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Near-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)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 166 (August 2020) . - pp 15 - 25 Titre : Near-real time forecasting and change detection for an open ecosystem with complex natural dynamics Type de document : Article/Communication Auteurs : Jasper A. Slingsby, Auteur ; Glenn R. Moncrieff, Auteur ; Adam M. Wilson, Auteur Année de publication : 2020 Article en page(s) : pp 15 - 25 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] approche hiérarchique [Termes descripteurs IGN] biodiversité [Termes descripteurs IGN] classification bayesienne [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] écosystème [Termes descripteurs IGN] incendie [Termes descripteurs IGN] internet interactif [Termes descripteurs IGN] Le Cap [Termes descripteurs IGN] milieu naturel [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] surveillance de la végétation [Termes descripteurs IGN] surveillance écologique Résumé : (auteur) Managing fire, water, biodiversity and carbon stocks can greatly benefit from early warning of changes in the state of vegetation. While near-real time tools to detect forest change based on satellite remote sensing exist, these ecosystems have relatively stable natural vegetation dynamics. Open (i.e. non-forest) ecosystems like grasslands, savannas and shrublands are more challenging as they show complex natural dynamics due to factors such as fire, postfire recovery, greater contribution of bare soil to observed vegetation indices, as well as high sensitivity to rainfall and strong seasonality. Tools to aid the management of open ecosystems are desperately required as they dominate much of the globe and harbour substantial biodiversity and carbon. We present an innovative approach that overcomes the difficulties posed by open ecosystems by using a spatio-temporal hierarchical Bayesian model that uses data on climate, topography, soils and fire history to generate ecological forecasts of the expected land surface signal under natural conditions. This allows us to monitor and detect abrupt or gradual changes in the state of an ecosystem in near-real time by identifying areas where the observed vegetation signal has deviated from the expected natural variation. We apply our approach to a case study from the hyperdiverse fire-dependent African shrubland, the fynbos of the Cape Floristic Region, a Global Biodiversity Hotspot and UNESCO World Heritage Site that faces a number of threats to vegetation health and ecosystem function. The case study demonstrates that our approach is useful for identifying a range of change agents such as fire, alien plant species invasions, drought, pathogen outbreaks and clearing of vegetation. We describe and provide our full workflow, including an interactive web application. Our approach is highly versatile, allowing us to collect data on the impacts of change agents for research in ecology and earth system science, and to predict aspects of ecosystem structure and function such as biomass, fire return interval and the influence of vegetation on hydrology Numéro de notice : A2020-349 Thématique : BIODIVERSITE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.05.017 date de publication en ligne : 05/06/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.05.017 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95231 [article]

Learning evolving user’s behaviors on location-based social networks / Ruizhi Wu in Geoinformatica [en ligne], vol 24 n° 3 (July 20202)  

Public [article]  inGeoinformatica [en ligne] > vol 24 n° 3 (July 20202) . - pp 713 – 743 Titre : Learning evolving user’s behaviors on location-based social networks Type de document : Article/Communication Auteurs : Ruizhi Wu, Auteur ; Guangchun Luo, Auteur ; Qi jin, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 713 – 743 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] comportement [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] filtrage d'information [Termes descripteurs IGN] géopositionnement [Termes descripteurs IGN] interaction homme-milieu [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] réseau social géodépendant [Termes descripteurs IGN] utilisateur Résumé : (auteur) With the popularity of smart phones, users’ activities on location-based social networks (LBSNs) evolve faster than traditional social networks. Existing models focus on modeling users’ long-term preferences, leveraging social collaborative filtering to enhance prediction performance. However, the dynamic mobility mechanism of user’s check-in behaviors on LBSNs is seldom considered. In this paper, we propose a new dynamic model that considers both geo-aware user preferences and the social interaction excitation arising from social connections to learn the dynamic mobility mechanism of user’s behaviors on LBSNs. Geo-aware location features, such as semantic features, latent features and dynamic features, are utilized to characterize the location information and reveal the evolution of the geographical impact of location. These geo-aware location features enable us to exploit user’s personal preferences. Meanwhile, we integrate a user’s social connections and friends’ preferences for modeling social interaction excitations. Finally, we jointly incorporate geo-aware user preference learning and social interaction excitation modeling to create a conditional intensity function for temporal point processes with which to explore the dynamic mobility mechanism of evolving user’s check-in behaviors on LBSNs. Extensive experiments on several real-world check-in datasets confirm that our proposed algorithm performs better than existing state-of-the-art methods. Numéro de notice : A2020-372 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00400-3 date de publication en ligne : 16/03/2020 En ligne : https://doi.org/10.1007/s10707-020-00400-3 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95267 [article]

