.023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90411
in ISPRS Journal of photogrammetry and remote sensing > vol 142 (August 2018) . - pp 151 - 161[article]Réservation
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