Fine-scale dasymetric population mapping with mobile phone and building use data based on grid Voronoi method / Zhenzhong Peng in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 16 p. Titre : Fine-scale dasymetric population mapping with mobile phone and building use data based on grid Voronoi method Type de document : Article/Communication Auteurs : Zhenzhong Peng, Auteur ; Ru Wang, Auteur ; Lingbo Liu, Auteur ; Hao Wu, Auteur Année de publication : 2020 Article en page(s) : 16 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes descripteurs IGN] bati [Termes descripteurs IGN] densité de population [Termes descripteurs IGN] diagramme de Voronoï [Termes descripteurs IGN] distribution spatiale [Termes descripteurs IGN] données démographiques [Termes descripteurs IGN] espace urbain [Termes descripteurs IGN] modèle de régression [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] petite échelle [Termes descripteurs IGN] régression géographiquement pondérée [Termes descripteurs IGN] téléphone intelligent Résumé : (auteur) Fine-scale population mapping is of great significance for capturing the spatial and temporal distribution of the urban population. Compared with traditional census data, population data obtained from mobile phone data has high availability and high real-time performance. However, the spatial distribution of base stations is uneven, and the service boundaries remain uncertain, which brings significant challenges to the accuracy of dasymetric population mapping. This paper proposes a Grid Voronoi method to provide reliable spatial boundaries for base stations and to build a subsequent regression based on mobile phone and building use data. The results show that the Grid Voronoi method gives high fitness in building use regression, and further comparison between the traditional ordinary least squares (OLS) regression model and geographically weighted regression (GWR) model indicates that the building use data can well reflect the heterogeneity of urban geographic space. This method provides a relatively convenient and reliable idea for capturing high-precision population distribution, based on mobile phone and building use data. Numéro de notice : A2020-315 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060344 date de publication en ligne : 26/05/2020 En ligne : https://doi.org/10.3390/ijgi9060344 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95170 [article]

Improved 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)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 106 - 124 Titre : Improved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation Type de document : Article/Communication Auteurs : Eslam Ali, Auteur ; Wenbin Xu, Auteur ; Xiao-Li Ding, Auteur Année de publication : 2020 Article en page(s) : pp 106 - 124 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] correction des ombres [Termes descripteurs IGN] COSI-Corr [Termes descripteurs IGN] déplacement d'objet géographique [Termes descripteurs IGN] désert [Termes descripteurs IGN] désertification [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] dune [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image optique [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] incertitude des données [Termes descripteurs IGN] modèle d'inversion [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] prévention des risques [Termes descripteurs IGN] sable [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] SINAI [Termes descripteurs IGN] variation saisonnière [Termes descripteurs IGN] vent de sable Résumé : (auteur) Sand dune migration poses a potential threat to desert infrastructure, vegetation, and atmospheric conditions. Capturing the patterns of long-term dune migration is useful for predicting probable desertification issues and wind conditions across vast desert areas. In this study, we employed optical image matching and a singular value decomposition approach to estimate the rates of dune migration in the North Sinai Sand Sea using the free Landsat 8 and Sentinel-2 archives. Our optical image matching time-series selection and inversion (OPTSI) algorithm limited the difference in the solar illumination of correlated pairs to decrease shadows and seasonal variability. We found that the maximum annual dune migration rates were 9.4 m/a and 15.9 m/a for Landsat 8 and Sentinel-2 data, respectively, and the results of time-series analysis revealed the existence of seasonal variations in dune migration controlled by wind regimes. The directions of sand movement extracted from the mean velocity solution agreed strongly with each other and with the drift directions estimated using wind data from meteorological stations. We assessed the uncertainty of each solution based on the variance of stable areas. Our results showed that the proposed inversion decreased uncertainty by up to 25% and increased the spatial coverage by up to 20%. This algorithm is also promising for the retrieval of historical time series on the ground displacements of glaciers and slow-moving landslides employing free archives that provide high-frequency images. Numéro de notice : A2020-253 Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.04.004 date de publication en ligne : 27/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.04.004 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94997 [article]

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Visualizing 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)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 5 (May 2020) . - 14 p. Titre : Visualizing when, where, and how fires happen in U.S. parks and protected areas Type de document : Article/Communication Auteurs : Nicole C. Inglis, Auteur ; Jelena Vukomanovic, Auteur Année de publication : 2020 Article en page(s) : 14 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] aire protégée [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] Floride (Etats-Unis) [Termes descripteurs IGN] géodatabase [Termes descripteurs IGN] incendie de forêt [Termes descripteurs IGN] lutte contre l'incendie [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] parc naturel national [Termes descripteurs IGN] prévention des risques [Termes descripteurs IGN] réserve naturelle [Termes descripteurs IGN] variation saisonnière [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Fire management in protected areas faces mounting obstacles as climate change alters disturbance regimes, resources are diverted to fighting wildfires, and more people live along the boundaries of parks. Evidence-based prescribed fire management and improved communication with stakeholders is vital to reducing fire risk while maintaining public trust. Numerous national fire databases document when and where natural, prescribed, and human-caused fires have occurred on public lands in the United States. However, these databases are incongruous and non-standardized, making it difficult to visualize spatiotemporal patterns of fire and engage stakeholders in decision-making. We created interactive decision analytics (“VISTAFiRe”) that transform fire history data into clear visualizations of the spatial and temporal dimensions of fire and its management. We demonstrate the utility of our approach using Big Cypress National Preserve and Everglades National Park as examples of protected areas experiencing fire regime change between 1980 and 2017. Our open source visualizations may be applied to any data from the National Park Service Wildland Fire Events Geodatabase, with flexibility to communicate shifts in fire regimes over time, such as the type of ignition, duration and magnitude, and changes in seasonal occurrence. Application of the tool to Everglades and Big Cypress revealed that natural wildfires are occurring earlier in the wildfire season, while human-caused and prescribed wildfires are becoming less and more common, respectively. These new avenues of stakeholder communication are allowing the National Park Service to devise research plans to prepare for environmental change, guide resource allocation, and support decision-making in a clear and timely manner. Numéro de notice : A2020-298 Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9050333 date de publication en ligne : 20/05/2020 En ligne : https://doi.org/10.3390/ijgi9050333 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95138 [article]

A global analysis of cities’ geosocial temporal signatures for points of interest hours of operation / Kevin Sparks in International journal of geographical information science IJGIS, vol 34 n° 4 (April 2020)  

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Online flu epidemiological deep modeling on disease contact network / Liang Zhao in Geoinformatica [en ligne], vol 24 n° 2 (April 2020)  

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Spatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China / Mingyue Wang in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)  

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Integration of remote sensing and GIS to extract plantation rows from a drone-based image point cloud digital surface model / Nadeem Fareed in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)  

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Spectral–spatial–temporal MAP-based sub-pixel mapping for land-cover change detection / Da He in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)  

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Land use and land cover change modeling and future potential landscape risk assessment using Markov-CA model and analytical hierarchy process / Biswajit Nath in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)  

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Object‐oriented tracking of thematic and spatial behaviors of urban heat islands / Rui Zhu in Transactions in GIS, Vol 24 n° 1 (February 2020)  

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Spatio-Temporal Prediction of the Epidemic Spread of Dangerous Pathogens Using Machine Learning Methods / Wolfgang B. Hamer in ISPRS International journal of geo-information, Vol 9 n° 1 (January 2020)  

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Tree and stand level estimations of Abies alba Mill. aboveground biomass / Andrzej M. Jagodzinski in Annals of Forest Science [en ligne], vol 76 n° 2 (June 2019)  

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On constrained integrated total Kalman filter for integrated direct geo-referencing / Vahid Mahboub in Survey review, vol 51 n° 364 (January 2019)  

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